Crawlora MCP
OfficialServer Quality Checklist
Latest release: v1.14.0
- Disambiguation4/5
Tools are grouped by provider and granular object (search/detail/reviews), so most are clearly distinguishable by name plus description. With 1,164 tools, however, some families (e.g., the many google_finance_* and yahoo_finance_ticker_* variants) are numerous enough to risk misselection.
Naming Consistency4/5The naming is mostly consistent snake_case with a provider/domain prefix and a noun + operation structure (e.g., bestbuy_product_reviews, jobs_lever_postings). A few deviations like brand_retrieve, extract, web_scrape, and usage_* break the dominant pattern, so it is not perfectly uniform.
Tool Count2/51,164 tools is an extreme count for any MCP server, even for a multi-site scraping platform. While the breadth is intentional, it becomes a liability for agent performance and model context budgets, and could have been grouped into several smaller servers.
Completeness4/5The server is a read-only data extraction service, and for that purpose it provides comprehensive coverage: search, detail, reviews/photos, availability, related items, and datasets across dozens of sites. Small gaps exist (e.g., some live scrapers lack a corresponding historical dataset entry), but on the whole the surface matches the 'private pathfinder' title.
Average 3.8/5 across 1078 of 1164 tools scored. Lowest: 2.3/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 42 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
Tools from this server were used 2 times in the last 30 days.
This repository includes a glama.json configuration file.
This server has been verified by its author.
How to sync the server with GitHub?
Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, placing full burden on the description. It mentions 'normalized' results but does not explain what that means, nor does it disclose any behavioral traits such as data sources, pagination, or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short (two sentences) but lacks substantive detail. It is concise but at the expense of clarity and completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool with one parameter and no output schema, the description still fails to provide sufficient context. It does not explain the structure of results or how they differ from other search tools, leaving gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter 'q' described simply as 'Search query'. The description adds no extra meaning beyond the schema, but since coverage is high, a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5Does the description clearly state what the tool does and how it differs from similar tools?
The description says 'Google Finance context search' which is vague and not clearly differentiated from sibling tools like google_finance_search or google_finance_quote. The term 'context search' is ambiguous and doesn't specify what kind of results are returned.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus other Google Finance tools. There are many sibling tools with overlapping purposes, but the description gives no context for choosing this one.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must bear the full burden. It only says 'runs a query' without disclosing whether the tool mutates data, requires authentication, or has rate limits. The term 'constrained' is vague and not elaborated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (one sentence) but lacks essential details, making it under-specified. Front-loading is minimal; it does not structure information effectively for an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (nested object parameter, no output schema, many sibling tools), the description is insufficient. It does not explain how to construct the request, what the response contains, or how this tool fits into the broader set of Yahoo Finance tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'request' is an object with a schema description 'Custom screener request'. The tool description merely echoes this, adding no detail about the required fields, format, or constraints beyond the schema. With 100% schema coverage, the description should compensate but does not.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states it runs a 'constrained Yahoo Finance custom screener query' using a specific JSON shape, which gives a general sense of purpose. However, it does not clarify how this differs from the sibling tool 'yahoo_finance_screener' nor explain what 'constrained' means, reducing clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'yahoo_finance_screener' or 'yahoo_finance_screeners'. There is no mention of prerequisites, limitations, or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description should fully disclose behavioral traits. It only states it returns data, but does not mention rate limits, authentication requirements, or what happens on invalid queries. Minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences and no unnecessary words. It is well-structured, but could be slightly more informative without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a single parameter and no output schema, but the description is incomplete for full agent utility. It does not describe the output format or what 'SimilarWeb data' entails, and it does not address the sibling similarweb_web tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter 'q', so the schema already defines its meaning. The description adds 'typically a domain', which is marginally helpful. Baseline 3 is appropriate as the description adds little extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states it searches SimilarWeb info and returns data for a query (typically a domain). It is clear but vague, as 'SimilarWeb Info' is not specific. It fails to differentiate from the sibling tool 'similarweb_web', which likely provides more detailed or specific SimilarWeb data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like similarweb_web. Without explicit when-to-use or when-not-to-use instructions, the agent is left to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It only states that it returns calendar events, without any details on data freshness, pagination, rate limits, or authentication requirements. The minimal description does not adequately inform the agent of potential side effects or constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at two sentences, with the key verb and resource front-loaded. However, it sacrifices clarity for brevity, missing an opportunity to specify the event type.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the tool's simplicity (single parameter, no output schema), the description is incomplete. It does not clarify what 'calendar events' encompass, leaving ambiguity. Given the richness of sibling tools, more detail is needed for proper context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage (symbol parameter is described as 'Yahoo Finance symbol such as AAPL'). The tool description adds no additional meaning beyond the schema, matching the baseline score of 3 for full schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the verb 'returns' and the resource 'Yahoo Finance calendar events for a symbol', but it does not specify what kind of calendar events (e.g., earnings, dividends, splits). This vagueness makes it hard to distinguish from sibling tools like yahoo_finance_ticker_earnings or yahoo_finance_calendar_results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, scenarios, or exclusions, leaving the agent without context to choose appropriately among many similar finance calendar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits. It only states it returns data, with no mention of idempotency, auth needs, rate limits, or side effects. The return is vaguely described as 'modules'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
Short but somewhat redundant: both sentences essentially say the same thing. Could be more efficient by removing the first sentence or merging.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a single required parameter and no output schema, the description is minimally complete but fails to explain what 'earnings modules' are or what the output contains, leaving ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description for 'symbol'. The description adds no extra meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states it returns Yahoo Finance earnings modules for a symbol, which gives a verb and resource. However, 'earnings modules' is vague, and the description does not distinguish it from sibling tools like yahoo_finance_ticker_earnings_dates or yahoo_finance_ticker_calendar.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives among the many yahoo_finance_ticker_* siblings. It does not mention prerequisites, exclusions, or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states 'returns normalized eBay search results' without mentioning pagination, rate limits, authentication, or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short (two sentences) and front-loaded with purpose. It is not verbose, but could benefit from a structured format.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (search with nested object parameter, no output schema), the description is insufficient. It fails to explain return format, pagination, or how to construct the option payload.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'option' is an object with a vague description 'eBay search payload'. The description adds no further meaning about the payload structure, so the agent cannot infer required fields or format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches eBay listings and returns normalized results. It distinguishes from sibling tools like ebay_item and ebay_seller, but lacks detail on what normalization means or the scope of search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like ebay_item or ebay_search variants. The agent gets no help deciding which eBay tool to pick.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states what the tool does, not any behavioral traits like caching, rate limits, or whether the headline updates frequently. The description adds no value beyond the tool name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences but redundant—'Google Finance top headline' and 'Returns the top Google Finance headline' convey the same information. Could be condensed to one sentence without loss.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and simple function, the description could still explain what constitutes a 'top headline' (e.g., most recent, most shared). It lacks completeness for an agent to fully understand the tool's capability.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters, so the description need not explain any. Schema coverage is 100% vacuously. The description is adequate for parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states it returns the top Google Finance headline, providing a specific verb and resource. However, 'top headline' is ambiguous—does it mean the most recent, most popular, or something else? It distinguishes from siblings like 'google_finance_news' but lacks precision.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'google_finance_news' or 'google_finance_markets_category_news'. The agent must infer from the name alone, which is insufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the tool retrieves metadata but does not disclose whether it's read-only, authentication needs, rate limits, or what 'normalized' means. Minimal behavioral context beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences. The first sentence effectively states the action and resource. The second sentence is somewhat redundant but not overly verbose. Could be slightly improved by merging.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema is present, and the description does not hint at the structure of the returned metadata (e.g., fields like title, description, episodes). For a tool with optional parameters and no output schema, more context is needed for an agent to understand the response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with brief parameter descriptions, but the tool's description adds no value beyond those. It does not explain the purpose of the boolean parameters or provide examples. Parameter semantics are shallow.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool retrieves Spotify podcast show metadata from Spotify Pathfinder. It distinguishes from siblings like 'apple_podcasts_show' and 'spotify_podcasts_episode' by focusing on show-level for Spotify. However, it could be more specific about what metadata is included.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives like 'spotify_podcasts_search' or 'spotify_podcasts_show_episodes'. The description implies it's for a single show's metadata but does not provide when-not-to-use or mention alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for behavioral disclosure. It only states the function without revealing traits like data freshness, pagination, or limitations. This is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, consisting of two short sentences that convey the essential purpose. It is front-loaded and avoids unnecessary words, though it could be slightly more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 parameters, no output schema), the description is minimally adequate for purpose but lacks important context about behavior, usage, and output format. It is incomplete for informed agent selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for both parameters (region and count). The description does not add any additional meaning beyond the schema, so it meets the baseline but adds no value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns trending Yahoo Finance symbols for a region, which is specific and distinguishes it from other yahoo_finance tools like search or screener. However, it could be more precise about what 'trending' means (e.g., most active, gainers).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as yahoo_finance_market_summary, yahoo_finance_search, or other trending tools. The description lacks context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only mentions 'returns normalized Apple Podcasts episodes' without detailing traits like data freshness, rate limits, or limitations of the iTunes Search API. The term 'normalized' is vague and insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is succinct (one and a half sentences) but lacks structure. It front-loads the purpose but does not efficiently convey critical information like supported parameters or return behavior. Could be more informative without added length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters and no output schema, the description omits important context: what 'normalized' means, pagination behavior, or typical use cases. For a search tool with multiple sibling tools, this is incomplete and may lead to incorrect invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so all parameters have descriptions in the schema. The description adds no additional meaning beyond the schema, such as clarifying how 'country' or 'lang' affect results or how pagination works with 'limit' and 'page'. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Search Apple Podcasts episodes' with a verb and resource, clearly identifying the tool's function. However, it does not distinguish from sibling tools like apple_podcasts_search (which searches shows) or apple_podcasts_show_episodes, missing an opportunity to differentiate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as apple_podcasts_search or apple_podcasts_show_episodes. The description does not include any context about prerequisites, appropriate search scenarios, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, but it only mentions 'normalized rows' and 'public brand chart.' It does not disclose sorting behavior, default ordering, pagination, limits, or what fields the rows contain, leaving the agent without key operational detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only two sentences, but the first sentence 'Box Office Mojo brand chart' is a redundant restatement of the tool name, and 'brand chart' is repeated in the second sentence. It is short but not tightly written.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with two optional parameters, no output schema, and no annotations, this description is too thin. It lacks information about valid sort fields, result row structure, and how this differs from related Box Office Mojo tools, preventing confident invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage for both parameters, so the baseline is 3. The description adds no additional meaning beyond the schema's generic 'Sort field' and 'Sort direction,' and it does not clarify valid values or how they affect results.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states it 'Returns normalized rows from Box Office Mojo's public brand chart,' clearly identifying the resource and action. It does not explicitly distinguish itself from sibling tools like boxofficemojo_brand, but the plural 'brand chart' gives a reasonable sense of scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives such as boxofficemojo_brand, boxofficemojo_franchises, or other box office chart tools. The phrase 'brand chart' implies a use case but offers no exclusions or comparison.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description fails to disclose behavioral traits such as read-only nature, authentication needs, or data scope. It simply states it returns data, offering no transparency beyond the bare action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and concise, but it lacks structure and front-loading of key details. It is efficient in word count but sacrifices informative value, making it merely average in this dimension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the large set of sibling tools and no output schema, the description fails to provide a complete picture. It does not clarify what 'normalized company information' includes, leaving the agent without sufficient context to anticipate the return value.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the parameter 'quote' is described with an example. The description adds no additional meaning beyond what the schema already provides, meeting the baseline for parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states it returns normalized company information from Google Finance, identifying a specific verb and resource. However, it does not differentiate from many sibling tools like google_finance_quote or google_finance_ticker, which also return company data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. It does not mention context, prerequisites, or exclusionary criteria, leaving the agent without direction for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full behavioral disclosure burden. It only says 'Returns apps' without mentioning pagination, defaults, rate limits, or output structure. For a read-only listing tool, this is minimal and lacks transparency about non-obvious behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only two sentences, but the second sentence 'Returns apps from a Google Play collection and category' is largely redundant with the first. It is brief but wastes a sentence, earning a mid score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 8 optional parameters and no output schema, the description provides insufficient context about how collection, category, and filters interact, or what a typical invocation looks like. The schema helps, but the description leaves too many gaps for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for all 8 parameters, so the baseline is 3. The description itself does not add any parameter-level meaning beyond what is already in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves apps from a Google Play top collection, indicating the verb and resource. However, it does not explicitly distinguish this from other Google Play tools like googleplay_search or googleplay_categories, and 'top collection' is somewhat ambiguous without schema context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives such as googleplay_search or appstore_list. The description implies it is for top collections but provides no exclusions or alternative conditions, leaving usage decisions to the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should fully disclose behavioral traits. It only states the tool 'retrieves' permissions, implying a read operation, but does not confirm if it's safe (non-destructive), or mention rate limits, authentication, or output format details beyond the vague 'groups or list'. This is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (two sentences), which is concise but at the expense of completeness. It front-loads the core action but lacks detail needed for effective tool selection. For a tool with four parameters and no annotations, it is under-specified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (4 params, no output schema, no annotations), the description is incomplete. It does not explain what permission groups look like, how to interpret the output, or how the 'short' parameter affects the result. An agent would be left guessing the return format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds minimal value beyond the schema: it hints that 'short' returns a name list, but this is already in the schema. Benefits of other parameters (country, lang) are not elaborated, but they are self-explanatory.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Google Play app permissions and specifies two types of output (permission groups or short permission names). However, it does not explicitly differentiate from siblings like googleplay_datasafety or googleplay_app, which reduces clarity in distinguishing use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description does not mention prerequisites, typical use cases, or when not to use it. Given the many sibling tools, this omission is a significant gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description is the sole source for behavioral traits. It only discloses that an empty queries array may be returned when no results exist. It does not mention side effects, authentication needs, rate limits, or other behavioral aspects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, short but includes redundancy (first sentence restates the name). It is front-loaded with the purpose but could be more concise by removing the first sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex tool with a single nested object parameter and no output schema, the description is insufficient. It does not detail the request object's fields, expected format, or the response structure beyond mentioning a 'queries array'. Important context for an AI agent is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% description coverage but the description for 'request' is minimal ('Explore request'). The tool description adds that it expects 'one or more Google Trends explore terms', providing some semantic context, but does not explain the internal structure or additional fields. This is adequate but not rich.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns the Top related queries widget for one or more Google Trends explore terms. This distinguishes it from siblings like 'google_trends_explore_interest_over_time' or 'google_trends_explore_rising_queries'. The verb 'returns' and resource 'top queries' are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus other Google Trends explore tools. No prerequisites, context, or comparisons with alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions credential-free access and normalized data, which adds some behavioral context, but it does not disclose rate limits, pagination behavior, or any other operational traits beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short at two sentences, but the first sentence ('Kalshi trades.') is essentially a tautology of the tool name and could be removed. The second sentence is informative. Every word earns its place, but the structure could be improved.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, yet the description does not explain the structure of the returned trades. It mentions 'normalized recent ... trades' but lacks details on the response format, making it incomplete for an agent to fully understand the tool's output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with clear descriptions for all five parameters (cursor, limit, max_ts, min_ts, ticker). The tool description does not add extra meaning beyond the schema, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized recent Kalshi market trades, using a specific verb and resource. It mentions recency and credential-free access, which helps distinguish it from sibling tools like kalshi_historical_trades, though it could be more explicit about the differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives such as kalshi_historical_trades. The description hints at recency and credential-free access but does not provide clear context or exclusions, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only states 'Retrieve' and 'Returns', omitting any details about data volume, response format, authentication needs, or rate limits. The term 'core product details' is vague and doesn't explain what is included or excluded.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description uses two sentences that are nearly identical, creating redundancy. It could be more concise: e.g., 'Retrieve core Product Hunt product details by slug or numeric ID.' Every sentence should add unique value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and a large set of sibling tools, the description is incomplete. It does not explain what fields are returned, how to interpret the data, or how this tool differs from similar ones like producthunt_about. A user would need external documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the parameter 'id' is already described in the schema as 'Product Hunt slug or numeric ID'. The description adds no extra meaning beyond the schema, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Retrieve') and resource ('Product Hunt product details'). However, it doesn't differentiate what 'core product details' means, especially among siblings like producthunt_about or producthunt_alternatives. The redundancy in the two sentences slightly reduces clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., producthunt_about, producthunt_search, producthunt_reviews). There is no mention of prerequisites, when not to use it, or specific contexts. The description is entirely generic.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only mentions 'pagination', which is already evident from the schema parameters (page, per_page). It does not disclose output format, whether country is required, or any behavioral quirks. This is insufficient for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two sentences that largely repeat each other: 'List Ticketmaster discover cities.' vs 'Lists Ticketmaster city discovery destinations...'. It is short but redundant; a single well-constructed sentence would be more effective. Still, it is not overly verbose or disorganized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema and no annotations, so the description needs to explain what the tool returns and how it behaves. It does not define what a 'discover city' is, nor does it mention the shape of the response or any usage context beyond the raw parameters. For an agent to invoke this correctly, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, as every parameter (page, country, per_page) has a description. The description's mention of 'for a country' and 'pagination' merely echoes the schema without adding additional meaning, constraints, or examples. Baseline 3 is appropriate given high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb ('List') and resource ('Ticketmaster discover cities'), and clarifies scope with 'city discovery destinations for a country with pagination'. It reasonably distinguishes from the sibling tool ticketmaster_discover_city_events, which concerns events for a city. However, the phrase 'discover cities' is slightly non-standard, so it is not a perfect 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description only mentions 'for a country with pagination', which is a parameter hint rather than usage context. There are no exclusions, prerequisites, or recommended scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It only says 'returns rows' without mentioning pagination, rate limits, data freshness, or any side effects. For a tool with 7 parameters, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise but lacking structure. It front-loads the purpose but misses opportunities to provide quick-reference hints for parameters or usage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 7 parameters and no output schema, yet the description fails to explain the return format, pagination limits, or how parameters interact. For a calendar results tool, more context on date range handling and result ordering is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents each parameter. The description adds value by listing the event types but does not explain parameter relationships or constraints beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'global Yahoo Finance calendar rows for earnings, IPOs, economic events, or splits,' specifying both the resource and event types. However, it does not differentiate from siblings like 'yahoo_finance_calendars' or ticker-specific calendar tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The sibling list includes 'yahoo_finance_calendars' and numerous ticker-specific tools, but the description provides no context for choosing this one.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavior. It only says 'returns... summary rows' without details on market format, error handling, or output structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and front-loaded, but it lacks any additional structure or details that would earn its place beyond the basic purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, and only one parameter, the description should provide more context about the expected output or usage. It is insufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a description for 'market'. The tool description adds no extra meaning beyond 'Market such as US', so baseline score is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns market summary rows for a market, which is a specific verb and resource. It differentiates from siblings like yahoo_finance_market_status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like yahoo_finance_market_status or other search tools. No exclusions or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It only states it returns 'normalized public room details', but doesn't disclose behavior like error handling, rate limits, or whether the id must be a specific format. The description is minimal for behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, using one sentence to convey the core purpose. It front-loads the verb and resource. While it could be slightly expanded, there is no wasted content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description covers the basics. However, with many sibling tools, some context about when to use this over similar tools (e.g., airbnb_search, airbnb_room_calendar) would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description does not add any meaning beyond the schema's 'Room id' for the 'id' parameter. It is adequate but does not enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets an Airbnb room and returns normalized public details. It uses a specific verb and resource, and while it doesn't explicitly differentiate from siblings like airbnb_room_calendar or airbnb_room_reviews, the function is distinct enough for an agent to infer.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, context, or cases where other tools (e.g., airbnb_search) would be more appropriate. Agents are left to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only mentions 'returns normalized grouped rows', omitting details like pagination behavior (implied by the offset parameter), rate limits, authorization needs, or the nature of the source page. This is insufficient for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of two sentences that directly state the purpose and output. No redundant information, well-structured for quick parsing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of an output schema, the description's mention of 'normalized grouped rows' is too vague to inform the agent about the return format. The offset parameter suggests pagination but is not explained. The tool's role among many similar siblings is not clarified, leaving gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description for the offset parameter (allowed values) is clear and covers 100% of parameters. The tool description adds no extra meaning beyond what the schema already provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it deals with 'domestic release schedule changes' from Box Office Mojo, which distinguishes it from other calendar tools like boxofficemojo_calendar. However, it could be more specific about what constitutes a change (e.g., delayed, added, removed releases).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as boxofficemojo_calendar or boxofficemojo_calendar_date. The agent is left to infer the context without explicit when-to or when-not-to instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It mentions 'public' (implying no auth) and 'normalized rows' (implying some data cleaning), but it does not disclose behavior such as default sorting, result limits, pagination, or the meaning of 'normalized'. This leaves significant ambiguity for a data-retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences with no fluff. It front-loads the primary purpose ('Box Office Mojo franchise chart') and then adds a concise functional detail. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and minimal annotations, the description fails to convey what the returned rows contain, what the chart ranks, or how sorting interacts with the data. An agent would struggle to know if this tool fits its needs or how to interpret the results. Given the low complexity, some additional context was expected.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for both parameters, but the parameter descriptions are minimal ('Sort field', 'Sort direction') with no allowed values or format details. The tool description does not add any parameter semantics, so it meets the baseline of 3 but does not exceed it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized rows from Box Office Mojo's franchise chart, with a specific verb ('Returns') and resource ('franchise chart'). It does not explicitly differentiate from the singular sibling 'boxofficemojo_franchise', but the plural name and 'chart' phrasing imply a list vs. a detail endpoint.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives like boxofficemojo_franchise or other Box Office Mojo charts. There are no context cues or exclusions, so the agent must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior itself. It only says 'normalized rows' and 'public genre chart,' which offers minimal insight into what data is included, return format, sorting behavior, or limitations. No details on read-only nature, data freshness, or pagination are provided.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences and no filler. It is front-loaded with the key concept, though 'normalized rows' is slightly vague.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description should explain what the genre chart contains and how sorting works. It does not mention any filtering, pagination, or output structure, making it incomplete for effective invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with two parameters (sort and sortDir), both described in the schema. The description adds no additional parameter semantics, such as valid sort fields or formatting rules, so it provides baseline value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description states it returns normalized rows from Box Office Mojo's public genre chart, clearly indicating the resource and action. However, it does not distinguish between this plural genres tool and the sibling boxofficemojo_genre tool, leaving potential ambiguity about when each is appropriate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Sibling tools like boxofficemojo_genre, boxofficemojo_year_domestic, and datasets_boxofficemojo_search exist, but the description provides no exclusions, prerequisites, or selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It mentions 'credential-free' (good) and 'normalized rows', but fails to explain pagination behavior, sorting, or what the rows contain. The output format is entirely undocumented, which is a significant gap for a data retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at three short sentences, front-loading the purpose. Every sentence adds value: what the tool does, that it returns normalized rows, that it is credential-free, and the allowed area values. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (2 params, no output schema, no annotations), the description should explain the output format and pagination. It does not specify what fields the rows contain (e.g., rank, title, gross), nor how offset works. This leaves significant ambiguity for an AI agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters have descriptions in the schema (100% coverage), so baseline is 3. The tool description adds the 'credential-free' context but doesn't provide additional meaning beyond the schema. It lists area values but that duplicates the schema. Thus a 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized rows from Box Office Mojo's lifetime gross chart, and specifies the area parameter values. The tool name and description effectively convey it provides all-time gross data, distinguishing it from sibling tools like boxofficemojo_year_domestic. However, it doesn't explicitly differentiate from other chart tools, so a 4 is appropriate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as boxofficemojo_year_domestic or boxofficemojo_weekend_domestic. The description lacks any context about when to choose this tool over others, resulting in a low score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states it returns normalized rows and supports vs_currency. It does not disclose whether it is read-only, if authentication is needed, rate limits, pagination, or what 'normalized' implies. For a data retrieval tool, this is insufficient behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only two sentences, very short and to the point. It front-loads the purpose. However, it lacks structure (e.g., bullet points or sections) and could incorporate more detail without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool with no output schema and two parameters, the description covers the basic purpose and one parameter hint. However, it misses context like output format, pagination behavior, and what 'normalized' means. It is adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with both parameters described. The description adds only that vs_currency is an enum (documented elsewhere), which is marginal value. The limit parameter is fully covered in schema. Baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized chain rows from the CoinGecko public website chains table, which is specific and identifies the resource. However, it does not explicitly differentiate from the sibling tool 'coingecko_chain' (singular), which could be for a single chain. The verb 'Returns' is clear, but lack of sibling distinction prevents a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool vs alternatives like coingecko_chain for single chain details or coingecko_markets for market data. There is no mention of prerequisites, exclusions, or typical scenarios. The description only states what it does, not when to choose it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description must disclose behavioral traits. It only mentions 'normalized rows' which is vague. No info on sorting, pagination, data freshness, or rate limits. The tool's behavior regarding the two gainer/loser sections is unclear, and the output format is not described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact with two concise sentences. It avoids redundancy and gets directly to the point. However, it could be slightly more structured by separating purpose from parameter hints, but overall it is efficient with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with two parameters, no output schema, and no annotations, the description is too sparse. It omits output format, sorting, and any prerequisites. The agent lacks enough context to confidently choose this tool over similar ones, making it incomplete for effective decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters. The description adds value by noting that vs_currency supports a 'documented enum', which hints at valid values beyond the schema. However, it doesn't elaborate on limit or provide examples, so it only modestly enhances schema info.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns crypto gainers and losers from CoinGecko. The name 'coingecko_gainers_losers' and first sentence convey the core function. It distinguishes from siblings like coingecko_trending or coingecko_markets by focusing on gainers/losers, though not explicitly excluding other tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool vs alternatives such as coingecko_trending or coingecko_markets. There is no mention of when not to use it or what context suits it best. The description simply describes what it does without usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Only mentions 'normalized' and 'public JSON endpoints' but no details on rate limits, authentication, or output behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, no redundancy, but lacks front-loading of key info. Conciseness is appropriate for minimal info.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, no annotations, and description insufficient for a tool with three optional parameters. Missing details on return format, data source limitations, or usage examples.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%; description adds no extra meaning beyond parameter descriptions. Baseline score is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized global chart series from CoinGecko, distinguishing it from other coingecko tools like coin or categories. However, it doesn't explicitly differentiate from similar tools like coingecko_global.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like google_finance_chart or other chart tools. No mention of prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the full burden. It states the tool returns rows but lacks details on read-only nature, rate limits, pagination behavior, or error handling. Minimal behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no fluff. Front-loaded with purpose and includes a key detail about vs_currency. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema is provided, yet the description does not describe the return format or field structure. For a tool with 4 parameters returning 'normalized rows', more context on output fields is needed for an agent to interpret results correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents all parameters. The description adds no extra meaning beyond mentioning vs_currency enum support, which is in the schema. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized NFT collection rows from a CoinGecko NFT category page, specifying the resource and action. However, it does not explicitly differentiate this tool from similar siblings like coingecko_nfts or coingecko_category_coins, which could lead to confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. It implies use for NFT categories, but does not compare with other NFT-related tools or state any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It states the source (public website) and normalization, but does not discuss pagination behavior, data freshness, rate limits, or that the operation is read-only (though implied). The description is too sparse for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise with two sentences and no redundant information. However, it could be slightly more informative without becoming verbose, so it's efficient but leaves some gaps.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description fails to describe the return format or fields of the normalized rows. Given the presence of multiple NFT-related sibling tools, the description should clarify what distinguishes this tool (e.g., lists of collections vs market data). The current description is incomplete for an agent to fully understand the output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds minimal value by noting that vs_currency supports a documented enum, but does not elaborate on the parameter meanings beyond what the schema provides. The page and limit parameters are already clear in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool returns normalized NFT collection rows from CoinGecko's public website, using a specific verb and resource. However, it does not differentiate from sibling tools like coingecko_nft_category, which is a related but distinct tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions that vs_currency supports a documented enum, but provides no guidance on when to use this tool versus alternatives, nor does it specify when not to use it. There is no mention of prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It mentions sorting by distance and the dataset ID, but lacks disclosure on pagination behavior, authentication needs, rate limits, data freshness, or side effects of optional filters. The enumeration of influence_tier is merely a repetition of schema content.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no unnecessary words. The purpose is front-loaded. However, the second sentence is slightly cryptic ('in dataset id enum value') and could be clearer. Overall appropriate length for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, so description should explain return format. It does not mention what fields are returned, how results are paginated, or what 'enriched' means. With 8 parameters and no side-effect details, the description is incomplete for guiding the agent on proper usage and expectations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds minimal value beyond schema: it confirms sorting by distance and ties to a specific dataset. However, it does not explain optional parameters like reachable, min_followers, or clarify how 'enriched' applies. The influence_tier enum repetition is redundant.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches GitHub users near a coordinate, sorted by distance. The verb 'search' and resource 'enriched GitHub users' are specific. However, it does not explicitly differentiate from sibling tools like datasets_github_users_search or datasets_github_users_facets, though the context implies a geo-search specialization.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., datasets_github_users_search for non-geo searches, datasets_github_users_facets for aggregated data). The description does not mention prerequisites, contexts, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must fully convey behavioral traits. It only states it 'searches enriched public GitHub user profiles stored in a search index' but does not disclose read-only nature, rate limits, pagination behavior, or any side effects. The schema provides some details, but the description adds little transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at two sentences (30 words). It is front-loaded with the verb 'Search' but lacks structure or bullet points. No unnecessary words, but could be more organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 30 parameters, no output schema, and no annotations, the description is minimally adequate. It does not explain return format, pagination constraints, or limitations. For a complex search tool, more context is needed for complete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (all 30 parameters have descriptions). The description lists enums for influence_tier and sort, but these are already in the schema. It does not add new meaning or clarify parameter usage beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches the GitHub users dataset and searches enriched public GitHub user profiles. The verb 'Search' and resource 'GitHub users dataset' are specific. It does not explicitly distinguish from sibling search tools like datasets_github_users_facets, but the name and description make the purpose clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of when not to use it or differentiation from other datasets_* tools. The description lacks any usage context or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only mentions that it returns terms aggregation counts and lists the facet enum, but does not explain response structure, how optional filters interact with the aggregation, or any edge cases like invalid facet values or bucket limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of two short sentences. Every word contributes meaning, and it gets straight to the point without unnecessary filler. The front-loaded phrasing makes the tool's purpose immediately clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 7 parameters, no output schema, and no annotations, the description is insufficiently complete. It does not explain the return value structure, nor does it clarify how filtering parameters (q, name, genre, etc.) affect the facet counts, leaving the agent without enough context to predict the tool's behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description merely repeats the facet enum already present in the schema and adds no new meaning about parameter interactions or usage. As a result, it does not elevate beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool facets the Goodreads authors dataset and returns terms aggregation counts, which conveys a specific verb and resource. It distinguishes itself from sibling datasets_*_search and datasets_*_item tools by focusing on aggregation counts, although it does not explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus the sibling search or item tools. The description implies a use case (getting facet counts) but does not state any exclusions, prerequisites, or alternative tool recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It correctly states read-only, but does not elaborate on caching, update frequency, or what 'capabilities supported' means. The term 'capabilities' is vague and lacks detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two short sentences. It front-loads the main action 'List stored scraped datasets' and adds a clarifying second sentence. No redundant or extraneous content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description should explain the return format. It mentions 'capabilities supported' but does not describe what that includes or how the data is structured. The agent is left guessing the output shape, which is insufficient for a tool with no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, and schema description coverage is 100% trivially. The description adds no parameter meaning beyond the schema, but baseline is 3 per instructions for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and the resource 'stored scraped datasets', and specifies 'read-only'. It distinguishes from sibling dataset-specific tools by indicating it provides an overview of available datasets. However, it could be more explicit that this is the top-level listing tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus sibling tools like datasets_airbnb_search or datasets_google_map_facets. It does not mention that this tool is useful for discovering available datasets before querying specific ones, nor does it state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavioral traits. It mentions the dataset source and sort enums but fails to state that the tool is read-only, pagination behavior (though schema has page/page_size), or what the return format is. Significant gaps for a 13-parameter search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (two sentences plus enum list) with no redundant information. It is front-loaded and efficient, though the structure could be improved by grouping sort values more clearly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 13 parameters, no output schema, and no annotations, the description is insufficient. It explains the dataset source but does not describe output format, filter behavior, or index meanings. Many details are missing for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already describes each parameter. The description merely repeats sort enum values already in the schema, adding no extra meaning or context for filtering parameters. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches a composite Numbeo countries dataset with seven index families. The purpose is specific and differentiated from sibling tools like datasets_numbeo_cities_search by name, though it does not explicitly contrast with alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this tool versus alternatives, such as city-level search or single-country retrieval, nor does it mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses the return type ('terms aggregation counts') and the available facet fields, but doesn't mention how filters (q, run_id, etc.) affect aggregations, whether pagination exists, or that this is a read-only operation. This is minimal behavioral disclosure for a data aggregation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is precisely two sentences, front-loaded with the primary purpose and the facet enum list. There is no filler or redundant phrasing, making it highly efficient for its content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 7 parameters, 1 required, and no output schema. The description explains the core purpose but doesn't clarify how filter parameters interact with the aggregation, what the returned counts look like, or any additional constraints. Given the lack of annotation support, the description is too sparse for a complete understanding of invocation behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters. The description's facet enum list duplicates the schema's property description, adding no new meaning. The baseline of 3 applies since the description doesn't need to compensate for schema gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the function: 'Facet PitchBook funds dataset' and 'Returns terms aggregation counts'. It identifies the specific dataset (PitchBook funds) and the operation (facet aggregation). Although it doesn't explicitly contrast with sibling search/item tools, the name and wording unambiguously indicate a faceting endpoint.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit usage guidance is given. The description implies the tool is for obtaining facet counts but doesn't state when to prefer it over siblings like datasets_pitchbook_funds_search or datasets_pitchbook_funds_item. There's no mention of alternatives or exclusion scenarios, leaving the agent to infer usage from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It conveys that the tool performs a search over a catalog in a search index, implying a read-only operation. It also lists enum values for price_tier, review_tier, and sort. However, it does not disclose pagination behavior, result limits, or return format beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short but contains redundancy: 'Search the Steam games dataset' and 'Searches enriched public Steam catalog records' say essentially the same thing. The enum lists are repetitive with the schema but useful. Overall, it's acceptable but not tightly written.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 29 parameters and no output schema, the description is sparse. It doesn't explain what a search result looks like, how results are ordered (beyond sort enums), or any constraints like the offset limit. The schema covers parameters well, but the description lacks return-value context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the description merely repeats the enum values already present in the schema (price_tier, review_tier, sort). It adds no new parameter semantics beyond what the schema provides, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies this as a search tool for the Steam games dataset, using the verb 'Search' and specifying the resource as 'enriched public Steam catalog records stored in a search index.' While it doesn't explicitly contrast with sibling tools, the name and description make it distinct from facet/item tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. There is no mention of when to prefer this over other Steam dataset tools (e.g., facets, item), nor any exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It mentions searching a search index but omits details like pagination behavior, rate limits, authentication, or output format. The sort options are listed but already in schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively concise at two sentences. It front-loads the main action and lists sort options efficiently, though it could be slightly more structured with bullet points or sections.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 17 parameters and no output schema, the description is too minimal. It does not explain pagination constraints, result format, or how the search index works. The sibling tool names suggest a related item tool exists, but this connection is not clarified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All 17 parameters have schema descriptions (100% coverage), so the description adds minimal new meaning. The description redundantly lists sort enum values. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches the X users dataset and searches public X user profiles. However, it does not explicitly differentiate from sibling tools like datasets_x_users_facets or datasets_x_users_item, relying on the name to indicate search functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as datasets_x_users_facets or datasets_x_users_item. The description implies general search usage but lacks explicit context for choosing this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description only states it is a read operation ('get', 'returns'). No disclosure of rate limits, authentication needs, or data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, no unnecessary words. Could potentially combine, but it is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is adequate for a simple one-parameter tool, but without an output schema, it would benefit from specifying what 'normalized details' include (e.g., seller name, feedback score).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear parameter description ('eBay seller username'). The tool description does not add extra meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it gets an eBay seller profile and returns normalized details. It is specific but does not explicitly distinguish from sibling tools like ebay_seller_about or ebay_seller_feedback.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as ebay_seller_about, ebay_seller_feedback, or ebay_seller_shop.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It mentions rate limiting for unauthenticated requests but fails to specify authentication options, return structure, pagination behavior, or error handling. This is insufficient for a search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise with two sentences, clearly stating purpose and a key constraint (rate limit). No unnecessary words, well front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description is too sparse. It lacks information on what fields are returned, how pagination works, and any prerequisites. For a search tool with five parameters, this is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All parameters are described in the input schema (100% coverage), so the description adds no additional meaning. It does not clarify search query syntax or valid sort/order values. Baseline 3 is appropriate given schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches public GitHub users and mentions developer discovery, which directly corresponds to the tool name. However, it does not differentiate from similar user search tools like dataset_github_users_search, though the purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as github_user for individual profiles or github_search_repositories. The only usage hint is the rate limit, which is more of a constraint than a usage guideline.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description simply states the tool returns trending developers. It does not disclose whether the tool is read-only, if there are pagination limits, or any other behavioral traits. Minimal transparency beyond the core action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single efficient sentence with a clarifying parenthetical. It is concise and front-loaded, though extremely brief.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description should elaborate on the returned data format or structure. It only vaguely states 'returns the developers,' which is insufficient for an agent to understand what fields or information will be provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema describes both parameters (since and language) with appropriate descriptions. The tool description adds no additional meaning beyond the schema, so baseline score of 3 applies given 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists trending GitHub developers and specifies it comes from GitHub's trending page. However, it does not explicitly differentiate from sibling tools like github_trending, though the name implies the distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like github_trending (which likely lists repositories). There is no mention of when not to use it or any context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It states 'returns normalized analyst article results' but does not disclose any behavioral traits such as readonly nature, authentication requirements, or rate limits. Minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no filler. Front-loaded with tool name and purpose. Efficient, though slightly under-specified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (1 required param, no output schema), the description is minimally adequate. It explains the tool's output (normalized analyst articles) but lacks details on result structure or additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter (quote) that already includes a description ('Quote identifier such as AAPL:NASDAQ'). The description adds no additional meaning beyond what the schema provides, so baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns analyst article results for a quote, distinguishing it from other finance tools like news or quotes. The verb 'returns' and resource 'analyst articles' are specific, but it does not explicitly differentiate from siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like google_finance_news. The description lacks context for appropriate use cases or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must convey behavioral traits. It states the tool returns data and accepts a window, but lacks details on data granularity (e.g., intraday for '1d'), rate limits, or whether the data is historical or real-time. This leaves the agent uncertain about the exact behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise with two short sentences and no unnecessary words. However, the structure could be improved by front-loading the main action and using a clearer format.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description should explain the return format, but it only says 'normalized chart points' without specifics (e.g., fields like date, open, high, low, close, volume). The tool has many siblings, but no differentiation is provided. The description feels incomplete for an agent to fully understand usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with both 'quote' and 'window' already described in detail. The description merely echoes these parameters without adding new meaning, so it meets the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns 'normalized chart points for a quote and window,' indicating a specific verb and resource. It distinguishes from other google_finance tools like google_finance_quote (which likely returns current data) by specifying chart data. However, it doesn't define 'normalized chart points' or the output format.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as yahoo_finance_ticker_history or google_finance_company. There are no usage conditions, exclusions, or context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool returns normalized classification strings but lacks details on data freshness, API limits, authentication needs, or what 'normalized' means. Behavioral traits beyond the basic action are absent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently conveys the core function. However, it could be slightly expanded to include context without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema and the large set of similar sibling tools, the description is incomplete. It does not hint at the output format or how this classification data differs from other google_finance endpoints like google_finance_quote.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes the lone parameter ('quote') with a clear example. The description adds no additional meaning beyond the schema. Since schema coverage is 100%, baseline is 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool returns normalized classification strings for a quote, using a specific verb ('Returns') and identifying the resource ('classification data'). It distinguishes itself from sibling google_finance tools by focusing on classification, but does not elaborate on what classification entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus other google_finance tools. There are many siblings (e.g., google_finance_quote, google_finance_ticker), but no comparison or exclusion criteria are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It only mentions 'normalized news' without explaining what normalization entails. No disclosure of auth, rate limits, or data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise with two short sentences, no redundancy or unnecessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity and lack of output schema, the description might suffice, but it fails to explain what constitutes a valid category id or how to obtain it, which is crucial for parameter usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions. The description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized news for a Google Finance category, matching the tool name. However, it does not differentiate from sibling tools like google_finance_news or google_finance_markets_headline, which could cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus other news tools (e.g., google_finance_news, google_finance_analyst_articles). No prerequisites or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must carry the full burden. It only says 'returns normalized instruments' without explaining behavior like pagination, rate limits, or whether it's read-only. This is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise at two sentences. No wasted words. The first sentence repeats the tool name, but the second adds value. Benefit of the doubt for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given only 2 parameters and no output schema, the description is adequate but missing context on what 'normalized instruments' means and how offset works. Could be more helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description does not add additional meaning beyond the schema's parameter descriptions. The schema already documents 'category' and 'offset' adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns normalized instruments for a Google Finance category. The verb 'returns' and resource 'category stocks' are specific. It distinguishes from siblings like google_finance_markets_category_news which returns news.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. The description does not mention when to use it or any prerequisites. Context from sibling tools is not leveraged.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry full burden. Only says it returns data, but no mention of side effects, authentication, rate limits, or data freshness. The term 'normalized' is vague. Minimal behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences are concise and front-loaded. No wasted words, but may be too brief for adequate clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description should provide more detail on the returned data structure and scope. 'Normalized earnings calendar instruments' is insufficient for an agent to understand what to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has no parameters and coverage is 100%, so baseline 3. Description adds 'normalized earnings calendar instruments' but does not explain what that entails. No additional meaning beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a Google Finance earnings calendar and returns normalized earnings calendar instruments. The verb 'returns' and resource are specified. However, it does not differentiate from sibling tools like yahoo_finance_calendar or other finance calendars.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., yahoo_finance_ticker_earnings or google_finance_quote). No context on prerequisites or expected usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only states it returns normalized top instruments, but does not mention any limitations, pagination behavior, data freshness, or required permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences that are front-loaded with the purpose. Every sentence is essential and there is no wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no sibling differentiation, the description is incomplete. It lacks information about return format, data quality, and how it fits among similar tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with both parameters described ('Google Finance metric id' and 'Page number'). However, the description adds no extra context beyond the schema, such as possible metric IDs or pagination defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized top instruments for a Google Finance metric, specifying the verb 'returns' and the resource 'top instruments'. It distinguishes from siblings like 'google_finance_markets_movers' by focusing on metric-specific rankings, but lacks detail on what metrics are available.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like google_finance_markets_movers or google_finance_markets_trending. There are no usage conditions or exclusions provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits fully. It only says 'Returns normalized trending instruments' without explaining update frequency, data source, what 'normalized' means, or any side effects. Lacks critical context for safe usage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two short sentences with no fluff. It front-loads the purpose and is well-structured for quick parsing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and low parameter count, the description should compensate with more details about the returned data (e.g., what fields are included, order, limits). It fails to provide enough context for an AI to fully understand what the tool returns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'limit' has a description in the schema ('Result limit'), covering 100% of parameters. The tool description adds no further explanation or examples, so it meets the baseline but does not enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'Google Finance trending stocks' and mentions 'normalized trending instruments', which distinguishes it from other Google Finance tools like featured, movers, or top. The purpose is specific and understandable, though the term 'normalized' could be more explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool over alternatives such as google_finance_markets_featured, google_finance_markets_movers, or google_finance_markets_top. The description does not provide context about suitable use cases or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behaviors like authentication, rate limits, or data freshness. It only says 'parsed from public Google web responses', which is vague.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, succinct and front-loaded. Could include more detail without being verbose, but currently no waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Lacks output schema and description of return values. Does not explain what 'normalized' means or handle error cases. Incomplete for a tool with a complex object parameter.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% since the only parameter 'option' is described. However, the description adds no extra detail about the expected payload structure beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches Google Jobs and returns normalized results. It distinguishes from general search tools like google_search, but could be more specific about what Google Jobs entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives, nor any prerequisites or limitations. The agent must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It only says 'Retrieve apps' and 'Returns apps' without disclosing limitations, rate limits, error behavior, or output structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that directly state the purpose and outcome with no extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having 5 parameters and no output schema, the description is very minimal. It lacks details on return format, pagination, error handling, and edge cases, making it insufficient for a data retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents all parameters. The description adds no additional meaning or constraints beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves apps by Google Play developer using developer ID or name. It distinguishes from siblings like googleplay_search and googleplay_app but does not explicitly differentiate from similar tools like googleplay_list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like googleplay_search or googleplay_list. No prerequisites or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description notes that an empty array is returned when Google returns no topic rows, which is helpful. However, it does not disclose other behavioral traits (e.g., idempotency, latency, authentication requirements) in the absence of annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (two sentences) and front-loaded with the primary purpose. No redundant information, though it could benefit from more structured parameter details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the nested input object with no schema definition, the description should provide more context on the request structure. The mention of 'term/filter combination' is insufficient for an agent to construct a valid input. No output schema is present, so the description should compensate but does not.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema's 'request' parameter description is generic ('Explore request'), and the tool description adds only a hint about 'term/filter combination' without specifying the object's structure. With 100% schema coverage but minimal descriptions, the description adds limited semantic value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns the 'related topics widget' from the Google Trends Explore widget flow, which differentiates it from sibling tools like interest over time or top queries. It also mentions handling empty results, reinforcing the purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., other google_trends_explore_* tools). No prerequisites, exclusions, or typical use cases are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Minimal behavioral disclosure beyond basic function; no mention of side effects, authentication, rate limits, or read-only nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, efficient and no wasted words, but could include more useful information without adding length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Incomplete: fails to explain structure of the request object, which is critical for using the tool, despite covering empty result edge case.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single 'request' parameter is vaguely described as 'Explore request' with no added meaning about expected properties, despite 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly specifies it returns 'Rising related queries widget' for explore terms, distinguishing it from sibling tools like google_trends_explore_top_queries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives; among many Google Trends explore tools, no exclusions or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose all behavioral traits. It only states the output (episodes and offers) but omits any side effects, rate limits, authentication needs, or data range constraints. For a data retrieval tool, more transparency about scope and limits is needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence that efficiently states the purpose and includes an example ID format. It is concise without being overly terse, though could be improved with structuring or bullet points.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with well-documented parameters and no output schema. However, the lack of usage guidelines and behavioral transparency leaves gaps. It is minimally acceptable for a straightforward tool but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters are fully described in the schema (100% coverage). The description adds no additional meaning beyond the schema. Since coverage is high, baseline is 3, and no extra value is provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves 'JustWatch season episodes' and its output includes episodes and normalized episode offers. It provides an example ID format for clarity. While it doesn't explicitly distinguish from siblings like justwatch_episode_by_id or justwatch_season_by_id, the resource (season episodes) is specific enough.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as justwatch_episode_by_id (for a single episode) or justwatch_show_seasons (to get season list). The description lacks any context about prerequisites or preferred use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description fully responsible for behavioral disclosure. It notes the tool is credential-free, which is a key trait. However, it does not mention that it is read-only (implied from public data but not explicit), rate limits, data freshness, or response format limitations. Lacks transparency for a data retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, no redundant words. Front-loaded with tool name and output description. However, it is almost too concise, lacking details that could be added without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 9 parameters, no output schema, and many similar siblings, the description is insufficient. It does not explain what 'normalized' means, what fields are returned, or how the filters in the schema interact. Without an output schema, more explanation is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (all 9 parameters described in input schema). The description adds no additional parameter meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
States that the tool returns 'normalized Kalshi event rows' from credential-free public data. Clearly identifies the resource (events) and action (returns rows). However, does not distinguish from sibling tools like kalshi_event (singular) or kalshi_event_history, leaving ambiguity about whether it lists events.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Mentions 'credential-free public market-data' implying use for public data, but provides no explicit guidance on when to use this tool versus alternatives like kalshi_event, kalshi_event_history, or other event-related tools. No when-not-to-use or prerequisites stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It mentions 'credential-free public market-data JSON', which is useful, but lacks details on rate limits, error handling, or side effects of the operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two short sentences, front-loading the core purpose. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema is provided, and the description does not specify the format or fields of the returned row. Also missing error behavior. For a detail tool, more context about the output would be expected.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'series_ticker' is described in the schema as 'Kalshi series ticker'. Schema coverage is 100%, so the description adds no meaningful extra context beyond the schema. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns 'one normalized Kalshi series row' from public data, specifying verb and resource. However, it does not differentiate from sibling tools like kalshi_series, which may also return series data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., kalshi_series, kalshi_event). The description only states what it does, not when it is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the burden of disclosing behavior. It states 'Returns detailed company information' but does not specify whether the operation is read-only, any authentication requirements, or potential limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, using two short sentences that front-load the core purpose. No extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple lookup tool with one parameter, the description is adequate but lacks specificity about the returned data fields (e.g., name, industry). Given no output schema, more detail would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter 'id', which is already documented as 'LinkedIn Company ID'. The description adds no additional meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves LinkedIn Company information by ID, specifying both the verb 'Get' and the resource. However, it does not differentiate from sibling tools like linkedin_product or linkedin_showcase.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternative tools such as linkedin_product or linkedin_showcase. There is no mention of prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It mentions 'credential-free public Gamma' but lacks details on rate limits, error handling, or the meaning of 'normalized'. The behavior beyond fetching data is opaque.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exceptionally concise, using only two sentences without extraneous words. Every part contributes to understanding the tool's purpose and result.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description offers minimal detail on the return value ('related tag rows'). It fails to specify the structure or fields of the response, leaving the agent with incomplete context for processing results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions for each parameter. The description adds no extra meaning beyond the schema, fulfilling the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves related tags by ID, specifying the source and that it returns normalized rows. However, it does not explicitly distinguish itself from sibling tools like 'polymarket_tag' or 'polymarket_tags', leaving room for ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'polymarket_tag' (single tag) or 'polymarket_tags' (all tags). The agent must infer the specific use case from the name 'related_tags'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It states it returns 'detailed review items' but omits details about pagination, rate limits, or what 'detailed' implies. This is insufficient for a tool with no additional metadata.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences front-loading the action. It wastes no words but could potentially include more detail without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema), the description is minimally adequate. It indicates the return type ('detailed review items') but does not specify fields or structure, which would be helpful for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers the single parameter 'id' with description 'Product Hunt slug'. The description does not add extra meaning beyond the schema, so baseline 3 is appropriate given 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the verb 'retrieve' and specifies the resource 'Product Hunt product detailed reviews', making the purpose clear. However, it does not differentiate from sibling tools like producthunt_product or producthunt_about, which reduces differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives (e.g., producthunt_search for general search). No exclusions or context about appropriate scenarios are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full burden for behavioral disclosure. It only states 'Returns normalized products' without mentioning pagination behavior, rate limits, data freshness, or whether private collections are excluded. The presence of page/limit parameters implies pagination, but the description doesn't confirm this.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, immediately stating the tool's purpose in the first sentence. No unnecessary words or redundancy. Every sentence adds value: the first states what it does, the second explains the data source and normalization.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and 4 parameters, the description lacks details about the return format, pagination (though implicit via parameters), and what 'normalized products' means. It does not explain that only public collections work or how the URL should be structured. The description is too brief for confident use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and each parameter has a clear description in the schema. The tool description adds no additional meaning beyond what the schema already provides, so a baseline score of 3 is appropriate. No extra context like parameter formatting or examples is given.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with 'List Shopify collection products,' clearly stating the action and resource. It further specifies that it returns normalized products from a public Shopify collection endpoint. However, it does not explicitly differentiate this from sibling tools like shopify_products, which also lists products but not from a specific collection.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal guidance on when to use this tool versus alternatives. It mentions the endpoint but lacks context on prerequisites (e.g., need a public collection) or when shopify_products would be more appropriate. No exclusions or when-not-to-use information is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description fails to disclose behavioral traits such as authentication requirements, rate limits, side effects, or error handling. 'Private Pathfinder responses' is unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences. However, 'private Pathfinder responses' adds unnecessary jargon without explanation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, so description should detail return structure. It only mentions 'metadata and tracks' vaguely. Also, all parameters optional but no defaults or behavior specified when none provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% so the schema already documents all parameters. The description adds no extra meaning beyond what is in the schema, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves Spotify album details and mentions returning metadata and tracks, distinguishing it from sibling tools like spotify_album_tracks. However, 'private Pathfinder responses' is vague and could be confusing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like spotify_album_tracks or spotify_albums_search. Missing when-not-to-use and context for parameter selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It states 'Retrieve' implying a read operation, but does not mention authentication, rate limits, error handling, or what happens if the artist is not found. The vague reference to 'private Pathfinder responses' adds no clarity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences with no wasted words. It could be slightly improved by front-loading the purpose more explicitly, but it is already concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description should hint at the return structure. It only says 'normalized Spotify Web Player artist overview data', which is vague. It does not mention key fields, pagination, or error conditions, making it incomplete for a tool with no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear descriptions for uri and id. The description does not add further meaning beyond the schema, such as how to choose between parameters or what happens if both are provided. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Retrieve Spotify artist details' and specifies the data source (normalized Spotify Web Player artist overview data from private Pathfinder responses). However, it does not explicitly differentiate from sibling tools like spotify_artist_albums or spotify_artist_playlists, but the mention of 'overview data' implies a general artist info endpoint.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives (e.g., spotify_artist_albums, spotify_artist_related). There is no mention of when to use it or when not to use it, which is a significant gap given the many sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must disclose behaviors. It only mentions 'Retrieve,' implying a read operation, but fails to describe auth requirements, rate limits, or the meaning of 'private Pathfinder responses.' The behavioral traits are insufficiently explained.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (two sentences) and front-loaded with the primary action. The second sentence adds jargon but no waste. It earns its brevity, though it could include more substance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and 6 optional parameters, the description should explain the return format and clarify that either uri or id is needed. It does not, leaving important usage gaps. The sibling tool list is large, and no cross-references are provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all 6 parameters, so the description adds minimal value. It does not elaborate on default values or combined usage of uri and id, but the schema is sufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves artist albums and returns discography items. However, it includes confusing jargon ('Spotify Web Player private Pathfinder responses') and does not differentiate from sibling tools like spotify_artist_playlists or spotify_artist_related.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as spotify_albums_search or spotify_artist. No exclusions or context for appropriate use are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry full burden. It hints at private source and show URI association, but lacks details on side effects, authentication, rate limits, error handling, or response format. For a data retrieval tool, more behavioral context is needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each serving a purpose: stating action, source, and domain fact. No superfluous words, but could potentially combine sentences for tighter structure. Still, good conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and many sibling tools, the description should clarify that this tool retrieves metadata for a specific audiobook by URI/ID, and that search or chapter tools are for other tasks. It does not provide enough context for an agent to reliably select it. Vague on output ('audiobook metadata').
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and parameter descriptions are already clear. The description adds the insight that audiobooks are exposed through show URIs, which ties parameters to the domain, but does not significantly enhance meaning beyond what's in the schema. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Retrieve Spotify audiobook details' as a specific verb+resource. It mentions the source (private Pathfinder responses) and that audiobooks use show URIs. However, it does not explicitly differentiate from sibling tools like spotify_audiobook_chapters or spotify_audiobooks_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Does not mention search tools for finding audiobooks or chapter retrieval. Agent receives no context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits, but it only mentions the internal operation. It lacks details on what happens with multiple parameters, required permissions, or any side effects, leaving the agent underinformed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences and no wasted words. However, it could be restructured to front-load the essential action and clarify the tool's scope relative to siblings.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (2 optional params, no output schema) and the large set of similar sibling tools, the description is insufficient. It lacks usage guidance, parameter interaction details (e.g., exclusive or optional), and behavioral transparency, making it incomplete for reliable agent selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema descriptions already cover both parameters (uri and id) with clear meaning. The description adds no new semantic nuance beyond the schema, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Spotify audiobook chapter details, using a specific verb and resource. However, it does not differentiate from similar siblings like spotify_podcasts_episode or spotify_track beyond the mention of 'audiobook chapter'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. The vague reference to the 'private Pathfinder operation' offers no actionable usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states 'returns normalized Spotify Web Player episode search results' without explaining pagination, rate limits, ordering, or what 'normalized' entails. The clamped limit behavior is in the schema but not elaborated in the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise at two sentences, with no redundant words or unnecessary information. It front-loads the action and resource effectively.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so the description should at least hint at the structure of returned data (e.g., list of episodes with metadata). It only says 'returns normalized... search results', which is vague. Given the tool's complexity and lack of annotations, the description is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are already documented. The description adds no additional meaning beyond what the schema provides (e.g., 'search term', 'offset', 'limit'). The meaning of 'q' as a search term is obvious, but no further clarification is given.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches Spotify episodes and returns normalized results from the Spotify Web Player. It specifies the resource ('episodes') and action ('search'), which distinguishes it from sibling tools like spotify_podcasts_search (podcasts) and spotify_shows_search (shows). However, it does not explicitly contrast with similar search tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as spotify_podcasts_search or spotify_search. The description lacks any context about suitable scenarios, prerequisites, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It only states 'returns normalized podcast episodes' without describing pagination behavior, error handling, rate limits, or what 'normalized' means. Minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two succinct sentences with no redundancy. Every word serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, so description should explain return structure. 'Normalized podcast episodes' is vague. Does not mention that it returns a list, typical fields, or how to interpret results. Incomplete for a tool with 4 parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description does not add any extra meaning beyond the schema; it merely restates the purpose. No explanation of default values, constraints, or interactions between parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Retrieve' the resource 'Spotify podcast show episodes' and specifies the input (show URI). It distinguishes itself from sibling tools like spotify_podcasts_show (which returns show details) and spotify_episodes_search (which searches episodes), but does not explicitly differentiate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like spotify_episodes_search or spotify_podcasts_episode. There is no mention of prerequisites, use cases, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description mentions 'Retrieve' implying a read operation but does not explicitly confirm non-destructive behavior, authentication needs, or error conditions. Minimal transparency beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, no extraneous information. Very concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Lacks output schema and does not describe the return format beyond 'normalized items'. The term 'browse section' is not defined. Incomplete for a data-retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with clear descriptions for each parameter. The tool description adds no additional meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a Spotify browse section and returns normalized items. It distinguishes from siblings like spotify_playlist or spotify_search by targeting 'browseSection Pathfinder response'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., spotify_home, spotify_genre). The description only states what it does, not when it's appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; the description only states it searches and returns normalized results. It does not disclose authentication needs, rate limits, pagination behavior, or what 'normalized' means, leaving significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. It is concise but could be slightly more informative without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite 100% schema coverage and no output schema, the description lacks details on return format or normalization. For a simple search tool with pagination parameters, it is minimally complete but could be improved.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with parameter descriptions for 'q', 'offset', and 'limit'. The description adds no additional meaning beyond the schema (e.g., 'search term' is already in schema), so baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches Spotify shows and returns normalized results from the Spotify Web Player. The verb 'search' and resource 'shows' are specific, and it is distinguishable from general 'spotify_search' but could differentiate more from 'spotify_podcasts_search'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus sibling tools like 'spotify_podcasts_search' or 'spotify_search'. The purpose is implied but no exclusions or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavioral traits. It mentions a source ('internalLinkRecommenderTrack Pathfinder') but fails to describe safety (e.g., read-only?), authentication, rate limits, or whether it mutates state. This is insufficient for transparent decision-making.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loading the core purpose. The second sentence adds technical detail about the data source. While every sentence earns its place, the second could be clearer about output format. Overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and 3 parameters with no required fields. The description says 'returns normalized recommended Spotify entities' but does not specify what fields those entities contain, nor that at least one of 'uri' or 'id' is needed. For a recommendation tool, more detail on return format is expected.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters have descriptions in the JSON schema (100% coverage). The tool description does not add new parameter-specific context. The baseline of 3 applies since the schema already documents each parameter, though the description could clarify the relationship between 'uri' and 'id' (e.g., that one is expected).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Retrieve Spotify recommended tracks', which is a specific verb+resource. While it doesn't explicitly differentiate among the many Spotify tools, the name and focus on recommendations make its purpose distinct from siblings like spotify_track or spotify_album.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidelines are provided on when to use this tool versus alternatives (e.g., spotify_track_similar_albums or spotify_artist_related). There is no mention of prerequisites, context, or exclusion criteria, leaving the AI agent without guidance on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states it 'returns available Top Ads location filters' but does not disclose any behavioral traits like rate limits, authentication needs, or data freshness. The behavior is minimal (no params), but transparency is lacking.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at two sentences, front-loading the main purpose. There is no unnecessary information, though it could be more efficient by merging the two sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description should hint at the return format or structure. It only vaguely mentions 'available Top Ads location filters', which lacks specificity (e.g., are they country codes, region names?). For a simple tool, more detail would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema is empty with no parameters, so schema coverage is 100%. The description adds no parameter-specific information, but none is needed. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves TikTok Top Ads locations and returns available location filters. It uses a specific verb 'Retrieve' and identifies the resource. However, it does not explicitly distinguish itself from the sibling 'tiktok_top_ads_location_info', though the mention of 'filters' provides some differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus other top ads tools, such as when to get location filters versus location details or lists. There is no mention of prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits beyond the basic function. It lacks details on authentication, rate limits, pagination behavior, error handling, or what the response contains. For a tool that returns matches, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences with no extraneous information. It is front-loaded with the tool name and purpose, making it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters (pagination offset/limit) and no output schema, the description does not explain how count/start affect results, what instrument types are valid, or the format of returned matches. It is incomplete for a search/lookup tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All four parameters have descriptions in the schema, so baseline is 3. The description only adds 'optionally filtered by instrument type', which mirrors the schema's 'Instrument type filter'. No additional meaning or usage hints beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it returns Yahoo Finance instrument matches for a query with optional type filter. It is specific about the resource (instrument matches) and the action (lookup). However, it does not explicitly differentiate from the sibling tool 'yahoo_finance_search', which may have a similar purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like yahoo_finance_search or ticker-specific tools. There is no mention of prerequisites, limitations, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose whether the operation is read-only, any side effects, or details about the returned metadata. It only states it 'returns' metadata.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no unnecessary words. It is as concise as possible.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and a single parameter, the description is too brief. It does not explain what 'chart metadata' includes or any limitations, leaving the agent underinformed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds no extra meaning beyond the parameter name 'symbol'. The mention of 'for a symbol' is redundant with the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns 'Yahoo Finance chart metadata for a symbol', but is vague about what 'history metadata' means. It does not differentiate from the similar sibling tool 'yahoo_finance_ticker_history'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives like 'yahoo_finance_ticker_history' or 'yahoo_finance_ticker_info'. No context on prerequisites or use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as authentication requirements, rate limits, or whether the operation is read-only. The description assumes a simple fetch but doesn't confirm safety or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, consisting of two sentences: one naming the tool and one listing the returned modules. It is front-loaded with the tool name and purpose, with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple schema and lack of output schema, the description is mostly complete but lacks depth. It doesn't explain what 'normalized' means or hint at the response structure, which would help an agent anticipate the output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with the single parameter symbol adequately described in the schema. The description does not add further meaning beyond what the schema already provides, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns ticker info including profile, quote type, price, statistics, and summary modules for a symbol. However, it does not explicitly distinguish this tool from sibling ticker-specific tools (e.g., yahoo_finance_ticker_quote), leaving the differentiation implicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of context, prerequisites, or when not to use it. The description simply lists what it returns.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for disclosing behavioral traits. It only states that the tool returns news results, but does not mention any side effects, rate limits, authentication needs, or other behaviors. The description is too minimal to be transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, consisting of two short sentences. It front-loads the purpose without any fluff. While it could be slightly more informative, it earns points for efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters and no output schema, the description is adequate but minimal. It doesn't explain the structure of the returned news items or any other contextual details. The parameter schema is complete, but the description could be more helpful by describing the return format or including a note about the data source.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, so the baseline is 3. The description does not add any further meaning to the parameters beyond what the schema already says (e.g., 'symbol' is a Yahoo Finance symbol, 'count' is news result count, 'tab' specifies a tab). No additional nuance or examples are provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool returns Yahoo Finance news search results for a symbol. It uses a specific verb ('returns') and resource ('Yahoo Finance news search results'). Among the many yahoo_finance_* sibling tools, this one is clearly about news, distinguishing it from tools like yahoo_finance_ticker_info or yahoo_finance_ticker_quote.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, nor any prerequisites or contexts. It simply describes what it does without indicating when it is appropriate or inappropriate to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, yet description fails to disclose behavioral traits such as rate limits, data freshness, response structure, or error handling. Merely stating 'returns normalized fast quote fields' is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise single sentence with no redundant text. Could benefit from more structured information, but compression is efficient for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description should provide more detail on the response content. 'Normalized fast quote fields' is vague; typical fields like price, change, volume are missing, leaving the agent with insufficient context to interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (parameter 'symbol' has description). Description adds no additional semantic value beyond what the schema already provides, meeting the baseline but not exceeding it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it returns normalized fast quote fields for one symbol. However, it doesn't contrast with sibling tools like yahoo_finance_ticker_info, leaving some ambiguity about what specific data is included.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The word 'fast' hints at use case but does not provide clear directives or comparisons.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. 'Fetch and parse' indicates a read operation, but there is no mention of side effects, authentication, rate limits, or what parsing entails. The truncated description offers minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief but incomplete—the second sentence cuts off mid-phrase ('as returned by.'). This is not well-structured conciseness; it is under-specification that hinders understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool, the schema covers the parameter thoroughly, and the operation is simple. However, the description does not explain the return value, parsing behavior, or URL requirements (left to the schema), and the truncation creates a gap. This is minimally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a detailed description of the 'url' parameter. The tool description itself adds no additional parameter semantics beyond the schema, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The first sentence clearly states the tool fetches and parses a congressional disclosure report. However, the description is truncated mid-sentence ('as returned by.'), which reduces clarity and fails to explicitly differentiate it from sibling tools like congress_stock_disclosures.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description hints at usage context ('by its filing_url'), implying it should be used with URLs from congress-stock-disclosures, but the sentence is incomplete. It does not state when to use this tool versus alternatives or provide exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden of behavioral disclosure. The word 'search' implies a read operation, and 'public' hints at accessibility, but the description does not disclose important behavior such as the deprecated ticker parameter, chamber-specific defaults, validation errors, or parameter compatibility constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short but contains redundancy: the second sentence 'Search public congressional stock disclosure filings (House or Senate)' largely repeats the first sentence with only slight additions ('public' and chamber scope). An ideal description would merge these or front-load the chamber scope more efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 17 parameters, no required fields, no output schema, and complex chamber-specific behavior, the description is far too sparse. It does not give the agent a high-level understanding of how to structure a request or what results to expect, leaving the agent to rely entirely on the schema descriptions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with all 17 parameters documented in the input schema. The description adds no additional parameter meaning beyond what the schema already provides, so the baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action (Search) and resource (congressional stock-disclosure filings), and explicitly scopes it to House or Senate filings. This makes the tool's purpose unambiguous and distinct from the sibling congress_report tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus alternatives, nor does it mention exclusions or prerequisites. The only context is the statement that it searches public filings, which is implicit in the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that the data is crawled from PitchBook's public sitemap, which hints at potential staleness or coverage limitations, but it does not explain pagination, result limits, or how filters combine. Critical behavioral details like the 10,000-result ceiling appear only in the schema, not in the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively short, but the first sentence 'Search PitchBook companies dataset' is largely redundant with the tool name. Useful information about crawling and sitemap discovery appears later, and the sort enum list repeats schema content. It is structured reasonably but not tightly front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 14 parameters, no output schema, and no annotations, the description only provides data provenance and a sort list. It does not explain return value structure, how filters interact, or when to use which parameters. Though the schema covers parameter documentation, the overall context for an agent selecting this tool is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so the baseline is 3. The description repeats the sort enum but adds no additional semantic meaning beyond what the schema already provides. No extra parameter context is given, making this a neutral contribution.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool enables searching the PitchBook companies dataset, and the second sentence specifies that it searches a crawled public company profile catalog. This distinguishes it from sibling tools like datasets_pitchbook_companies_item or facets, which serve different purposes. The scope is explicit and actionable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives such as datasets_pitchbook_companies_facets, datasets_pitchbook_companies_item, or pitchbook_company. It implies usage through the word 'search' but lacks exclusions or alternative recommendations. An agent navigating the large sibling list would not know which tool to choose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It does not disclose behavioral traits such as read-only nature, pagination behavior, rate limits, or what happens on failure. Only states it searches public startups.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences plus enumeration of sort and status. Front-loaded but redundant with schema. Could be more structured and concise by avoiding repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema. Description does not explain what the search results contain (e.g., key fields of startups) or mention pagination/result count. For a tool with many optional filters, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% description coverage for all 26 parameters. Description adds a high-level summary of filter types but does not provide deeper semantics beyond what schema already offers. Baseline 3 due to high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it searches the TrustMRR dataset of public startups with verified revenue. Mentions filtering categories. Distinguishes from siblings by naming the specific dataset, but does not contrast with similar search tools like datasets_trustmrr_facets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage as primary search tool for TrustMRR data. No explicit guidance on when to use this versus alternatives like datasets_trustmrr_item or datasets_trustmrr_facets.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description only says 'returns' but doesn't disclose any behavioral traits such as authentication requirements, rate limits, or what 'normalized' implies. Lacks transparency for a read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise one-sentence description. Could benefit from more clarity but no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description is insufficient for an agent to fully understand the return structure or context. 'Normalized featured instruments' is vague.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters, so schema coverage is 100%. The description doesn't need to add parameter info; baseline for 0 params is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns Google Finance featured stocks as normalized featured instruments. This distinguishes it from sibling tools like markets_top, markets_trending, etc., but could be more specific about what 'featured' means.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, no context about prerequisites or typical use cases. The agent must infer from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries full burden but only states it 'returns' data, implying a read operation. No details on authentication, side effects, or limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise but sacrifices completeness. Front-loads purpose but omits necessary details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Lacks explanation of 'market movers', filtering logic, or output structure. Incomplete for a tool among many finance siblings with no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema descriptions cover 100% of parameters, so baseline is 3. Description adds no extra meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description is specific with verb 'returns' and resource 'normalized market mover instruments', clearly distinguishing it from siblings like google_finance_markets_top or google_finance_markets_featured.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus other Google Finance market tools. No explicit context or alternative recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden. It only states the function without disclosing read-only nature, rate limits, error handling, or behavior when data safety info is absent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short but contains redundancy between 'Retrieve...' and 'Returns...' Could be more concise. Adequate but not exemplary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema or explanation of return values. Does not describe potential errors or response format. Incomplete for a tool with no annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers both parameters with clear descriptions. The description adds no additional parameter info beyond schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves Google Play data safety details, using a specific verb and resource. It distinguishes from sibling tools like googleplay_permissions or googleplay_reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like googleplay_app or googleplay_permissions. No mention of prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and description does not disclose read-only nature, rate limits, data freshness, or results scope. Only states it runs a screener, leaving behavioral traits unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, but first sentence is a noun phrase lacking a verb. Second sentence is clear. Could be more direct and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema and description does not explain result format or list valid screener ids. With 5 parameters, more context is needed for proper tool use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All 5 parameters have schema descriptions (100% coverage), so baseline is 3. Description adds only an example for 'id', not extra meaning for other parameters like count or offset.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool runs predefined Yahoo Finance screeners, with specific examples like day_gainers or most_actives. This distinguishes it from the sibling yahoo_finance_screener_custom which handles custom screeners.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like yahoo_finance_screener_custom. Missing prerequisites or context for choosing a screener.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description is minimal and does not disclose behavioral traits such as data freshness, return format, or rate limits, leaving the agent underinformed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, but it redundantly mentions 'Yahoo Finance SEC filings' twice. It could be more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and only a vague reference to 'summaries', the description lacks details about the structure or content of the returned data, which is insufficient for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of the single parameter with a clear description. The tool description adds no additional semantic value beyond the schema, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns SEC filing summaries for a symbol, distinguishing it from other yahoo_finance_ticker_* tools like yahoo_finance_ticker_actions or yahoo_finance_ticker_dividends.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool vs. alternatives, nor any context about prerequisites or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior; it only mentions returning normalized result cards but fails to explain pagination, sorting, or any side effects or limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (two sentences) and front-loaded with the action, but it could include more context without being excessively long.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, and the description does not explain what 'normalized Amazon search result cards' entails, nor does it cover sorting or page behavior, leaving gaps for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the description adds no additional meaning beyond what the schema already provides for parameters, meeting the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches Amazon products and returns normalized search result cards for amazon.com, differentiating it from sibling tools like amazon_product and amazon_suggest.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., amazon_suggest for suggestions or amazon_product for details), no exclusions or contextual prerequisites provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries full burden. Mentions data source but omits behavioral traits like rate limits, result ordering, default behavior for limit/page, or any destructive actions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is concise and front-loaded with the main action. However, it could be slightly more informative without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 5 parameters, no output schema, and sibling tools, the description is too sparse. Lacks explanation of pagination, country/lang semantics, and how results are formatted. Does not compensate for missing annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline 3 applies. Description adds no additional meaning beyond what the schema already provides for parameters. No enrichment of parameter purpose or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'Search' and resource 'Apple Podcasts shows'. Distinguishes from sibling tools like apple_podcasts_charts or apple_podcasts_episodes_search by specifying shows. Also mentions normalized results and the data source.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like apple_podcasts_charts for top charts or apple_podcasts_show for details. No context about prerequisites or exclusions provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool 'returns' data, implying read-only behavior, but does not explicitly confirm no side effects, authorization requirements, rate limits, or output format details. The description is insufficient for a mutation-agnostic agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences covering purpose and parameter hint. No redundant information. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two required parameters, the description covers the basic purpose and parameter requirements. However, it lacks details on output structure (e.g., what 'normalized grouped rows' means), potential pagination, or data limits. Given the absence of an output schema, more complete context would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions for both parameters (month and year). The description simply repeats 'Provide year and month' adding no additional semantic context beyond what the schema already provides. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves the 'Box Office Mojo domestic release schedule' and returns 'normalized grouped rows'. The verb 'returns' and resource 'domestic release schedule' are specific. However, it does not distinguish from sibling tools like boxofficemojo_calendar_changes or boxofficemojo_calendar_date, which may have overlapping purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description only instructs to 'Provide year and month', but offers no context on when to use this tool versus alternatives (e.g., calendar_changes or calendar_date) or any prerequisites. There is no mention of use cases or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses that empty valid searches return empty arrays but does not mention rate limits, authentication (assumed public), or what 'normalized' means. Minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (two sentences) and front-loaded with the purpose. Every sentence contributes value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool with no output schema, the description is adequate but lacks detail on the structure of returned sections. It mentions 'normalized CoinGecko search sections' but does not clarify typical sections (coins, exchanges, etc.) or how results are organized, leaving some ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description does not add meaning beyond what the schema already provides for the two parameters (q and limit). Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a search for CoinGecko discovery, using specific verbs ('search', 'returns') and resource ('CoinGecko search sections'). It distinguishes from the many sibling specific coingecko tools (e.g., coingecko_coin, coingecko_categories) by being a general discovery search, though it could be more explicit about which sections are included.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternative coingecko tools. It does not mention when not to use it (e.g., for specific coin data, use coingecko_coin instead). This is a significant gap given the large set of sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full burden. It implies a read-only operation by referencing 'public crypto treasuries tables' but does not explicitly confirm non-destructive behavior, authentication needs, or rate limits. The mention of 'supports the documented vs_currency enum' adds some transparency, but key behavioral traits are omitted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loading the core purpose and adding a relevant detail about the vs_currency enum. It is efficient with no redundant information, though the second sentence could be merged with the first.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description should at least outline the structure of returned data. It mentions 'normalized entity rows' but does not clarify fields, columns, or pagination behavior. This lack of detail hampers an agent's ability to interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with each parameter having a clear description (e.g., 'Treasury asset filter, default all'). The description adds only that vs_currency is an enum, which is already in the schema. No additional meaning or usage nuance is provided beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized entity rows from CoinGecko's public crypto treasuries tables. It specifies the resource ('crypto treasuries') and a supported parameter (vs_currency enum), distinguishing it from sibling tools like coingecko_coin or coingecko_markets. However, it could more explicitly define what 'treasuries' entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives among the many sibling CoinGecko tools. The description does not mention context, prerequisites, or exclusions, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears the full burden. It mentions 'deduped trending coins and categories' and enum support, but omits details like error conditions, rate limits, pagination, or read-only nature. Basic traits are covered minimally.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary purpose, and contains no redundant information. Every word serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given two optional parameters and no output schema, the description is moderately complete. It covers the main functionality but lacks details on return structure or behavioral constraints, which would help in a tool-rich environment.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds minor value by noting that `vs_currency` supports a documented enum, but does not elaborate beyond the schema's property descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns 'trending coins and categories' from CoinGecko, using specific verbs and resources. However, it does not explicitly differentiate from siblings like coingecko_markets or coingecko_gainers_losers, though the mention of 'deduped' and 'public highlights page' provides some distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus other Coingecko tools (e.g., coingecko_markets, coingecko_search). The description implies support for vs_currency enum but does not state context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits. It only states it returns observations, but doesn't mention ordering, pagination, rate limits, or whether results are cumulative. The listed change types are already in the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, no redundancy. Efficient for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema and no annotations. The description lacks details on return format, pagination, empty results behavior, or any error conditions. For a data retrieval tool, this is insufficient for full autonomous use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%. The description repeats the change_type enum, which adds slight reinforcement but no new meaning. The limit parameter is not elaborated beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves recent changes for Chrome Web Store items, listing the specific change types. This differentiates it from sibling tools like datasets_chrome_extensions_history or datasets_chrome_extensions_metrics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. The agent must infer usage from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It mentions 'chronological change-only observations' but does not disclose rate limits, authentication needs, error behavior, or the nature of the observations. Only basic operational context is given.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the core purpose. Every phrase is informative with no redundancy. Highly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with no output schema, the description is adequate but lacks details about the observation format, pagination, or limits beyond the parameter 'limit'. It is minimally complete but could be enhanced.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all 4 parameters with descriptions. The description adds no additional meaning beyond 'chronological change-only observations'. Baseline 3 for high schema coverage, and no extra value from the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'Chrome Web Store item history', with 'chronological change-only observations' clarifying the output. However, it does not differentiate from siblings like datasets_chrome_extensions_changes, which may serve a similar purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternative tools (e.g., datasets_chrome_extensions_item for full item details). The description lacks any contextual hints for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and description does not disclose behavioral traits beyond the basic function. Mentions 'returns a page' but lacks details on pagination behavior, rate limits, or authentication requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff. Efficiently conveys the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with full schema coverage, the description is adequate but lacks usage context and behavior details. Could mention pagination or sorting options.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters. The description adds no additional meaning beyond what is in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool lists a repository's public forks and returns a page, with specific resource 'forks'. However, it does not explicitly distinguish from sibling tools like github_repo_stargazers or github_repo_contributors.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., stargazers, contributors). No context on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description must carry the burden. It only says 'returns normalized news' but omits behavioral details like freshness, ordering, pagination, or what 'normalized' means. Lacks disclosure of side effects or limits (e.g., default limit).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no redundancy. Front-loads purpose and result. Every word is necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, more detail on the return format would help. Also, with numerous sibling tools, missing context on how this differs from other Google Finance news tools or generic news tools reduces completeness for a complex domain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds no extra meaning beyond schema; 'for a quote' matches the 'quote' param. No new semantics for 'limit' either.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb and resource: 'returns normalized news articles for a quote'. However, it doesn't distinguish among siblings like google_finance_analyst_articles (analyst news) or google_finance_markets_category_news (category news).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this vs other news tools or alternatives. Usage is implied but not explicit, and no exclusions or conditions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the full burden falls on the description. It states a fetch operation but omits details like authentication requirements, rate limits, or whether the operation is read-only. The description is insufficiently transparent for a tool with zero annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (two sentences) with no redundancy. Every sentence contributes meaning, and it is front-loaded with the tool's identity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two parameters and no output schema, the description provides a reasonable overview but lacks details on the return format or data structure. It is adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers both parameters with examples and options, achieving 100% coverage. The tool description adds no additional semantic value beyond the schema, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'fetches' and identifies the resource as 'chart ticker data', making the purpose clear. However, it does not distinguish this tool from similar siblings like 'google_finance_chart', which might fetch chart data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as 'google_finance_quote' or 'google_finance_chart'. The description only states what the tool does without any context on selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It only discloses the rate limit (1 req/s) but does not mention authentication requirements, output format, or that it is a read-only operation. This is insufficient for full behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise with two sentences: first states purpose, second adds rate limit. No unnecessary information. Perfectly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description is adequate but could be improved by explaining what 'detailed information' includes or any prerequisites. It covers the basics but lacks completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'place_id' has a description in the schema ('Google Place ID'), achieving 100% coverage. The tool description does not add additional meaning beyond what the schema already provides, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it returns detailed information for a specified place_id. The verb 'returns' and resource 'place details' are specific. However, it does not distinguish from sibling tools like google_map_search, but the purpose is clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as google_map_search or geocoding. Only mentions a rate limit, which is not usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the rate limit (1 req/sec), adding behavioral context beyond the schema. However, there are no annotations, and it does not describe other important behaviors like search result structure or pagination. It is adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences: one for purpose and one for rate limit. It is front-loaded and efficient, with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and a nested object parameter, the description is too minimal. It lacks information about return values, pagination, or result types, which are necessary for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter, 'mapSearchOption', is described in the schema as 'Search options', which is generic. The description repeats this without adding semantic details. With 100% schema coverage, the baseline is 3, and no additional value is provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a search API for Google Maps that returns results, providing a specific verb and resource. However, it does not distinguish this tool from related siblings like 'google_map_place' or 'datasets_google_map_businesses_search', which could cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives, such as 'google_map_place' for specific places or 'datasets' tools for business data. The rate limit is mentioned but does not help in choosing between tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It mentions that the data is 'normalized' and sourced from an 'internal TrendsUi batch RPC replay,' which offers some transparency about data origin and processing. However, it does not disclose any side effects, authorization needs, rate limits, or the shape of returned data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise and front-loaded. However, it includes technical jargon ('TrendsUi batch RPC replay') that may reduce clarity. Every word earns its place, but the jargon could be simplified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 9 optional parameters and no output schema, the description is insufficiently complete. It does not explain what the returned rows contain, how parameters interact, or what a typical response looks like. The agent lacks context to form proper expectations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no parameter-specific meaning beyond the schema. The term 'normalized' might hint at data transformation, but it does not explain how individual parameters like 'geo', 'hl', or 'window' affect the output.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns 'normalized Google Trends Trending Now rows from the internal TrendsUi batch RPC replay.' The verb 'returns' and the resource 'Google Trends Trending Now data' are specific. However, it does not differentiate from sibling tools like google_trends_trending_detail, which may have a similar purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There is no mention of prerequisites, exclusions, or typical use cases. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It only says 'Returns the media details' without specifying what those details include (e.g., likes, comments, image/video), any auth requirements, or that it is a safe read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, consisting of two sentences with no unnecessary words. It is front-loaded with the primary action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description should clarify the return structure. 'Media details' is vague; it does not indicate what fields are returned (e.g., URL, caption, timestamp). This leaves the agent guessing about the response format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (both parameters described in schema). The description repeats the schema information ('by user ID and post ID') without adding new meaning about parameter formats, constraints, or allowed values. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Retrieve'), the resource ('specific Instagram post'), and the required identifiers ('user ID and post ID'). It effectively distinguishes from sibling tools like instagram_profile (retrieves user profile) and instagram_reels (retrieves reels).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus sibling tools such as instagram_profile or instagram_reels. The description does not mention any prerequisites, limitations, or alternative use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description notes that the tool returns data from credential-free public JSON, indicating no authentication is needed. However, it does not disclose the data format (e.g., OHLCV fields), any side effects (none expected), or potential limitations like rate limits or data freshness. With no annotations, the description carries the full burden but provides only basic context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that includes key information (purpose, data source, scope). It is front-loaded and efficient, though adding a brief sentence on output could improve structure without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters and no output schema, the description should provide more detail about the return values (e.g., candlestick fields). It states 'normalized Kalshi candlesticks' but does not explain normalization or data fields. This is insufficient for an agent to fully understand the tool's behavior without prior knowledge.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with each parameter described in the input schema. The description adds no additional parameter-level information beyond what the schema provides, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool returns normalized Kalshi candlesticks for one settled historical market, specifying it uses credential-free public market-data JSON. However, it does not explicitly differentiate from sibling tools like kalshi_historical_market or kalshi_market_history, which might have similar functions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. It mentions 'credential-free' but does not discuss prerequisites, when not to use it, or how it compares to other historical Kalshi tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description must disclose behavioral traits. It mentions 'credential-free' (no auth) and 'historical', but omits pagination details, rate limits, data freshness, or that it returns trades (not aggregates). Minimal disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-loading the tool's name and core purpose. No wasted words, but could be slightly more structured (e.g., listing key traits).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters and no output schema or annotations, the description lacks details on return format, pagination behavior, and parameter usage, making it insufficient for effective use without external knowledge.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline 3. The description adds no parameter-level information beyond what the schema already provides; it does not explain cursor, limit, or timestamp filters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states it returns 'normalized older Kalshi trades from credential-free historical market-data JSON', specifying the resource (historical trades) and distinguishing it from current trade tools like kalshi_trades.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives (e.g., kalshi_trades for current trades, kalshi_market_history for market-level history). The description only implies historical context but lacks explicit direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description lacks details on behavior such as auth needs, rate limits, or error handling. It mentions 'public' but doesn't explicitly state read-only or any constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no fluff, but could be more concise (e.g., 'Returns forecast summaries for a question'). Front-loaded with name and action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, and description does not explain what 'aggregation method' means or the structure of the returned data. Given the tool's simplicity, more detail would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only one parameter 'id' with schema description 'Metaculus question or post id'. Tool description does not add extra meaning beyond the schema, which already covers the parameter well (100% coverage). Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns forecast summaries for one question, using verbs like returns and resource like forecast summaries. It distinguishes from siblings like metaculus_question_forecast_history by specifying 'latest' and 'by aggregation method'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like metaculus_question_forecast_history or metaculus_question. The description does not mention use cases or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It implies a read-only, credential-free operation ('normalized wrapper around credential-free public JSON'). However, it does not disclose behavior like rate limits, caching, or what happens without filters. Partial disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, two sentences. The first sentence is a fragment ('Polymarket fee types.') but still clear. No unnecessary words. Could be slightly improved with a complete sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given two optional parameters and no output schema or annotations, the description is minimal. It does not explain filter behavior, output format, or limitations. For a tool with filters, more context is needed for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%; both parameters have descriptions. The tool description adds no extra meaning beyond what the schema provides. For example, it does not explain how 'active' or 'search' affect the results. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns fee type data from Polymarket Gamma. The verb 'returns' and the resource 'fee type data' are specific. However, the tool name 'polymarket_public_data' is broader and could cause confusion. It is not fully distinguished from sibling tools, though no other fee-specific tool exists.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus other Polymarket tools. No mention of prerequisites, when not to use, or alternative tools. The description only states what it does, not the context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description adds some transparency by noting 'credential-free' (no auth needed) and 'normalized tag rows' (output format). However, it lacks details on rate limits, pagination behavior, or any side effects. The added context is useful but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (13 words) and front-loaded with the key action. However, it could include more context without becoming verbose, making it slightly under-specified for the task.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's 5 parameters, no output schema, and many sibling tools, the description is too sparse. It does not explain what tags are, how they relate to other entities, or how to effectively use parameters, leaving the agent under-informed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description does not need to add parameter details. It provides no extra meaning beyond what the schema already offers, meeting the baseline but not exceeding it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists tags and specifies the data source (credential-free public Gamma tags JSON). However, it does not distinguish from sibling tools like polymarket_tag, polymarket_event_tags, or polymarket_market_tags, which reduces differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool vs. alternatives, no prerequisites, and no exclusions. Given the many sibling tools, this omission makes it difficult for an agent to choose correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must bear the full burden of behavioral disclosure. It only states it returns a public CLOB price, but does not mention safety (read-only), authentication needs, rate limits, or error behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two clear sentences with no extraneous information. It is front-loaded with the core action and scope.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description should explain the return value structure. It mentions returning a price but not the format or additional fields. It is sufficient for a simple price lookup but lacks completeness for an agent to fully understand the response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with descriptions for both parameters. The description adds context about the return being a 'public CLOB buy or sell price', but does not elaborate on the side parameter values or token_id format. This provides marginal added value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies the verb 'Get' and the resource 'Polymarket token price'. It mentions the CLOB buy or sell price for one token id, but does not explicitly differentiate from sibling tools like polymarket_token_midpoint or polymarket_tokens_prices, which reduces clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives such as polymarket_token_midpoint or polymarket_tokens_prices. No context about prerequisites or scenarios is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so description must bear full burden. It does not disclose behavioral traits like read-only nature, authentication needs, or side effects. Only states it returns payload.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no redundant information, front-loaded with purpose. Efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple structure (one param, no output schema), the description is minimally viable. However, it does not explain what the 'category page payload' contains, leaving some ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the description adds no additional meaning beyond the parameter name. Baseline score of 3 is appropriate as the schema already covers the parameter's role.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it retrieves category details and returns the category page payload. It is specific about the resource (category) and action (retrieve). However, it does not explicitly distinguish from sibling category-related tools like producthunt_category_products.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives, such as producthunt_category_products. No prerequisites or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does not disclose whether the tool is read-only, requires authentication, has rate limits, or any other behavioral traits beyond the basic retrieval operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences. The first sentence states the primary purpose, and the second adds key details about pagination and the underlying operation. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a paginated retrieval tool with no output schema, the description is minimally complete. It mentions pagination but does not describe the response format, data fields, or any considerations like rate limiting or authentication requirements.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents each parameter. The description does not add any additional meaning or constraints beyond what is in the schema, such as valid values for order or acceptable page ranges.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Product Hunt product customers and mentions pagination and the GraphQL operation. However, the phrasing 'customer products' is somewhat ambiguous, and it doesn't explicitly differentiate from sibling tools like producthunt_product or producthunt_reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, such as producthunt_product or producthunt_reviews. There is no mention of prerequisites, context, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It states the tool returns 'normalized public product details' but does not disclose what 'normalized' entails, potential side effects, rate limits, or authorization needs. Minimal behavioral context beyond the core function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short, direct sentences with no redundant information. Every word contributes to understanding the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, and the description does not explain the return structure or what 'normalized public product details' includes. For a simple retrieval tool it's adequate, but given siblings with more specific offerings, additional context on returned fields would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with id described as 'Product id' and variant_id as 'Variant id'. The description adds no extra meaning beyond the schema, so it meets the baseline but provides no additional value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get Shop.app product' with a specific verb and resource. It distinguishes from siblings like shop_app_product_related and shop_app_product_reviews by indicating it returns main product details, but lacks explicit differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool over alternatives or any prerequisites. Without context on when to prefer this vs sibling tools like shop_app_product_related or shop_app_product_variant, the agent must infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose beyond the basic function. It does not mention pagination, sorting, rate limits, or any side effects. The return format is not described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two short sentences that front-load the purpose. No unnecessary words or clauses.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the tool is simple but lacks specification of return format or error handling. It covers the basic functionality but could benefit from more detail, such as expected response structure or authentication needs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description does not add significant new meaning beyond the schema. The 'id' and 'limit' parameters are adequately described in the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists public product reviews from a Shop.app product page. It is distinct from other review tools like shop_app_shop_reviews or appstore_reviews, though no explicit sibling differentiation is provided.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like shop_app_shop_reviews or other review tools. There is no mention of prerequisites or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It mentions the source path and inferred types, but lacks details on error conditions, required permissions, or data freshness. The behavior is partially clear but insufficiently transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one sentence describing the action and a second clarifying the return. Every word is purposeful, with no redundancy or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains the tool's purpose and output (child sitemap URLs with types), but lacks details on the output structure (e.g., format, whether it's a list or tree). Given no output schema, more completeness would be beneficial. Adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameter 'url' is described in the schema as 'Shopify storefront URL', and the tool description adds that it accesses the public /sitemap.xml index. With 100% schema coverage, the baseline is 3, and the description adds marginal value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists Shopify sitemaps, specifying it returns child sitemap URLs from the public /sitemap.xml index with inferred types. This provides a specific verb and resource, and implies a distinction from sibling tools like shopify_sitemap_urls, but does not explicitly differentiate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool vs alternatives. It does not mention prerequisites, context, or when not to use it. The description simply states its function without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It mentions 'private Pathfinder responses' suggesting reliance on a non-public API, but lacks details on authentication, rate limits, or whether the tool is read-only. The safety profile is unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief with two sentences, but the second sentence largely repeats the first ('Returns artist playlists' vs 'Retrieve Spotify artist playlists'). Slightly redundant, but still efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description does not define what 'artist playlists' are (playlists featuring the artist vs. curated by the artist). With no output schema, the tool should hint at the return format or structure. The reference to 'private Pathfinder responses' adds ambiguity rather than clarity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with descriptions for both parameters (uri and id). The description adds no extra meaning beyond what the schema already provides, so a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Retrieve' and the resource 'Spotify artist playlists', making the purpose explicit. It distinguishes from sibling tools like spotify_artist_albums and spotify_artist_related by specifying the exact resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as spotify_playlists_search or spotify_featured_charts_by_country. The description does not mention prerequisites, limitations, or context for optimal use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavior. It mentions 'normalized' results but does not describe the response structure, data freshness, or any side effects. Lacks details important for an agent to predict outcomes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise, one sentence with essential verb and object. Front-loaded with action. However, it could benefit from additional context without sacrificing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, so description should explain return values. It only says 'artist search results' without structure or other details like pagination hints (despite offset/limit parameters missing behavioral context). Incomplete for effective tool use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% description coverage, so baseline is 3. The description adds no extra meaning beyond the schema (e.g., no clarification on offset behavior beyond 'search offset').
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it searches for Spotify artists and returns normalized Web Player search results. The verb 'search' and resource 'Spotify artists' are specific. It distinguishes from sibling tools like spotify_search or spotify_tracks_search by focusing on artists.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like spotify_search or spotify_artist. The description does not mention exclusions or preferred contexts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must fully disclose behavior. It indicates the tool returns data from 'private Pathfinder responses' but fails to state whether it is read-only, requires authentication, or has rate limits. No side effects or return structure are mentioned, leaving significant ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences, front-loading the purpose. However, it is so brief that it sacrifices useful context. While no words are wasted, it could be slightly expanded for clarity without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 4 parameters, no output schema, and no annotations, the description omits critical details such as response format, pagination behavior, and error handling. The sibling list includes many Spotify tools but no cross-referencing is provided. The description is insufficient for an agent to use this tool reliably without external knowledge.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with all parameters described. The description adds no additional meaning beyond the schema; it does not explain parameter relationships (e.g., uri vs id exclusivity, offset/limit for pagination). Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Spotify audiobook chapters, using a specific verb and resource. It distinguishes from siblings like spotify_audiobook (full audiobook) and spotify_chapter (single chapter) by specifying chapters. The mention of 'private Pathfinder responses' adds technical context but doesn't obscure purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool vs alternatives such as spotify_audiobook or spotify_chapter. There is no mention of prerequisites, conditions, or exclusions. The agent must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It mentions retrieval and return of sections/items, but does not explain pagination behavior (despite having pagination parameters), side effects, or required permissions. The technical 'browsePage Pathfinder response' is not elaborated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first states core purpose, second adds technical context. No wasted words, but could be structured more clearly (e.g., list parameters or behavior).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 6 parameters, no output schema, and no annotations, the description is insufficient. It does not explain the distinction between page and section pagination, return format, or how parameters interact. Agents may struggle to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so each parameter has a description in the schema. The description adds no additional meaning beyond what is already in the schema, achieving baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states action ('Retrieve') and resource ('Spotify genre page'), and mentions the return type ('normalized sections and items'). However, does not explicitly differentiate from sibling tools like spotify_section or spotify_home, which may also deal with sections.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage from description (for genre or page URIs), but no explicit guidance on when to use this tool versus alternatives, nor any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It mentions the data source and parameter format but does not state crucial details: whether the tool is read-only, requires authentication, has rate limits, or what happens when the parameter is omitted. This is insufficient for safe and effective usage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two short sentences, no unnecessary words, and front-loaded with the core purpose. Every sentence adds meaningful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, so the description should elaborate on the return format. It vaguely mentions 'normalized Spotify country hub shelves' but does not specify the structure, fields, or examples. Essential for an agent to interpret results correctly. The optionality of the parameter is also not clarified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100% (the single parameter 'country_code' has a description). The description adds value by providing an example URL and explaining that the code comes from open.spotify.com, which aids parameter understanding beyond the schema's minimal description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Retrieve') and resource ('Spotify popular by country'), clearly stating what the tool does. It mentions the normalized shelves from a specific endpoint, which adds precision. However, it does not explicitly distinguish itself from similar sibling tools like spotify_featured_charts_by_country, slightly reducing clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like spotify_featured_charts_by_country or spotify_search. It lacks when-to-use and when-not-to-use information, making it hard for an agent to select this tool correctly among many similar Spotify tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as rate limits, authentication needs, or what 'normalized albums' means. The term 'Pathfinder response' is left unexplained.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded and efficiently communicates the core purpose without unnecessary words. It is appropriately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and a tool that returns data, the description fails to explain the return format or constraints. The vague term 'normalized albums' and reliance on schema alone leave the agent underinformed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions (uri, id, limit, albums_only). The description adds no additional meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Retrieve' and resource 'Spotify track similar albums', and distinguishes from other Spotify tools by specifically referencing the 'similarAlbumsBasedOnThisTrack Pathfinder response'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus other Spotify tools (e.g., spotify_album, spotify_artist_albums) or any prerequisites. It lacks contextual cues for appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It only mentions the return type (chart and percentile) and metric values, but lacks details on behavioral traits like data freshness, authentication requirements, or whether the operation is read-only (likely read, but not stated).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise with two sentences, no redundancy. It front-loads the purpose and then lists supported metrics. Every sentence adds value, though it could be slightly more structured (e.g., separating parameter details).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 parameters and no output schema, the description is incomplete. It does not explain how the parameters affect the output, nor does it describe the structure of the returned chart or percentile. More detail is needed for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for all three parameters, so the baseline is 3. The description does not add extra nuance beyond the schema definitions (e.g., what values period_type can take or the format of material_id), so it does not exceed the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Retrieve' and the resource 'TikTok Top Ads interactive time analysis', which distinguishes it from sibling tools like tiktok_top_ads_detail or tiktok_top_ads_filters. It specifies that it returns an interactive time analysis chart and percentile, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus alternatives. Among many TikTok top ads sibling tools, no contextual hints about when to prefer this one (e.g., over tiktok_top_ads_detail or tiktok_top_ads_list) are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full burden. It implies a read operation ('Retrieve', 'Returns') but does not mention side effects, rate limits, data freshness, or any constraints. The phrase 'initial location and industry context' is vague.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two sentences effectively communicate the core purpose. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one optional parameter and no output schema, the description provides minimal context. It does not explain the return structure, how the module parameter affects results, or how this tool relates to sibling tools. Adequate but incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only one optional parameter ('module') with 100% schema description coverage. The description adds no additional meaning about the parameter beyond what the schema provides ('Creative Center module id'). Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it retrieves TikTok Top Ads location info and returns initial location and industry context. The verb 'Retrieve' is specific, but it doesn't distinguish from sibling tools like tiktok_top_ads_locations or tiktok_top_ads_list, which may have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., tiktok_top_ads_locations). No context about prerequisites or ideal use cases is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must cover behavioral details. It only states returns of recommended materials but does not disclose pagination behavior, rate limits, or authentication needs. It does not contradict any annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences with key information front-loaded. No redundant words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema and annotations, the description is minimally adequate for a simple retrieval tool but lacks details on the nature of recommendations or response structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with descriptions for each parameter. The description adds nothing beyond what the schema provides. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves TikTok Top Ads recommendations related to a material id, using a specific verb and resource. However, it does not distinguish it from siblings like tiktok_top_ads_suggestions or tiktok_top_ads_list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as tiktok_top_ads_analysis or tiktok_top_ads_list. The agent receives no context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral transparency. It only states the tool returns related company cards 'from rails', which is vague. There is no disclosure about read-only nature, rate limits, authentication needs, or potential side effects. The description could benefit from clarifying that this is a read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long and extremely concise. Every word adds value: it identifies the action, resource, and source. No filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (1 parameter, no output schema, no annotations), the description covers the basic functionality but lacks depth. It does not mention output format, potential limitations, or any pagination behavior. For a simple tool, it is adequate but could be more informative.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for the single 'slug' parameter, so the baseline is 3. The description does not add additional meaning beyond the schema's 'Trustpilot business slug' – it does not provide format examples or clarify what a valid slug looks like. No extra value is contributed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves related businesses from Trustpilot using the public business page rails. The verb 'Get' and resource 'related businesses' are specific. While it distinguishes from sibling tools like trustpilot_business (single business) and trustpilot_business_search (search), the term 'related company cards' is slightly vague but acceptable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as trustpilot_business or trustpilot_business_search. There is no mention of prerequisites, optimal scenarios, or conditions to avoid.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It only states that it returns data, but does not disclose whether it is read-only, any authentication needs, rate limits, or side effects. The term 'normalized' is undefined.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that convey the core purpose and source. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with 4 parameters and no output schema, the description lacks details about return format, pagination, or how the output is structured. It is minimally complete but could be more informative.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with basic descriptions for each parameter. The tool description adds no additional meaning beyond the schema, which is adequate but not helpful.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Search') and the resource ('Trustpilot categories'), and mentions that it returns normalized results from the API. However, it does not explicitly differentiate from sibling tools like trustpilot_categories (list) or trustpilot_category (detail), leaving some ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There are no prerequisites, exclusions, or context about preferred use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description does not detail behavioral traits such as rate limits, authentication, error handling, or pagination. It only states what the tool returns, lacking transparency beyond that.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the key purpose. It contains no unnecessary words and is well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description provides a high-level overview of return types (quotes, news, lists, research). However, it lacks details on result structure, pagination, and error behavior, making it only moderately complete for a search tool with 6 parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for all 6 parameters, so the schema already clearly defines each parameter. The description adds no additional meaning beyond the schema, which is adequate for a baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs a Yahoo Finance search and returns normalized quotes, news, lists, and optional research reports for a query. This distinguishes it from more specific sibling tools like yahoo_finance_ticker_quote or yahoo_finance_news, but does not explicitly contrast with them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, when to prefer this over more specific Yahoo Finance tools, or any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the types of data returned but fails to disclose any potential issues such as symbols without analyst data, required previous calls, rate limits, or whether the data is real-time or delayed. The description is minimal and does not provide sufficient transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, immediately stating the tool's purpose and listing the data it returns. It is front-loaded and concise, with no unnecessary words. Every sentence provides meaningful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool returns multiple data types (recommendations, upgrades/downgrades, price targets, estimate modules) and lacks an output schema, the description provides a basic overview but does not detail the structure or format of the returned data. It is adequate for a high-level understanding but leaves ambiguity about what exactly 'estimate modules' entails.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of parameters with a description for 'symbol' (Yahoo Finance symbol such as AAPL). The tool description adds no extra meaning beyond the schema. Baseline 3 is appropriate as the schema already sufficiently documents the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns analyst data including recommendations, upgrades/downgrades, price targets, and estimate modules. It identifies the resource (Yahoo Finance analyst data) and the verb (returns). However, it does not explicitly differentiate itself from sibling tools like yahoo_finance_ticker_earnings or yahoo_finance_ticker_info, which might also provide related financial data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus its siblings. The description does not mention when it is appropriate to call this tool, what prerequisites exist, or when alternatives like yahoo_finance_ticker_info should be preferred. This lack of context could lead to misselection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions that results come from 'Yahoo Finance calendar HTML when Yahoo serves the table', implying conditional availability and HTML parsing. However, it does not disclose error handling, latency, or what happens if the table is not served. This is adequate but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise. However, it includes a redundant phrase 'Yahoo Finance earnings dates' that could be omitted. It is front-loaded but slightly wordy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema is provided, and the description only vaguely mentions 'standalone earnings-date rows' without detailing the return format. Given the complexity of parsing HTML, more information about the structure of returned data would be helpful. The description is insufficient for an agent to fully understand the output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions for all three parameters (symbol, limit, offset). The description adds no additional semantics beyond what the schema provides. Baseline is 3, and no extra value is added.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns earnings dates from Yahoo Finance calendar HTML. It uses the verb 'returns' and specifies 'standalone earnings-date rows', making the purpose clear. However, it does not explicitly differentiate from sibling tools like yahoo_finance_ticker_earnings or yahoo_finance_calendar, which could cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. The description lacks any when-to-use or when-not-to-use instructions, leaving the agent to infer based on the tool name alone. No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It labels the result as 'experimental' (hinting at instability) but does not disclose error behavior, rate limits, or authentication needs. The output format is vaguely described as 'yfinance-compatible'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no superfluous text. The first sentence serves as a title, the second adds context. Efficient, though could be more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no output schema or annotations, the description is minimal. It lacks details on return shape, error conditions, and integration context (e.g., how ISIN results are typically used).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (symbol parameter well-documented). The description adds context about the output nature but does not enhance parameter meaning beyond what the schema provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns an ISIN lookup result for a given symbol, distinguishing it from other yahoo_finance_ticker_* tools by specifying 'ISIN' and 'experimental yfinance-compatible'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus other lookup/search tools in the sibling list (e.g., yahoo_finance_lookup, yahoo_finance_search). The description does not mention alternatives or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as rate limits, authentication needs, or error handling. It simply describes the output without addressing side effects or limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences, no fluff, and front-loaded with purpose. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple lookup tool with one parameter and no output schema, the description is minimally adequate. It states what is returned but omits details like output structure or potential data limitations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides full description coverage (100%) for the single parameter 'symbol'. The description adds no additional meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns option expiration dates and the current option chain for a symbol. It specifies a verb ('returns') and a resource ('options chain'). However, it does not explicitly differentiate from similar siblings like yahoo_finance_ticker_options_expiration, which may only provide expiration dates.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., other options or ticker tools). The description only states what it does without context on prerequisites or scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description lacks behavioral details such as authentication requirements, rate limits, data freshness, or error handling (e.g., what if symbol has no splits). Only states it returns split events.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise and to the point. It could be slightly more informative but is not verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 parameter, no output schema, no annotations), the description is insufficient. It does not explain what a split event contains, how to interpret the output, or any prerequisites. A minimal viable description would include more context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%. The description mentions the symbol parameter but adds no new meaning beyond the schema description. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns split events for a symbol. Among many sibling yahoo_finance_ticker_* tools, it distinguishes itself as dealing with splits. The verb 'returns' and resource 'split events' are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus other ticker tools (e.g., dividends, earnings). It does not mention alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It simply states it retrieves and returns privacy cards, but does not disclose rate limits, authentication needs, error handling, or data freshness. The behavior is implied as a read-only retrieval, but more detail would be beneficial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of two sentences that convey the purpose and return value without any extraneous information. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the fact that the input schema covers all parameters, the description is mostly complete. It clearly explains what the tool returns. However, it could mention that the required parameter 'id' is an App Store track ID, which is only in the schema, not the description. Minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no additional meaning beyond the input schema, which already has 100% coverage with descriptions for all three parameters. The schema provides the parameter definitions, so the description does not need to add more, but it also does not enhance understanding. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Retrieve' and the resource 'App Store privacy disclosures', and specifies that it returns privacy cards with data categories and purposes. However, it does not explicitly distinguish this tool from sibling tools like appstore_app, which might also be used to get app details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not mention when to use this tool instead of alternatives, nor does it indicate any prerequisites or constraints. Agents must infer that it's for privacy data only.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It only states that it returns normalized release rows, omitting details like read-only nature, authentication requirements, or data scope. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with key purpose. No redundant information. Efficient and to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description covers the core purpose. However, it lacks details about the output format ('normalized release rows') which would be helpful. Mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only one parameter 'date' with schema description 'Calendar date in YYYY-MM-DD format'. Schema coverage is 100%, so the description adds no extra meaning beyond what is already in the schema. Baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description specifies verb 'returns', resource 'domestic release schedule date', and output 'normalized release rows'. It is clear but does not explicitly differentiate from siblings like boxofficemojo_calendar (which likely covers a range) or boxofficemojo_date_domestic.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus siblings. The description implies it is for a single date, but does not state alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description takes on the full burden. It discloses a specific behavioral trait: empty upstream pages return a typed not-found error. However, it lacks information on rate limits, data freshness, or whether the operation is read-only. The single disclosure is helpful but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, each serving a purpose: identification, output specification, and error behavior. It is efficient and front-loaded with the main purpose. No extraneous words, but could be slightly more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two parameters and no output schema, the description covers the source, output type, and error behavior. However, it does not detail the output structure (columns of a normalized distributor row) or mention ordering/pagination. This leaves some ambiguity for the AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the input schema already describes both parameters (week and year) with ranges. The description does not add any extra meaning or context beyond what the schema provides. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized distributor rows from a specific Box Office Mojo chart. It distinguishes this tool from similar sibling tools by specifying 'by-distributor'. However, it could be more explicit about what 'normalized distributor rows' entails, such as the columns or data types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like boxofficemojo_weekend_domestic or boxofficemojo_weekend_domestic_estimates. The description implies use for distributor-level data but does not provide context or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits. It only mentions that the endpoint supports the vs_currency enum and returns normalized coin rows. It does not describe pagination behavior, rate limits, or potential side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief (two sentences) and front-loaded with the tool's main purpose. However, the first sentence ('CoinGecko category coins') is somewhat redundant with the tool name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the many sibling CoinGecko tools, the description provides adequate core function but lacks differentiation and contextual cues. It does not explain 'normalized coin rows' or the return structure, which is needed since there is no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds marginal value by noting that vs_currency supports a documented enum, but it does not elaborate on the slug, page, or limit parameters beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns normalized coin rows from a CoinGecko public category page, specifying the resource and action. It distinguishes from sibling tools like coingecko_categories (which lists categories) and coingecko_coin (which gets a single coin) by focusing on coins within a category.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternative CoinGecko tools (e.g., coingecko_markets, coingecko_gainers_losers). There is no mention of prerequisites, context for use, or when to avoid this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only mentions normalization without specifics. It does not disclose pagination behavior, rate limits, or data freshness, leaving behavioral expectations unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two focused sentences with no extraneous information. First sentence states purpose, second adds detail about vs_currency. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description fails to explain what 'normalized rows' means or what columns are returned. For a list tool, this omission leaves users guessing about the data structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so schema already documents parameters. Description adds 'supports the documented vs_currency enum' but does not provide additional meaning beyond the schema, meeting baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized rows from CoinGecko's public new cryptocurrencies table, specifying the verb 'returns' and resource 'new cryptocurrencies', differentiating from siblings like coingecko_coin or coingecko_markets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like coingecko_markets or coingecko_coin. No context about typical use cases or exclusions is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It mentions the search operation and that reviews are stored as one document per review, but does not discuss rate limits, authentication, data freshness, error states, or any side effects. This is insufficient for a search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the core purpose, followed by key details (store and sort enums). No extraneous information or repetition. Efficiently conveys the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite 8 parameters and no output schema, the description is very brief. It omits details about pagination behavior, what data fields are returned, how filters interact, and the scope of the dataset. This leaves significant gaps for an agent to understand the tool's full capability.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema provides descriptions for all 8 parameters. The description adds minimal extra value by listing store and sort enums, but these are also present in the schema. Overall, it does not significantly enrich parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches an app-reviews dataset with reviews from iOS and Google Play, using store and sort enums. It distinguishes itself from sibling tools like appstore_reviews and googleplay_reviews by explicitly mentioning both stores and the 'apps_reviews' dataset name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., appstore_reviews, googleplay_reviews). There is no mention of prerequisites, when-not-to-use, or which scenarios benefit from this aggregated dataset over individual store tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It states returns 'terms aggregation counts' but does not explain how filter parameters (q, country, min/max indices) interact with the facet, pagination, or output structure. Critical behavioral details are missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. Efficiently communicates the core function and the facet enum.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 12 parameters and no output schema, the description is too brief. It lacks explanation of how filters affect aggregations, what the output format looks like, and any limitations. Incomplete for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with detailed parameter descriptions. The description adds no new semantics beyond what is already in the schema, such as clarifying the role of filter parameters in aggregation. Baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it facets the Numbeo cities dataset and returns terms aggregation counts, specifying the facet enum is 'country'. The verb 'facet' and the explanation differentiate it from sibling search and item tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like datasets_numbeo_cities_search. The description implies usage for aggregation but does not provide when-to-use or when-not-to-use advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions the record is 'crawled', which hints at data provenance, but does not describe return format, error behavior, or any limitations. Being a read operation is obvious from 'Get', but no additional behavioral insight is offered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, concise and front-loaded with the core action. The duplication between 'from dataset' and 'dataset id enum value' is slightly redundant but does not waste significant space.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple item fetch tool, the description is adequate: it specifies the input and that it returns one record. However, with no output schema, it does not describe the record's structure or fields, and no information is given about edge cases like missing ids, which is a moderate gap for a data retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with a clear description and example for the `id` parameter. The description adds little beyond restating that retrieval is by id, but the schema already fully documents the parameter, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves a single PitchBook limited partner record by id from a dataset, using a specific verb and resource. It distinguishes itself from search/facets siblings by emphasizing 'by id', though a sibling `pitchbook_limited_partner` exists without the datasets prefix which could cause slight ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied: you need an id to fetch a record. However, no explicit guidance is given on when to use this tool versus the search or facets alternatives, nor any mention of prerequisites like having the dataset id enum value.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses the corpus composition and sort defaults, but lacks information on pagination behavior, rate limits, authentication, or read-only nature. Since no annotations are provided, the description partially carries the burden but is incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences with no redundancy. Front-loaded with the core action and corpus description. Could be more compact, but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Lacks return format details since no output schema is provided. Does not mention result limits or pagination beyond what is in schema. Adequate but leaves gaps for an agent to understand the full response context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions for all 7 parameters. The description adds minor extra context (e.g., 'most-helpful' corpus, max 256 chars for q, page*page_size constraint). Baseline 3 is appropriate as the schema already does heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it searches the steam-reviews dataset, describes the corpus as the most-helpful reviews per game, and lists the full-text query and filters. Distinguishes from other steam datasets by specifying review-specific content, but does not explicitly differentiate from similar review tools like steam_reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides no guidance on when to use this tool versus alternatives. Does not mention when not to use it or compare with sibling tools like steam_reviews or other datasets. The description only states what it does, not the context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description must disclose behavioral traits, but it only briefly mentions that feedback is from the public eBay tab. It does not address potential pagination, data freshness, or any limitations (e.g., only recent reviews).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences, front-loading the purpose. It efficiently conveys the core functionality without extraneous detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of an output schema, the description provides a reasonable overview of what is returned (summary, ratings, review cards). However, it omits details on error handling, rate limits, or data format, which are important given the absence of annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions (seller username, page number, reviews per page). The description adds context about the return types (summary, ratings, review cards) but does not further clarify parameter usage or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool retrieves eBay seller feedback, specifying it returns a summary, detailed ratings, and recent review cards. It differentiates from sibling tools like ebay_seller_about or ebay_seller, which focus on other seller information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like ebay_seller or ebay_seller_shop. The description simply states the function without context on selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose all behavioral traits. It fails to mention rate limits, authentication requirements, or any side effects. The term 'normalized listings' and pagination reference are vague.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the main purpose. No wasted words, though it could benefit from additional structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description is moderately complete. It covers the basic function and pagination but lacks details on output format, errors, or usage constraints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers both parameters fully, so baseline is 3. Description adds minor context about pagination but does not explain parameter behavior beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets eBay seller shop listings, specifying the resource (seller shop) and action (get). It distinguishes from siblings like ebay_search or ebay_seller by focusing on shop listings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus siblings. The description mentions pagination but does not differentiate from alternative tools like ebay_search or ebay_seller.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the basic action and result, but does not mention read-only behavior, pagination, sorting, default limits, or any other operational quirks. For a search tool this is minimally adequate, but it lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the verb. The second sentence 'Returns Etsy shops matching a keyword' is slightly redundant with the first, but it does clarify the keyword-based nature of the search, so it earns its place. It is appropriately sized and has no excessive verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a low-complexity 2-parameter search tool with no output schema. The description explains the basic purpose and result, but it does not describe what fields are returned for each shop, any pagination behavior, or sorting. Given the simplicity and full schema coverage, the description is minimally complete but leaves some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both 'q' and 'limit' clearly described in the input schema. The description adds no extra meaning beyond the schema (e.g., 'matching a keyword' simply restates the 'q' parameter), so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search Etsy shops' with the specific verb 'search' and the resource 'Etsy shops', and adds 'Returns Etsy shops matching a keyword' to clarify the query-based nature. It is distinct from siblings like etsy_search or etsy_shop, but does not explicitly differentiate itself from them, which prevents a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for finding shops via keyword, but it gives no guidance on when to use this over sibling tools such as etsy_search, etsy_shop, or etsy_shop_listings. There are no alternatives named or exclusions given, so usage context is only implied, not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description notes 'Returns a page', indicating pagination, but does not disclose whether it returns only commit authors or all repo collaborators, or any rate limits. With no annotations, more detail would be helpful.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with a parenthetical, effectively communicating the core function without fluff. It is appropriately sized but could be slightly expanded without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema is provided, and the description does not mention return format or fields. However, the tool is straightforward, and the schema covers parameters fully. Adequate for a simple listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% coverage with descriptions for all 4 parameters. The description adds minimal value beyond 'who builds a project'. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists a repository's contributors and includes a parenthetical explanation ('who builds a project'). It distinguishes from sibling tools like 'github_repo' (repo info) and 'github_repo_forks' (forks). However, it could be more specific about returning a page of contributors.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives like 'github_repo' or 'github_search_users'. Without context about when contributors are needed over other repo data, an agent may misuse it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description states it returns a page of repos, implying pagination, but does not disclose authentication needs, rate limits, error behavior (e.g., non-existent user), or what fields are returned. The phrase 'tech-stack signal' adds minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, no fluff. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 6 parameters, many siblings, and no output schema, the description is too sparse. It does not describe the return format, pagination details, or how to interpret results for the mentioned tech-stack signal. An AI agent lacks sufficient context to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with all parameters described. The description adds no additional information beyond the schema; the 'tech-stack signal' hint does not relate to specific parameters. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and the resource 'a GitHub user's public repositories'. It also adds the context 'tech-stack signal' which hints at the use case. Among many Github sibling tools, this one is distinct for listing a single user's public repos.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like github_org_repos or github_search_repositories. The description does not mention when-not-to-use or provide any context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It only states the output type without details on data freshness, pagination, rate limits, or what 'normalized' means. This is insufficient for an agent to understand the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no redundancy. Every word serves a purpose. Perfectly concise for the minimal information provided.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters, no output schema, and a simple purpose, the description is somewhat complete. However, it lacks detail about the returned data structure (field names, units). For market indices, more context (e.g., common fields like price, change) would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so schema coverage is 100%. The description adds no parameter information, but with zero parameters the baseline is 4. The description could hint at implicit context but does not, so score remains at the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized market index instruments, specifying the resource and action. However, it does not distinguish this tool from many similar Google Finance market tools (e.g., google_finance_markets_top, google_finance_markets_featured), which reduces clarity for selection among siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. The description lacks any context about prerequisites, use cases, or when not to use it, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It merely states the basic action without revealing any side effects, rate limits, or prerequisites. No mention of what 'quote data' includes or excludes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences are efficient. However, the second sentence is a URL example that may be marginally useful but doesn't add critical information. Still, it's well-front-loaded and wastes no words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
As a simple one-parameter tool with no output schema, the description covers the minimum: what it does and an example. However, it does not specify the return format or scope of 'quote data', leaving some ambiguity. Adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline 3. The description reiterates the schema's parameter meaning ('stock symbol') and gives an example, but adds no additional semantic value beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Fetches'), resource ('latest quote data'), and context ('for a provided stock symbol from Google Finance'). It effectively distinguishes the quote-fetching tool from sibling tools like google_finance_ticker or google_finance_company.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., google_finance_ticker for detailed info, other finance tools for different data). The description lacks exclusions or context about its niche within the finance tool family.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must disclose behavioral traits. It only states the tool 'returns normalized Google Trends keyword analytics' without mentioning rate limits, authentication requirements, or the fact that it is a read-only operation. The behavior of the 'request' parameter is also not described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that lists the output types, which is fairly concise. However, it could be slightly more structured (e.g., separating output description from source) but overall it is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the nested object parameter and the presence of many sibling tools (including specific explore components), the description is incomplete. It does not explain the request format, how it differs from the sub-tools, or any response structure. This is a significant gap for a tool with a complex parameter.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has a single 'request' object parameter described only as 'Explore request', which is very vague. The description adds no clarification on how to structure the request or what fields it expects. While schema coverage is 100%, the description does not compensate for the lack of parameter detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Google Trends explore data, listing the specific analytics types (interest over time, by region, related queries, topics). It differentiates well from sibling tools like google_trends_trending or google_trends_explore_interest_over_time by specifying it returns multiple data types from a single request.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for keyword analytics but does not explicitly state when to use this tool versus the more specific explore sub-tools (e.g., google_trends_explore_interest_over_time). No guidance on prerequisites or when to choose alternatives is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It mentions 'credential-free' and the limit clamp, but lacks details on response structure, rate limits, or any side effects. Absence of this information creates a significant gap for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no extraneous information. The purpose and key constraint are front-loaded, earning their place efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having only two parameters, the description omits return value structure – 'normalized rows' is vague. No output schema exists, so the description should explain what fields to expect. This gap reduces completeness for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and already documents limit default/max and query. The description repeats the limit clamping, adding minimal extra value beyond the schema. No new parameter semantics are introduced.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs an IMDb title search and returns normalized rows from credential-free public pages. This specific verb-resource combination distinguishes it from other IMDb tools that handle names, awards, or detailed title information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like imdb_title or other search tools. The description only mentions parameter limits, not usage context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It states the core function but does not mention that the operation is read-only, any required authentication, rate limits, or what happens if the provider name is invalid. For a simple lookup, minimal disclosure is acceptable but still incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with the purpose. No redundant or extraneous words. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, so the description should explain the response structure. It only says 'Returns popular movie/show titles' without specifying format, pagination, ordering, or how to interpret results. Given 5 parameters, more details on output would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with all parameters described. The description adds a concrete example for the provider parameter ('such as `nfx`'), which adds slight value beyond the schema. However, it does not elaborate on semantics or relationships between parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Get JustWatch provider titles' and specifies it returns popular movie/show titles for a given provider short name. It distinguishes from siblings like justwatch_providers (which returns providers) or justwatch_search (which searches titles).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like justwatch_discover, justwatch_genre_titles, or justwatch_popular. The sibling list includes many JustWatch tools, but the description does not differentiate usage contexts or mention when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry full behavioral burden. It states the use of a public credential-free website, implying no authentication. But it does not mention rate limits, whether the operation is read-only, or what data is returned. This is insufficient for a fully transparent description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at two sentences. The first sentence front-loads the purpose, the second adds context on the endpoint and parameter formatting. No superfluous content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the 4 parameters and no output schema, the description adequately covers the endpoint source and parameter constraints. However, it lacks information on result format, pagination, or error handling. For a simple search, it is minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents all parameters. The description adds formatting details for country and language (e.g., 'US', 'en') but these are minor. For limit, the schema already notes defaults and clamping. Thus the description adds only marginal value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches JustWatch titles using a public GraphQL endpoint. The verb 'search' and resource 'JustWatch titles' are specific. However, it does not differentiate from sibling tools like justwatch_discover or justwatch_popular which also return titles but via different criteria.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides format requirements for country and language parameters ('two-letter ISO code', 'two-letter code'). It also mentions the endpoint is credential-free. However, it does not explicitly state when to use this search tool versus alternative title-finding tools like justwatch_discover or justwatch_popular.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Mentions 'credential-free public market-data JSON' which implies read-only, but lacks details on rate limits, data freshness, or side effects. More context needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no fluff, efficiently conveys purpose. Slightly more detail could be added without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema or annotations. Description defines return content (normalized event row and markets) and credential-free access, but lacks format details or example. Adequate for a simple single-parameter tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the schema already describes 'event_ticker' as 'Kalshi event ticker'. Description does not add additional meaning beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns a Kalshi event detail with normalized event row and markets. It distinguishes from siblings like kalshi_events (plural list) and kalshi_event_metadata (metadata only), but could explicitly state 'use for a single event by ticker'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage for getting event details, but no explicit when-to-use or alternatives guidance. Sibling tools like kalshi_events serve different purposes, but description doesn't clarify.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'credential-free' and 'public market-data' but does not describe important traits like pagination behavior, rate limits, or what constitutes a 'series row'. The return format is also unspecified. Essential behavioral details are missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that immediately states the purpose. It is concise with no filler. However, it could be slightly more informative while remaining concise. Front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has only two optional parameters and no output schema, the description is minimally adequate but insufficient. It does not describe the structure of the returned data or any constraints on the cursor. For a public data tool, users might need more context about what a 'series' is and how to use the cursor effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the two parameters (cursor and limit) with descriptions already provided. The tool description adds 'normalized rows' implying pagination but does not explain cursor usage or limit boundaries beyond what the schema states. Baseline 3 is appropriate as the description adds minimal additional semantic value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns normalized Kalshi series rows from public market-data JSON. The verb 'Returns' and specific resource 'normalized Kalshi series rows' make the purpose unambiguous and distinguish it from sibling tools like kalshi_event or kalshi_market.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives. There is no mention of scenarios, exclusions, or comparisons with sibling tools such as kalshi_series_detail or kalshi_markets. The description only states it is credential-free but does not help the agent decide if this is the right tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It only mentions returning 'detailed product information' without specifying the nature of the data, any side effects, or prerequisites. The tool is likely read-only, but this is not stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, consisting of two short sentences. While efficient, it could be more informative without becoming verbose, such as mentioning the output content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 parameter, no output schema, no annotations), the description is minimally adequate but lacks details about what 'detailed product information' includes. An agent would benefit from knowing the structure of the response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter 'id', which is described as 'LinkedIn Product ID'. The description adds no new meaning beyond the schema, so a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get'), the resource ('LinkedIn Product info'), and the method ('by ID'). It is specific and distinguishes from sibling tools like linkedin_company and linkedin_showcase.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, such as when to prefer linkedin_company or linkedin_showcase. The description only states the retrieval method ('by ID').
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions 'credential-free public page data', implying no authentication is needed. However, with no annotations, it fails to disclose error behavior (e.g., invalid ID), rate limits, or the meaning of 'normalized'. It partially addresses safety by indicating public data, but more detail would improve transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, stating the purpose and data source in a single sentence. However, it could include a brief note on what 'normalized' entails without becoming verbose, but the current structure is efficient for such a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one parameter, no output schema), the description is adequate but leaves gaps. It does not specify what fields are included in the 'normalized' question, which could lead to ambiguity when compared to sibling tools that return more specific data like metadata or options. The description should clarify the output scope to be fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the parameter 'id' is described as 'Metaculus question or post id'. The description does not add additional meaning beyond what the schema provides. It merely restates that the tool returns a question detail, offering no extra context on the parameter's format or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns one normalized Metaculus question from public page data. The verb 'returns' and resource 'normalized Metaculus question' are specific, but it does not explicitly distinguish itself from sibling tools like metaculus_question_forecasts or metaculus_question_metadata, which return related but different data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, it does not clarify that this tool retrieves the base question detail, while other Metaculus tools handle forecasts or metadata. The description lacks when-to-use and when-not-to-use context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the burden. It lists returned fields, but does not disclose potential side effects, authentication needs, or rate limits. For a read-only metadata tool, the transparency is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single well-structured sentence that lists included fields without redundancy. Efficient for the information provided.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so the description must explain return values. It lists field categories but not their structure. For a simple tool, it is minimally complete but could benefit from more detail.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description does not add meaning beyond the schema's description of the 'id' parameter. Baseline of 3 is appropriate as no extra semantic value is provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns public metadata for one Metaculus question, listing specific fields like option labels and scaling metadata. It distinguishes from sibling tools like metaculus_question which likely returns more comprehensive data, but does not explicitly differentiate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like metaculus_question or metaculus_question_options. The description implies metadata retrieval but lacks explicit context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It discloses the return fields and the roster_type enum values, but does not mention any limitations, authentication requirements, or default behavior for parameters like season or roster_type. It only lightly describes the behavior, so it remains a minimal disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences with no fluff. The first sentence states the action, the second lists the returned data, and the third clarifies the enum values. Information is front-loaded and every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is adequate for a simple read-only roster tool, but it lacks some context like the need to obtain `team_id` from another source (e.g., `mlb_teams`) and detailed output structure since there is no output schema. The season default is only in the schema, not in the description. Thus, it is not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes all three parameters, but the description adds crucial semantics by enumerating the accepted values for `roster_type` (`active`, `40Man`, `fullSeason`), which the schema only labels as 'Roster type'. This goes beyond the schema and enhances correct invocation, though it does not detail other parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('MLB team roster') and enumerates the returned fields (players, jersey numbers, positions, roster status). However, it does not differentiate from sibling tools like `espn_team_roster` which also retrieves a team roster, so it lacks sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention any exclusions, prerequisites, or comparisons to other roster tools (e.g., `espn_team_roster`). The only usage hint is the roster_type enum values, which are parameter guidance rather than overall tool usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'Credential-free' as a behavioral trait, but does not disclose error handling, rate limits, return format, or behavior for invalid inputs. For a tool with no output schema, more detail is needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, but the first and second sentences are nearly identical ('Get...' vs 'Returns...'). The 'Credential-free' note is useful but could be integrated. Some redundancy reduces conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema and the presence of many siblings, the description adequately states the tool's scope (global country-level) and data source, but lacks examples, details on ranking structure, or guidance on how this tool fits with other numbeo indices tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although schema description coverage is 100%, the schema's parameter description ('Index family') is minimal and no enum or examples are provided. The tool description does not add any additional meaning or permissible values, leaving the agent uncertain about valid input.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and the resource ('global Numbeo country ranking for an index family'). It explicitly distinguishes this tool from siblings by specifying it provides global country-level rankings, differentiating it from city-level or specific cost-of-living indices.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a global country ranking for a Numbeo index is needed, but it does not provide explicit guidance on when to avoid this tool or mention alternatives among the many numbeo siblings. No when-not conditions are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the full burden of behavioral disclosure. It does not mention any side effects, permissions, rate limits, or error conditions. For a read operation, this is minimal but insufficient for transparency about what happens on invalid condition IDs or data availability.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: the first clearly states the action and resource, the second lists returned fields. Every word adds value, and it is front-loaded with the essential verb and object. No redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with one required parameter and no output schema, the description is fairly complete. It specifies input (condition id) and output contents (detail row with specific fields). Could mention that it returns a single row or that it might be used for CLOB-specific markets, but overall adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one parameter well-described as 'Polymarket market condition id'. The description adds no extra semantic beyond the schema, achieving the baseline for high coverage. No enums or additional constraints are needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get Polymarket CLOB market') and the resource ('CLOB market detail row'), with the key identifier 'market condition id'. It lists the included fields (tokens, reward settings, etc.), making the purpose specific. However, it does not explicitly differentiate from the sibling tool 'polymarket_market_detail', which could cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like polymarket_market_detail, polymarket_events, or other CLOB-related tools. The description lacks context for appropriate selection or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must fully disclose behavior. It mentions 'credential-free public Gamma tag JSON' but does not describe return format, error handling, or rate limits. Implicitly a read operation, but not explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, each adding distinct information: retrieval by ID and source details. No fluff, efficiently conveys core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema is provided, yet the description only vaguely mentions 'normalized Polymarket tag' without specifying fields or structure. For a simple retrieval tool, this leaves the agent guessing about return content.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters have schema descriptions (100% coverage). The tool description adds no additional meaning beyond what the schema already provides, earning the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get a Polymarket tag by id', specifying it returns a single normalized tag from credential-free public Gamma JSON. This differentiates from sibling tools like polymarket_tags (plural) and polymarket_market_tags.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Does not mention prerequisites, limitations, or exclusions. Among many sibling tools, instructions for selection are absent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It mentions 'via Product Hunt GraphQL' but does not disclose rate limits, data freshness, authentication requirements, or any side effects. The read-only nature is implied but not explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loaded with the purpose, and contains no redundant information. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 9 parameters, no required fields, and no output schema. The description is minimal and does not explain the return format, pagination via cursor, or how the leaderboard ranking works. Given the complexity, it is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (all 9 parameters have descriptions). The description adds no additional meaning beyond the schema; it does not explain how parameters like date, year, month, day, week interact. Baseline 3 applies due to high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb (Retrieve/Fetches), the resource (Product Hunt leaderboard), and the scope options (daily, weekly, monthly, yearly). It distinguishes this tool from sibling tools like producthunt_about or producthunt_search by specifying leaderboard data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus other Product Hunt tools (e.g., producthunt_search, producthunt_product). It does not mention any prerequisites, alternatives, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavioral traits. It only states returns maker items but does not mention pagination behavior, authentication, rate limits, or error handling. The cursor parameter hints at pagination but is not explained.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences, but the second sentence largely restates the first. Still, it is not verbose and front-loads the purpose. Minor redundancy prevents a 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with no output schema, the description is adequate but could benefit from clarifying pagination (cursor is optional?), error cases, or what constitutes a valid slug. With many siblings, more context would help an agent decide.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with both parameters described in the schema. The description adds no additional meaning beyond what the schema already provides. As per guidelines, baseline is 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (retrieve) and the resource (Product Hunt product makers). It distinguishes from sibling tools like producthunt_product or producthunt_reviews by specifying 'makers'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Does not mention prerequisites, context, or when not to use it. With many sibling producthunt tools, this omission is a notable gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It states it analyzes and returns a snapshot, but does not mention whether it modifies data, requires authentication, has rate limits, or what happens on failure. The lack of behavioral context is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loading the main action and then detailing the output and a key parameter constraint. It is concise, well-structured, and contains no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (analysis, 5 parameters, no output schema, no annotations), the description is insufficient. It does not explain the return format, whether prior search results are required, or how the analysis is performed. This leaves key contextual gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds that limit defaults to 20 and max is 50, which is already in the schema. No additional meaning is provided for other parameters beyond what's in the schema, so score remains at the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool analyzes query results and returns a market snapshot with specific metrics like price ranges, currencies, sale counts, discounts, and top shops. This distinguishes it from sibling tools such as shop_app_search (which returns raw results) and shop_app_product (single product details).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide guidance on when to use this tool versus alternative tools like shop_app_search or shop_app_product. It lacks explicit context for appropriate usage, such as prerequisites or when to avoid.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose all behavioral traits. It states the tool is read-only ('returns public product cards') and lists sort options, but omits details on pagination behavior, error handling for invalid handles or collection IDs, rate limits, or authorization requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loading the core purpose and immediately adding the crucial sort values. No redundant or extraneous words; every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main purpose and sort parameter, but given the lack of annotations and output schema, it leaves gaps: no mention of the return format, pagination beyond the limit parameter, or error conditions. It is minimally adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, providing a baseline of 3. The description adds value by enumerating the allowed sort_by values (MOST_SALES, PRICE_LOW_TO_HIGH, etc.), which are not specified as enums in the schema. This helps the agent select valid sort modes.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists collection products from Shop.app and returns public product cards. It distinguishes from similar sibling tools (e.g., shopify_collection_products) by specifying 'Shop.app' but does not explicitly contrast with other product listing tools in the same domain.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like shop_app_search or shop_app_shop_products. The description lacks context about scenarios or prerequisites for using this specific collection product lister.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description only mentions it returns public product cards. Does not disclose pagination, rate limits, authorization requirements, or behavior when the handle is invalid or out of stock.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two sentences that front-load the core action and immediately provide useful details. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Provides basic info but lacks details on pagination, error handling, and limitations. For a listing tool with no output schema, more completeness (e.g., what fields are in a product card) would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds explicit allowed values for sort_by (MOST_SALES, PRICE_LOW_TO_HIGH, etc.), which the schema only describes as 'Sort mode'. This extra detail improves usability.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it lists shop products from a merchant profile and specifies return type (public product cards). Does not explicitly differentiate from sibling tools like shop_app_search or shop_app_collection_products, but the focus on a specific merchant profile is implied.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like shop_app_search or shop_app_collection_products. No context on prerequisites or typical usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only notes 'public reviews' but omits authentication needs, rate limits, pagination, or return format details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no wasted words. The purpose is front-loaded and immediately clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description should explain what the returned data contains. It only says 'returns public reviews' without field details. Given simplicity, more completeness is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers both parameters (handle, limit) with descriptions. The tool description adds no extra meaning beyond what the schema provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists public reviews for a Shop.app merchant profile, using specific verb 'List' and resource 'shop reviews'. It distinguishes from siblings like shop_app_product_reviews by targeting shop-level reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternative review tools (e.g., shop_app_product_reviews). No exclusions or context for selection are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the endpoint, normalization, and empty result handling, but lacks details on authentication, error behavior, or rate limits. This is moderate transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and to the point with three sentences. No extraneous information. Could arguably include more detail without being verbose, but it is concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description could elaborate on the structure of the returned collections. It mentions normalization but not field details. It is adequate but not complete for a tool with no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage, so the description adds no extra meaning beyond the schema's parameter descriptions. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool lists Shopify collections and specifies it returns normalized collections from a public endpoint. However, it does not explicitly differentiate from sibling tools like shopify_collection_products or shopify_products, which weakens distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, exclusions, or context for selection among sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry full burden. It mentions credential-free access and that body HTML is returned as cleaned text, but lacks details on error handling, rate limits, or output structure beyond body text.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences are efficient and front-loaded with key info. First sentence could be redundant given the name, but overall no waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with no output schema or annotations, the description provides essential info but lacks details on what 'normalized page detail' includes. Slightly incomplete for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with basic descriptions. The description adds context about the endpoint and cleaning, but does not enhance parameter understanding beyond what schema provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it gets a Shopify page, specifies the endpoint, and indicates return normalization. However, it does not explicitly distinguish from sibling tool 'shopify_pages' which likely lists pages, but the singular noun 'page' implies single retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like shopify_pages or shopify_product. No preconditions or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavioral traits, but it only states the return type ('traffic and engagement data') without details on authentication, rate limits, data format, or potential errors. The agent lacks essential behavioral context for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (two sentences) and front-loaded with the tool's primary action. However, the first sentence 'Get SimilarWeb Web Info.' is somewhat redundant with the tool name and could be merged for better conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool (1 parameter, no output schema), the description is minimally adequate but lacks specifics about return data structure, units of traffic/engagement, or usage restrictions. It does not fully compensate for the missing output schema or annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already describes the only parameter (domain). The description adds no extra meaning beyond what's in the schema, such as domain format or example inputs. This fails to enhance the agent's understanding of parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('Get') and resource ('SimilarWeb Web Info'), and specifies it returns 'traffic and engagement data' for a specific domain. This effectively distinguishes it from sibling tools like similarweb_search, which likely handle broader searches or different queries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing traffic/engagement data for a known domain, but it does not explicitly provide when-to-use or when-not-to-use guidance compared to alternatives. No exclusions or alternative tool references are given, leaving the agent to infer context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It does not disclose read-only nature, rate limits, or what happens if no data. Only mentions availability of managers, which is marginal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence that front-loads the purpose. No redundant words, but could benefit from breaking out parameters or output details. Still efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description provides basic return type (record) but lacks detail on format, scope (e.g., date range), or additional fields. Adequate for a simple tool but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one parameter 'id' already described as 'Numeric SofaScore event (match) id'. Description adds no extra meaning, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool returns historical head-to-head win/draw record between a match's two teams, including managers when available. This is specific and distinguishes it from other sofascore tools like event details or statistics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. It mentions the data source (SofaScore's credential-free public JSON) but does not specify use cases or provide exclusions relative to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavior. It states it returns 'normalized Spotify Web Player album tracks from private Pathfinder responses' but does not explain what 'normalized' means, what 'private Pathfinder responses' implies, or any constraints like authentication, rate limits, or side effects. Reads like a data retrieval tool, but lacks detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with the core action. No fluff or repetition. Every sentence adds value: first sentence states purpose, second gives context about return type and source.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite good schema coverage, the description lacks completeness. No output schema, so agent doesn't know response structure. No explanation of how parameters interact (e.g., at least uri or id required?). For a tool with 4 optional params and no annotations, more context is needed to avoid misuse.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description does not add extra meaning beyond the schema; it simply says 'Retrieve Spotify album tracks'. No clarification on parameter relationships (e.g., uri vs id are likely alternatives, offset/limit pagination) beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves album tracks, with specific verb 'Retrieve' and resource 'Spotify album tracks'. It distinguishes from sibling tools like spotify_album (which returns album metadata) and spotify_track (single track). The mention of 'normalized' and 'private Pathfinder responses' adds context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like spotify_tracks_search or spotify_artist_albums. No indication of prerequisites (e.g., requiring album URI or ID) or scenarios where this tool is preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that anonymous credentials are fetched, which is useful, but lacks other behavioral details such as read-only nature, rate limits, or result normalization specifics. Important traits are omitted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences with no redundancy. The first sentence front-loads the purpose, and the second adds a key behavioral note. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 9 parameters, no output schema, and no annotations, the description is too brief. It lacks details on parameter interactions, pagination behavior (offset/limit), return structure, and example usage. The tool is complex but under-described.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds minimal context beyond the schema (e.g., 'normalized Spotify Web Player results'). It does not provide new meaning or usage hints for parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Search Spotify audiobooks.' It specifies it returns normalized Spotify Web Player audiobook search results for a search term, distinguishing it from general search or single audiobook tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description only mentions that caller-supplied tokens are not required. It provides no guidance on when to use this tool vs alternatives like spotify_search or spotify_audiobook, nor does it specify prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It mentions normalized return types but omits critical details like rate limits, authentication, side effects, or whether results are paginated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence efficiently conveys the core purpose with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite high schema coverage, the description lacks details about return format, behavior of boolean flags (include_pre_releases, etc.), and how pagination works. For 9 parameters and no output schema, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds minimal value beyond parameter names and types; 'top results' loosely correlates to number_of_top_results but doesn't clarify its semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches Spotify Podcasts and returns shows, episodes, and top results. The verb 'Search' and resource 'Spotify Podcasts' are specific, and it differentiates from sibling search tools like spotify_search or spotify_shows_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. With many sibling search tools (e.g., apple_podcasts_search, spotify_episodes_search), explicit context or exclusions are missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description should fully disclose behavior. It merely states it returns a metadata payload without detailing any limits, authentication, or side effects. This is minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no wasted words. The description is front-loaded and efficiently communicates the tool's action and output.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (1 parameter, no output schema), the description is adequate. However, it could be slightly more informative by mentioning what the metadata includes (e.g., view count, posts), but it is functionally complete for basic use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for the single parameter 'name', with an example ('christmas'). The description adds no further meaning beyond what the schema provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Retrieve' and resource 'TikTok hashtag details', and specifies it returns the metadata payload. However, it does not explicitly differentiate from sibling tools like tiktok_search_hashtag.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as tiktok_search_hashtag or tiktok_challenge_list. The description lacks any context about appropriate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It describes the output content but fails to indicate that this is a read-only operation, lacks any mention of rate limits, authentication, or potential side effects. It does not contradict annotations but leaves significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the tool purpose ('Yahoo Finance industry detail') and then lists what it returns. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description provides a list of returned data categories (overview, sector linkage, top companies, growth companies, research reports), which gives the agent a good idea of what to expect. However, it does not mention whether the output is paginated, if keys are case-sensitive, or where to find valid industry keys.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes the 'key' parameter with a good example ('semiconductors'). The description adds no additional meaning beyond stating it is 'for an industry key'. Since schema coverage is high (100%), the description adds no extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns industry detail including overview, sector linkage, top companies, etc. It uses a specific verb 'Returns' and identifies the resource. However, it does not explicitly distinguish itself from sibling tools like yahoo_finance_industries or sector tools, though the singular form implies it's for a single industry.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternative tools such as yahoo_finance_industries for listing industries or yahoo_finance_sector for sector data. The description does not mention prerequisites or correct contexts for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full burden for behavioral traits. It does not mention what dividend events include (e.g., dates, amounts, types), whether the data is historical or current, or any limitations. The word 'events' is vague.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences with no redundancy. Every word adds value: the tool name, the data source, and the action. Highly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Lacks details about the structure of the response (e.g., date, amount, type). Without an output schema, the description should clarify what dividend events are returned, but it doesn't. Incomplete for a financial data tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter 'symbol' described as 'Yahoo Finance symbol such as AAPL'. The description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns dividend events for a given symbol. The verb 'returns' and resource 'dividend events' are specific, and the tool is easily distinguished from siblings like yahoo_finance_ticker_splits or yahoo_finance_ticker_info.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus other Yahoo Finance tools that might also provide dividend data (e.g., yahoo_finance_ticker_financials). No prerequisites or context for when dividend events are available.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It states the return data but provides no behavioral details such as data freshness, authentication requirements, rate limits, or error behavior. The agent is left uninformed about side effects or constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-load the core purpose. Every sentence provides essential information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively simple but lacks output schema. The description fails to cover data format, supported date ranges, or limitations. Given the financial domain, more detail on data scope would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds minimal value beyond schema descriptions, e.g., 'historical shares-out rows' confirms data type but no further semantic context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the resource ('Yahoo Finance historical share counts') and the action ('Returns historical shares-out rows'). It distinguishes from sibling tools by specifying the exact data type and source.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., yahoo_finance_ticker_shares). No exclusions or prerequisites mentioned, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description hints at conditional availability ('when Yahoo serves the table'), which adds some behavioral context. However, with no annotations provided, it does not disclose rate limits, data freshness, or response variability beyond the mention.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences efficiently convey the core purpose without redundancy. Could be slightly more informative but is concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given one parameter and no output schema, the description is adequate but lacks detail about what the valuation table contains (e.g., market cap, enterprise value) and the output format. Leaves gaps for an agent to infer.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one parameter 'symbol' described as 'Yahoo Finance symbol such as AAPL'. The description does not add extra meaning beyond the schema, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns the valuation table from Yahoo Finance key statistics page, providing specific verb and resource. However, it does not differentiate from sibling tools like yahoo_finance_ticker_info or yahoo_finance_ticker_financials.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Lacks context on prerequisites or scenarios where this tool is preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that no credentials are required and that it uses Yelp's Android app backend, which is a useful behavioral insight. However, it does not mention rate limits, response format, or any side effects, leaving significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the purpose, but the first sentence largely repeats the tool name. Overall it is efficient without unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool, the description gives the essential purpose and a key auth detail, but lacks information about output shape, pagination behavior, or distinguishing features from similar Yelp review tools. This leaves gaps in contextual completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are well-described in the input schema. The description adds no parameter-specific semantics, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool fetches reviews for a specific Yelp business, using a specific verb and resource. However, it does not differentiate from sibling tools such as yelp_business_reviews_search or yelp_business_review_highlights, so it lacks explicit distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives like yelp_business_reviews_search. The credential-free note provides some context but does not clarify selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that setting format to text/srt/vtt yields plain-text output instead of the standard response, but does not explain error states (e.g., missing captions), authentication needs, or rate limits. Adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no redundancy. First sentence states purpose clearly; second provides actionable format usage. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks explanation of the standard response envelope, timestamps parameter behavior, and default language behavior. For a tool with 5 parameters and no output schema, it is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining the format parameter behavior (plain-text output), but does not enhance semantics for id, lang, translate_to, or timestamps beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Retrieve transcript for a YouTube video' with a specific verb and resource. It mentions using 'YouTube's native player captions,' which adds detail. However, it does not differentiate from the sibling tool 'youtube_captions', which may overlap in functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'youtube_captions' or 'youtube_transcript_languages'. It does not mention prerequisites (e.g., video must have captions) or context for language parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description only says 'Returns normalized Airbnb public review snippets.' It does not disclose pagination behavior, rate limits, or what 'normalized' entails. Minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences front-load the action and provide direct purpose. No extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description lacks detail about the structure of reviews (e.g., rating, text, date). The term 'normalized' hints but is incomplete. Adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already describes parameters (id, page). The description does not add meaning beyond what the schema provides, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get Airbnb room reviews' with a specific verb and resource, and distinguishes itself from sibling tools like 'airbnb_room' and 'airbnb_room_calendar' by focusing on reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'tripadvisor_reviews' or 'googleplay_reviews'. It does not mention prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the burden of behavioral disclosure. It mentions the data comes from Apple's public marketing-tools RSS JSON feed, hinting at public data, but does not disclose defaults, pagination, rate limits, or response format. Behavior remains largely opaque.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the action, and not overly verbose. Minor redundancy ('chart rankings' repeated) is acceptable. It is overall concise and structured effectively.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description provides insufficient context. It does not explain default behavior when no parameters are provided, expected result structure, or any limitations. The moderate complexity of four optional parameters warrants more contextual details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all four parameters (genre, limit, country, collection). The description adds no additional parameter semantics beyond what the schema provides, aligning with the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Apple Books chart rankings, with specific supported collections (`top-free` and `top-paid`). This distinguishes it from other Apple Books tools like `apple_books_book` or `apple_books_search`, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for chart rankings but does not explicitly say when to use it versus alternatives. There are no named alternatives or when-not-to-use conditions, though the supported collections provide some parameter-level guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral disclosure burden. It adds useful context by stating results come from 'Apple's public iTunes Search API' and are 'normalized,' implying a public, read-only source. However, it fails to disclose pagination behavior, rate limits, or the concrete shape of normalized output, which are material for a search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two tight sentences with the primary action front-loaded ('Search Apple Books titles'). Every word earns its place—'public iTunes Search API' and 'normalized' add informational value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 5-parameter tool with no annotations and no output schema, this description is only high-level. It gestures at return values via 'normalized Apple Books ebooks' but omits pagination semantics for page/limit and the filtering effect of lang/country, leaving noticeable gaps for an agent invoking this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description marginally links 'Search Apple Books titles' to the term parameter, but it does not explain how lang, country, page, or limit interact or add meaning beyond their existing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Search') with a clear resource ('Apple Books titles') and adds scope by specifying 'normalized Apple Books ebooks,' which subtly distinguishes it from the sibling apple_books_audiobook_search. However, it does not explicitly name or contrast sibling alternatives, such as apple_books_book or apple_books_author.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus its alternatives. It does not mention apple_books_audiobook_search for audiobooks, apple_books_book for specific titles, or any exclusions. Usage is only implied by the generic 'Search' phrase, with no context about when this search is preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits. It mentions the return includes both show and episodes from Apple's iTunes Lookup API, but does not disclose pagination, rate limits, or data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no redundant information. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the basic purpose but lacks guidance on pagination or how the 'limit' parameter affects results. No output schema, so return format is ambiguous.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with descriptions for all 4 parameters. The description adds no additional semantic context beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the verb 'Retrieve' and the noun 'show episodes', clearly indicating the resource. It distinguishes from siblings like 'apple_podcasts_show' by specifying it returns episodes, though it does not name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus siblings like 'apple_podcasts_show' or 'apple_podcasts_episodes_search'. No prerequisites or exclusions mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavior. It adds that the data is public and sourced from a credential-free API, addressing auth needs, and mentions pagination via 'Returns a page'. However, it does not disclose potential edge cases, rate limits, or the structure of the returned page, so transparency is partial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short but contains a redundant opening sentence 'A Bluesky account's followers.' that repeats the information in the second sentence. The third sentence adds useful context about the public API, but the redundancy means not every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, so the description should provide insight into the response. It mentions a 'page' of followers but does not describe the response fields (e.g., whether it returns DIDs, handles, full profiles). For a simple paginated list tool, this is adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% coverage with clear descriptions for all three parameters (actor, limit, cursor). The tool description adds little beyond the schema, only reinforcing the pagination concept with 'Returns a page'. Since schema coverage is high, the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool 'Returns a page of a Bluesky account's followers', which is a specific verb+resource statement. It does not explicitly distinguish from sibling tools like bluesky_follows or bluesky_profile, so it lacks sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context that the data is 'public' and 'credential-free', implying it is safe to use without authentication. However, it does not explicitly state when to use this tool versus alternatives such as bluesky_follows or bluesky_profile, so usage guidance remains implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'returns a detail page' but gives no information about read-only behavior, response structure, or what data will be present. For a lookup tool, the lack of behavioral disclosure is a notable gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with 'Booking.com attraction detail,' and contains no redundant information. Every word contributes meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description is too sparse for the agent to know what the 'detail page' contains. It doesn't specify whether the output is structured data, fields included, or how to interpret the result, making the tool under-specified for the task.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Even though the schema covers the slug parameter 100%, the description adds valuable context by explaining the slug originates from a prior attraction search result, which helps the agent understand the parameter's provenance and how to obtain it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a Booking.com attraction's detail page, which is a specific verb+resource combination. It distinguishes from search siblings by focusing on the detail page, though it doesn't explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The parameter description indicates the slug comes from a prior attraction search, implying a sequential workflow after booking_attractions_search. However, there is no explicit guidance on when to use this tool versus alternatives like booking_attractions_reviews or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that empty weekend pages return a typed not-found error rather than empty success, which is helpful. However, it lacks info on auth, rate limits, or whether the data is updated periodically.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, no filler. Front-loaded with purpose, then output, then error behavior. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description could have elaborated on the fields in the normalized rows. It also doesn't mention the year range (1982–2100) which is in schema but not in description. Adequate but has gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline 3. The description does not add extra meaning beyond what the schema already provides for year and week parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized rows from Box Office Mojo's public domestic weekend chart, with a specific verb 'returns' and resource. It mentions error handling, but does not explicitly differentiate from sibling tools like boxofficemojo_weekend_domestic_by_distributor or boxofficemojo_weekend_domestic_estimates.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus siblings. The description does not mention prerequisites, when-not to use, or alternatives. The agent is left to infer from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description appropriately discloses a key failure mode (503 on challenge pages) and notes that results are from public HTML. However, it omits details on rate limits, authentication, or what 'normalized' means, and doesn't address mutability or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with purpose, and contains no redundant information. Every sentence adds value, making it concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description covers purpose, source, and a failure mode, but doesn't describe return format or pagination. It is adequate but could be more informative about the structure of results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents all parameters. The description reiterates default country and lang, adding minimal extra meaning. It provides an overview but doesn't enhance parameter understanding significantly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches Brave news results and returns normalized results, distinguishing it from general search tools like brave_search. However, it doesn't explicitly differentiate from other news-specific tools like bing_news or google_news.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description mentions locale defaults but lacks context for when the tool is appropriate or when to prefer sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behaviors like data freshness, pagination limits, or nondestructive nature. It only states it returns normalized rows and is not for real-time trading, failing to explain potential rate limits or data source reliability.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no fluff. The first states the core function, the second adds relevant context about vs_currency and usage warning. Could be more structured but efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, and the description vaguely mentions 'normalized cryptocurrency market rows' without specifying fields like price, volume, or change. For a markets tool, this lacks return structure details, making it incomplete for an agent to understand what data to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema descriptions cover 100% of parameters. The description adds a note about vs_currency being a documented enum, but does not provide additional meaning beyond the schema's parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized cryptocurrency market rows from CoinGecko public pages. It specifies the verb 'returns', the resource 'market rows', and the source, distinguishing it from sibling tools like coingecko_coin or coingecko_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions it supports the vs_currency enum and is not for real-time trading, but provides no explicit guidance on when to use this tool versus alternatives like coingecko_coin or coingecko_categories. Implied context but lacks clear exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states it returns 'normalized article cards,' lacking details on rate limits, authentication, pagination, or any behavioral traits beyond what is obvious.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences with no redundancy, front-loading the core purpose and including the key parameter constraint.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one optional parameter, no output schema), the description is adequate but could benefit from detailing what fields are in a 'normalized article card' or pagination behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter 'limit.' The description's mention of 'default 20, max 50' mirrors the schema description without adding extra meaning, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns CoinGecko news cards from the public news page, using a specific verb ('Returns') and resource ('normalized article cards'). It distinguishes itself from other coingecko tools like coingecko_search or coingecko_markets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, no when-not-to-use conditions, and no context for ideal use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits. It only states it returns normalized rows from a public page, implying it's a read operation, but fails to mention rate limits, authentication, or any side effects. Minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loads the source and purpose, and contains no unnecessary words. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description is adequate but incomplete. It does not describe what fields are in the returned rows or what 'incoming token unlocks' means, which could help the agent understand the output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'limit' is already fully described in the input schema (default 100, max 100). The description adds no additional meaning beyond what the schema provides, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized rows from CoinGecko's public incoming token unlocks page. It uses a specific verb ('returns') and resource ('normalized rows'), and distinguishes itself among many CoinGecko sibling tools by focusing on token unlocks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. There are many CoinGecko siblings, but the description does not mention any specific context, prerequisites, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does disclose the core behavior—returning terms aggregation counts—and lists the facet dimensions. However, it does not describe output format, pagination behavior, or how filter parameters affect the aggregation. It also doesn't clearly state that this is a read-only operation, though 'returns counts' implies non-destructive behavior. This is adequate but lacks deeper behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded, with the main action in the first sentence. The facet enum list is useful and compact. However, it repeats 'Instagram users dataset' in both sentences, which is minor redundancy. It could be more concise by saying 'Returns terms aggregation counts' once. Overall, it is efficient but not maximally polished.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 20 parameters, no output schema, and no annotations, the description is quite sparse. It only states that terms aggregation counts are returned, but does not explain the output structure, how to paginate through results, or whether facets are computed with respect to active filters. It also lacks guidance on common usage patterns, such as first using facets to understand distributions and then drilling into specific users with the search tool. For a tool with this complexity, the description feels incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds marginal value by explicitly listing the facet enum values, but this duplicates the schema's own facet property description. It does not explain the interaction between the required 'facet' parameter and optional filters like q, min_followers, or date ranges. The schema already handles individual parameter meanings, so the description contributes little beyond that.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Facet the Instagram users dataset' and 'Returns terms aggregation counts', which conveys a specific action and resource. It enumerates the valid facet fields, helping the agent understand exactly what dimensions can be aggregated. It does not explicitly differentiate from sibling tools, but the dataset name ('Instagram users') distinguishes it from other datasets_*_facets tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: use this tool when you need terms aggregation counts for Instagram users, as opposed to searching full user records. However, it does not explicitly state when to use this vs. alternatives like datasets_instagram_users_search, nor does it mention that filters can be combined with facets. The purpose is clear enough to imply the context, but there are no explicit exclusions or alternative tool references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the full disclosure burden. It only states that the search covers public profiles in a search index and lists sort options, but omits important behavioral details like pagination limits (page * page_size <= 10000), how results are ordered by default, or what fields are returned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the core purpose. However, the second sentence is a long list of sort enum values already present in the schema, which is redundant and consumes space without adding unique value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex search tool with 19 parameters and no output schema, the description is too thin. It does not explain default behavior, how queries combine with filters, pagination constraints, or what a result record contains, leaving the agent to guess from parameter names alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of the 19 parameters with descriptions, so the baseline is 3. The description's only parameter-related content is the sort enum list, which duplicates the schema's parameter description and adds no new meaning beyond what is already structured.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a search over the Instagram users dataset with a specific verb ('Search') and resource ('Instagram users dataset'). It also differentiates from siblings by specifying it searches public Instagram user profiles stored in a search index, distinguishing it from item or facets tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for searching the dataset, but it does not explicitly state when to use it versus alternatives such as datasets_instagram_users_item or datasets_instagram_users_facets. There is no mention of exclusions or preferred contexts, so guidance is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It adds useful context about the data source (crawled public sitemap, search index) and the sort options, but it does not mention result format, pagination behavior, rate limits, or any other operational behavior. It provides some transparency but not a complete picture.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, starting with 'Search PitchBook funds dataset.' It includes relevant provenance and sort info, though some content (sort enum) duplicates the schema. It is compact and readable, with only minor redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description should explain what the tool returns, but it only says it searches the 'fund profile catalog' without detailing return structure or fields. It also does not mention pagination constraints beyond the schema, nor does it guide users toward facets/item tools for related tasks. This leaves significant gaps for a search tool with 9 optional parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 9 parameters. The description only repeats the sort enum values already present in the schema, adding no new semantic meaning. This aligns with the baseline of 3 when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches the PitchBook funds dataset, with a specific verb and resource. It also adds context about the source (crawled public catalog, search index, discovered from sitemap), but it does not explicitly distinguish itself from sibling tools like datasets_pitchbook_funds_item or datasets_pitchbook_funds_facets beyond the generic 'search' verb.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies its usage as a search tool over the PitchBook fund catalog, but it does not state when to prefer it over alternatives such as facets or item lookups, nor does it mention any exclusions or alternative tools. The use case is implied by the name and the 'search' phrasing, but no explicit guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description implies a read-only search via 'Search' and 'public fields only', but does not disclose behavioral traits such as rate limits, pagination behavior, or whether the tool is destructive. With no annotations provided, the description fails to fully carry the burden of transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the core purpose and dataset ID, followed by a clear explanation of what makers are and key details. No unnecessary words; each sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks context on return format, pagination limits (though in schema), and when to use this vs. sibling tools. Given the detailed schema, it is adequate but not fully complete for an agent to confidently select and invoke the tool without additional hints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so each parameter is already described in the input schema. The description adds minimal extra value by explicitly listing sort enum values and hinting that 'q' covers name and headline. This is adequate but does not significantly enhance understanding of parameters like min_products or min_total_votes.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches Product Hunt makers from a specific dataset, differentiating it from other producthunt tools that search products or live API. However, it does not explicitly distinguish from the sibling tool 'producthunt_makers' which may serve a similar function but without the dataset context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'datasets_producthunt_makers_facets' or 'producthunt_makers'. The statement 'Public fields only' hints at limitations but does not provide explicit when-to-use or when-not-to-use context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must fully disclose behavior. It states it returns aggregation counts but does not mention that the numerous optional filter parameters (e.g., q, has_bio, min_followers) can restrict the dataset before aggregation. This omission reduces transparency for agents expecting predictable behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with three sentences. However, it could be more structured by front-loading that it supports optional filters and then specifying the aggregation behavior. Minor room for improvement.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 16 parameters (1 required, 15 optional) and no output schema, the description should explain what the aggregation output looks like and how optional filters affect it. The current description only mentions the facet enum, leaving agents to infer behavior from the schema, which is insufficient for complete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description lists the facet enum values (already in schema) but adds no additional meaning about how other parameters interact with the aggregation. No added value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it facets the X users dataset and returns terms aggregation counts for specified facet fields (is_blue_verified, has_bio, has_external_url, source_tier). It distinguishes from sibling tools like datasets_x_users_search (searching) and datasets_x_users_item (single item retrieval) by indicating aggregation behavior.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance is provided. The description implies use for aggregated counts by facet fields, but does not mention that for detailed or filtered user lists, search should be used instead. Sibling names suggest differentiation, but the description itself lacks direct guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden for behavioral traits. It mentions credential-free and official data, but lacks details on pagination, result format, rate limits, or error handling. Essential for a search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (3 short sentences) and front-loaded with the primary purpose. However, there is slight redundancy between 'Search the Discogs database' and 'Searches Discogs releases...'.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and 4 parameters, the description does not explain what the search returns, pagination behavior, or type filter options. It provides minimal context beyond the domain and credential-free nature.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter descriptions. The description adds minimal value beyond schema, only noting the entity types searched. It does not explain possible values for 'type' or behavior of 'page'/'per_page'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches the Discogs database across releases, masters, artists, and labels. It distinguishes from sibling tools like discogs_artist or discogs_release which target specific entities, and includes 'credential-free' as a unique attribute.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (for general search across entity types) but does not explicitly state when not to use or provide alternatives. No mention of using specific entity tools for direct lookups.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It does reveal that the tool returns 'normalized' results limited to 'departing-leg offers', which is a meaningful behavioral trait. However, it omits other important behaviors such as error handling, rate limits, or whether the tool requires authentication. It provides some context but is not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, using only two sentences, and leads with the primary purpose. The redundancy of 'Expedia Flights' and 'Expedia flights' is a minor inefficiency, but the overall length is appropriate and the structure is clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a nested object parameter with no schema details and no output schema, so the description must provide more context to be effectively invoked. It mentions the key inputs (IATA pair, date range) but does not explain how to structure the 'option' object or what the response contains beyond 'normalized departing-leg offers'. This is insufficient for reliable use without additional assumptions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter is 'option' with a generic schema description ('Flights search payload'). The tool description partially compensates by specifying that the payload should contain an origin/destination IATA pair and date range. However, it does not describe the exact structure, field names, or required vs. optional fields, leaving ambiguity for an agent constructing the payload.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Search Expedia flights.' It specifies the resource (Expedia flights) and the action (search), and adds details about the input scope (origin/destination IATA pair and date range) and output (normalized departing-leg offers). This distinguishes it from sibling tools like expedia_properties_search and expedia_activities_search, which target different domains.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to use this tool versus alternatives, nor any exclusions or prerequisites. For instance, it does not mention that an IATA code might need to be obtained via expedia_locations_search, or that round-trip searches are not supported. The description only states what the tool does, not when to choose it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description reveals a two-step process (scrape to Markdown then extract JSON) and the requirement of a supplied bounded JSON Schema. It implies public URLs are needed, which is useful. However, it does not disclose error handling, rate limits, or behavior on schema mismatch.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences that directly convey the core functionality. Every word adds value, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with a complex operation (scraping and schema validation), the description is moderately complete. It explains the input (URL) and output (schema-conforming JSON) but lacks details on error handling, response format, and contrasts with sibling tools like 'web_scrape'. No output schema amplifies the gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The sole parameter 'extractOption' is an object with only a minimal description 'Extraction options' in the schema. The tool description does not elaborate on its structure or contents, leaving the agent to guess what properties are required.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool extracts JSON conforming to a schema from a URL, specifying the action, resource, and output. It distinguishes from simple scrapers like 'web_scrape' by mentioning schema-based extraction, but could be more explicit about the supported schema format.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'web_scrape' or other data retrieval tools. It does not specify prerequisites (e.g., public URLs only), limitations, or scenarios where this tool is not appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full burden for behavioral disclosure. It does not mention potential errors, rate limits, authentication requirements, or whether the result is always a single place. The phrase 'nearest typed' is vague.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no redundant information. The purpose and return format are front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description provides a high-level overview but lacks details on optional parameter usage, return structure, and edge cases. Given 7 parameters and no output schema, more guidance would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All 7 parameters have explicit descriptions in the schema (100% coverage), so the description does not need to add much. However, the description provides no additional context on how parameters like zoom or addressdetails affect the result.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it performs reverse geocoding, converting coordinates to a place. It specifies the output format (Nominatim JSONv2) and distinguishes itself from forward geocoding tools like geocoding_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like geocoding_search or geocoding_lookup. The description does not mention prerequisites, context, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It mentions 'public' (implies no auth) and 'company-side enrichment', but does not disclose rate limits, required authentication, or any side effects. The behavior beyond a simple retrieval is unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences without any redundant information. Every word serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with no output schema, the description should give more detail about what the returned profile contains. The phrase 'company-side enrichment' is vague. The description is incomplete for an agent to understand the output structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% coverage with a description for 'org' ('GitHub organization login'), so the description adds no additional meaning. It does not elaborate on the parameter or provide examples or constraints beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'retrieve' and the resource 'GitHub organization profile', and adds context 'company-side enrichment'. It distinguishes well from siblings like github_org_repos and github_user.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The purpose is clear, but there is no mention of when not to use it or which sibling tools might be more appropriate for related tasks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description must fully disclose behavior. It only states 'Retrieve' and 'public detail', implying read-only operation but does not mention authentication, rate limits, or what fields are returned. Minimal transparency beyond what the schema already indicates.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the main action, no unnecessary words. Efficiently communicates the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description vaguely states 'Returns public detail for a single repository (the core project object)'. It is adequate but could be more specific about the return structure, e.g., mentioning typical fields like description, stars, etc.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with clear descriptions for both parameters ('Repository name' and 'Repository owner (user or org login)'). The description adds no extra meaning, earning the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Retrieve a GitHub repository' and specifies it returns 'public detail for a single repository (the core project object)'. This distinctly differentiates it from sibling tools like github_org, github_user, or github_repo_contributors.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives such as github_org_repos or github_search_repositories. The description does not provide context for selection among the many GitHub-related sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions that it returns 'a page of the public accounts', disclosing pagination and public-only scope. However, with no annotations provided, it lacks details on authentication needs, rate limits, or behavior for invalid usernames.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two clear sentences. Every word is necessary and front-loaded effectively.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool with no output schema, the description is adequate but vague about the returned fields. It mentions 'public accounts' but does not specify what data is included for each account.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are already documented. The description adds no additional meaning beyond the schema definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List who a GitHub user follows' with a specific verb and resource. However, it does not explicitly distinguish from the sibling tool 'github_user_followers', relying on the name alone for differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, such as when to use 'github_user_followers' instead. No exclusions or context are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only states it returns results for a term. It does not disclose behavioral traits such as pagination, sorting, rate limits, authentication needs, or the scope of search (e.g., apps only vs. other content). Since no annotations are provided, the description carries full burden but is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences. It front-loads the core action ('Search Google Play') and immediately states the output. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with 6 parameters but no output schema, the description is somewhat lacking. It does not explain the format or content of results, nor does it clarify parameter interactions (e.g., how 'full_detail' and 'num' affect output). It is adequate for a simple search but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides descriptions for all 6 parameters (100% coverage). The description adds no extra meaning beyond the schema, such as usage examples or relationships between parameters. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Search' and the resource 'Google Play', and indicates it returns results for a term. This distinguishes it from sibling tools like googleplay_app (specific app details) and googleplay_similar (similar apps).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention exclusions, prerequisites, or context for choosing this tool over other Google Play tools (e.g., googleplay_list, googleplay_suggest).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full behavioral burden. It only states that the tool returns a timeline, with no information on read-only nature, rate limits, data format, or any side effects. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-load the core functionality and scope. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Even though sibling tools exist, the description fails to explain what output format is returned (e.g., structure of timeline data). With no output schema, the agent lacks enough context to interpret results correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'request' is an opaque object with a generic description ('Explore request'). The tool description adds only that it supports multiple comparison terms, providing minimal semantic value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns the interest-over-time timeline from Google Trends Explore, with support for multiple comparison terms. This distinctively separates it from sibling tools like interest_by_region or related_topics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for time-series data (not region or topics), but no explicit when-to-use, when-not-to-use, or alternatives are mentioned. The guidance is implicit at best.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description is minimal. It does not disclose any behavioral traits such as rate limits, authentication, data freshness, or what the return value looks like.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single short sentence with no wasted words. Efficient, though could be slightly more informative without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (3 parameters, no nested objects, no output schema), the description is adequate. It explains the purpose and id format, though it could mention the return value (e.g., season details).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds an example id pattern ('tss297253') and mentions 'raw JustWatch GraphQL id', providing context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the action (get/lookup), the resource (season by raw id), and provides an example of the id format. Differentiates from sibling tools like justwatch_season_episodes and justwatch_show_seasons.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives. Does not mention when not to use it or suggest other tools for related queries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; the description does not mention side effects, permissions, rate limits, or return format. For a read operation, the lack of disclosure is a gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no redundant information. Efficiently conveys the core purpose and ID format example.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no complexity, the description is adequate but could be improved by noting what is returned (e.g., list of season objects) or any pagination behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already explains all parameters. The description adds a concrete example ('ts287292') for show_id, which is helpful but minimal. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('show seasons') with a specific example of the input ID format, effectively distinguishing it from sibling tools like justwatch_title or justwatch_season_by_id.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., justwatch_season_by_id for a specific season) or any prerequisites. The description only gives the ID format example.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It notes 'credential-free' (no auth) and 'public data', but lacks disclosure of error handling, rate limits, or data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that lists returned data. It is efficient but could be slightly more structured (e.g., bullet points) to improve scanning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has one parameter, the description adequately explains what is returned (media, market metadata, settlement sources, optional competition context). Lacks output schema but sufficient for a simple metadata lookup.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with the parameter description 'Kalshi event ticker'. The tool description adds no additional meaning or format details beyond this, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns specific metadata (media, market metadata, settlement sources, optional competition context) for one Kalshi event from public data, distinguishing it from siblings like kalshi_event or kalshi_markets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as kalshi_event or kalshi_market. The description implies it's for detailed metadata but lacks explicit when/when-not or alternative references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool is credential-free and returns public data, which implies safety, but it does not disclose rate limits, data freshness, whether it is read-only, or any destructive potential. For a data retrieval tool, this is insufficient transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with three sentences that front-load the purpose. It avoids unnecessary details but could be better structured (e.g., bullet points for mutual exclusivity). The length is appropriate, and every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 6 parameters, all optional, and no output schema. The description explains parameter relationships but does not describe the output structure or what fields the rows contain. For a tool that returns data, this is a gap. However, the tool is relatively simple, and the description covers the essential usage patterns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by clarifying that 'tickers', 'event_ticker', and 'series_ticker' are mutually exclusive, and that 'mve_filter' accepts 'exclude'. This goes beyond the schema descriptions, which only state the filter names. The description also implies cursor usage for pagination.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized settled Kalshi historical market rows from credential-free public data. It specifies the mutual exclusivity of filters, which gives a sense of scope. However, it does not explicitly differentiate from sibling tools like kalshi_historical_market or kalshi_markets, missing an opportunity to clarify when this tool is preferred.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage through filter mutual exclusivity but offers no explicit guidance on when to use this tool vs alternatives. It mentions the mve_filter enum but does not explain the context of multivariate events. Without a when-to-use section, the agent must infer from the tool name and siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully bears the burden of behavioral disclosure. It only states it uses 'credential-free public market-data', indicating a read operation. However, it does not describe any side effects, rate limits, data freshness, or other behavioral traits that would help an agent understand its runtime behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two concise sentences with no fluff. It is front-loaded with the key action and resource, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has only one parameter and no nested objects, but also no output schema, the description does not explain what fields are in 'one normalized Kalshi market row'. While context from sibling tools might imply typical market data fields, the lack of explicit return format information makes it somewhat incomplete for an agent to fully understand what it will receive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (the only parameter 'ticker' has a description in the schema: 'Kalshi market ticker'). The tool description adds no additional meaning beyond what the schema already provides, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Returns one normalized Kalshi market row' from 'public market-data JSON'. It uses a specific verb ('Returns') and identifies the exact resource ('one normalized Kalshi market row'), which distinguishes it from sibling tools like 'kalshi_markets' or 'kalshi_market_history'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions it is 'credential-free public market-data', implying no authentication is needed, but it provides no explicit guidance on when to use this tool versus alternatives (e.g., when a client wants a list of markets vs a single market). No when-to-use or when-not-to-use criteria are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the return includes both teams' batting, pitching, and fielding lines, which is useful behavioral context. However, it does not mention read-only safety explicitly, response size, error behavior, or whether the game must be final, leaving gaps in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, immediately front-loaded with the primary action and resource. The second sentence adds the key return detail without fluff. Every word earns its place and there is no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description's mention of 'batting, pitching, and fielding lines' gives a general idea of the return, but lacks structural details like grouping by team or player field names. It also does not cover edge cases (e.g., postponed games, live vs final). Adequate for a simple one-param tool but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage for the single 'id' parameter, describing it as 'Numeric MLB game id'. The description adds no additional parameter meaning beyond contextualizing that the game is the target. Baseline 3 is appropriate since the schema carries the full load.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear action ('Get') and resource ('MLB player boxscore'), but the first sentence is slightly misleading since the tool name indicates a game boxscore. The second sentence clarifies it returns both teams' player lines for a game, so the overall purpose is clear. It doesn't explicitly distinguish from sibling tools like mlb_game or mlb_player_stats, but the name and content scope do so implicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like mlb_game, mlb_player_stats, or mlb_game_play_by_play. There is no mention of prerequisites, such as needing a completed game or how to find the game id. The description does not include any exclusion or preference context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that it returns a page of pins, lists the output fields, and notes that data is public from profile pages. With no annotations, it carries the transparency burden, but it omits details like pagination control, rate limits, or error behavior, which would be valuable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences with no fluff: the first states the purpose, the second enumerates the return fields, the third provides data source context. Every sentence adds value and the description is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool, the description is reasonably complete, but it lacks information on how pagination works (e.g., next-page token) and does not differentiate from sibling Pinterest tools. Since no output schema exists, the description could have compensated with more return structure details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema fully describes the only parameter (username) with 100% coverage, so the description adds no additional semantic nuance. The baseline of 3 applies since the parameter is adequately documented by the schema itself.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get a Pinterest user's own pins' with a specific verb and resource, and it enumerates the returned fields (title, description, image, board, pinner). It distinguishes from sibling tools like pinterest_user or pinterest_user_boards by emphasizing 'own pins,' though it does not explicitly name those alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives is provided. It does not mention when to choose this over pinterest_user, pinterest_user_boards, or pinterest_pin, nor does it state any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description notes that the data is 'credential-free public' implying no authentication needed, and describes the source. However, with no annotations, it does not disclose rate limits, pagination behavior beyond schema, or other traits like idempotency. Some context is added but incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, no redundant information. Concise and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and a moderate number of parameters (5). The description only vaguely mentions 'normalized event rows' without detailing what fields are returned. This leaves agents guessing about the output structure, which is critical for a listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All five parameters have descriptions in the input schema (100% coverage). The description adds no extra meaning beyond what the schema already provides, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists Polymarket events and specifies the data source (Gamma events JSON). It distinguishes itself from sibling tools like polymarket_event_detail or polymarket_events_similar by focusing on listing all events.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus siblings such as polymarket_event_detail or polymarket_events_similar. An agent would need to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. States it is a public read operation but does not disclose rate limits, authentication needs, or data freshness. Minimal behavioral context beyond the obvious.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that front-load the purpose. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple one-parameter tool, but lacks information about output format, error conditions, or relationship to sibling tools. Slightly under-specified given no output schema and no behavioral annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description for the single parameter. The tool description adds no additional meaning beyond the schema, so baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Name and description clearly specify the action (Get), resource (Polymarket token midpoint), and scope (for one token id). Distinguishes from sibling tools like polymarket_token_price or polymarket_token_orderbook.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as polymarket_token_price or polymarket_token_orderbook. Does not mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavior. It states that returns are for up to 25 token ids and requires no authentication. However, it does not disclose behavior when more than 25 ids are provided, rate limits, data freshness, or the exact response format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: the first states the core purpose, the second adds important authentication context. Both sentences are valuable and there is no unnecessary information. It is efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema, the description should explain the return structure but does not. It mentions the limit of 25 token ids and authentication-free nature, but lacks details on input structure (how to pass tokens in the body) and output format (e.g., mapping of token ids to midpoints). This leaves gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'body' is described in the schema as 'Token ids request body', which is vague. The description repeats this without adding details about the expected format (e.g., array of strings, how to indicate token ids). Schema coverage is 100% but the description adds no new meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get Polymarket token midpoints', specifying the verb and resource. It mentions returning public CLOB midpoints for up to 25 token ids. However, it does not distinguish from the sibling tool 'polymarket_token_midpoint' (singular), missing an opportunity to clarify when to use the batch version.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains that the tool uses credential-free public market data and does not require authentication, providing context for when to use it. However, it does not mention when not to use it or suggest alternatives (e.g., the singular version for a single token id).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It only states the tool returns the spread, but does not mention rate limits, authentication needs, or any side effects. No behavioral traits beyond basic function are described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long with no unnecessary information. It is front-loaded with the core purpose and immediately conveys the function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description provides the basic purpose but does not explain what 'spread' represents or the format of the return value. This could leave the agent uncertain about how to interpret the output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with the parameter 'token_id' already described as 'Polymarket CLOB token id'. The description adds no additional meaning beyond what is in the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool retrieves the public CLOB spread for one Polymarket token id. The verb 'Get' and resource 'Polymarket token spread' are specific and distinguish this from sibling tools like polymarket_token_midpoint or polymarket_token_price.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description does not mention any prerequisites, conditions, or exclusions, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so description must fully disclose behavior. It states 'Faithful pass-through of Redfin's public similars resource' implying no transformation beyond normalization, but lacks details on rate limits, auth requirements, error handling, or what happens for invalid property IDs. Minimal disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no fluff. Purpose front-loaded in first sentence. Actionable and scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description mentions 'normalized listing rows' which provides some clue about return format. However, lacks details on fields included, number of results, or edge cases. Adequate for a simple tool but incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Single parameter property_id with schema description 'Redfin property id'. Schema coverage is 100%, so description adds no extra meaning. Does not specify format or how to obtain the ID.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'Get' and specific resource 'Redfin comparable listings'. Distinguishes from sibling tools like redfin_search and redfin_property by focusing on similar listings. Mentions output format 'normalized listing rows' and pass-through nature.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives such as redfin_search or redfin_property. No mention of prerequisites, context, or situations where it should not be used.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It indicates a read operation ('returns public store typeahead suggestions'), which is non-destructive. However, it does not disclose rate limits, authentication requirements, or potential costs (e.g., API usage). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with key information front-loaded. No unnecessary words, and the purpose is immediately clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema provided. Description mentions returning 'products and collections' as suggestions, but does not specify the structure (e.g., array of objects with ids/names). For a typeahead, this is somewhat adequate but leaves ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with descriptions for all three parameters. The description adds minimal value beyond the schema, simply stating 'typeahead suggestions' which implies the query parameter. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool suggests products and collections inside a Shop.app shop, and returns public typeahead suggestions. It distinguishes from siblings like shop_app_search (full search) and shop_app_suggestions (recommendations) by the specific typeahead focus, but does not explicitly differentiate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like shop_app_search or shop_app_suggestions. The description implies usage for real-time suggestions but lacks explicit context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the endpoint is credential-free and uses Ajax, and that the handle is resolved to a product ID. However, it does not mention error behavior (e.g., invalid handle), rate limits, or the exact nature of 'normalized' output. This is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at three sentences with no wasted words. It front-loads the core purpose. Minor improvement could be adding a more explicit first sentence that directly states the action, but it is already clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite a small parameter count and 100% schema coverage, the description lacks detail about the return format (e.g., fields, pagination) since no output schema exists. It only says 'normalized recommended products,' which is vague. The 'intent' parameter has schema description but is not elaborated in the tool description. This leaves the agent guessing about what data to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents each parameter. The description adds value by explaining that 'handle' is resolved to a Shopify product ID, which helps the agent understand its role. This is a baseline contribution, not exceptional.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists Shopify product recommendations and explains it returns normalized recommended products from a specific endpoint. It mentions the handle-to-id resolution, giving a precise verb+resource. However, it does not explicitly distinguish from sibling tools like shopify_product or shopify_products, which are about individual product retrieval rather than recommendations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for fetching product recommendations, but it provides no explicit guidance on when to use this tool versus alternatives (e.g., when to use shopify_product for a single product vs recommendations). No when-not or alternative tool names are mentioned, leaving the agent to infer context from sibling tool names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses a useful behavioral detail: empty result pages return 200 with empty array. However, it omits other traits like rate limits, authentication needs, or whether results are paginated beyond the parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no waste. Front-loaded with purpose, then adds a unique behavioral note. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is straightforward (3 params, simple list). Description explains empty page behavior but doesn't describe the output format (e.g., product fields) or pagination details. Adequate for a simple tool, but could add value for agents unfamiliar with Shopify.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions for all three parameters. Description adds no extra meaning beyond schema, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'List Shopify products' with verb and resource. While it doesn't explicitly differentiate from sibling tools like shopify_product, the scope is clear. Distinction from siblings is partially implied by the plural 'products' vs singular listings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives (e.g., shopify_collection_products or shopify_product). The note about 'public /products.json endpoint' implicitly suggests public stores only, but no explicit when-not or alternative mentions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions it returns data from a 'credential-free public JSON' API, which is helpful. However, with no annotations, it fails to disclose potential behavioral traits like rate limits, caching, or data freshness. For a simple read operation, this is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences packing the source, return fields, and credential-free nature. Every word is useful, with no fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema), the description covers the basics: match detail fields and data source. However, it omits potential error states, response structure, or any limitations, which a complete description should include.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides 100% coverage of the single parameter 'id' with a clear description. The tool's description does not add additional meaning beyond what the schema already conveys, so the value added is minimal.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the tool returns a single match's detail (teams, score, status, venue, referee). The purpose is unambiguous, though it doesn't explicitly distinguish from sibling tools like sofascore_event_lineups or sofascore_event_statistics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus its siblings. The description does not mention alternatives or exclusions, leaving the agent to infer usage context from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries the burden. It discloses that the tool returns normalized profiles from a specific service and that private profiles may error. However, it lacks details on pagination behavior, rate limits, or what happens with empty results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences, front-loaded with purpose, followed by source and error conditions. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description does not explain the return structure or pagination behavior. It mentions 'normalized public follower profiles' but lacks specifics on fields or handling of offset/limit.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already explains each parameter. The description does not add any extra meaning or context beyond what is in the schema, thus baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Spotify public profile followers, using the verb 'Retrieve' and specifying the resource. It distinguishes from siblings like spotify_profile and spotify_profiles_search by focusing on followers, though not explicitly contrasting.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like spotify_profile or spotify_profiles_search. The warning about private profiles hints at limitations but doesn't help the agent choose among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, yet the description fails to disclose behavioral traits such as pagination, rate limits, error handling for invalid IDs, or authentication requirements. The description simply states the return type without fuller behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long with no extraneous information. It efficiently explains the tool's purpose and parameter dependency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema), the description adequately conveys the basic purpose and parameter source. However, it lacks details on response structure, error conditions, and usage limitations, which would help complete the picture for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the schema description already explains that 'id' is a category type id from the category endpoint. The description adds minimal additional value by mentioning it retrieves explore videos, but does not elaborate on valid id values or formatting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves the TikTok explore feed for a category and returns explore videos. It specifies the resource (explore feed for a category) and the action (retrieve), distinguishing it from sibling tools like tiktok_category or tiktok_trending.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The description does not mention when to choose tiktok_explore over tiktok_trending, tiktok_category, or other TikTok tools, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description bears full burden. It only says 'retrieve' and 'returns payload' without disclosing any behavioral traits (e.g., rate limits, authentication, error handling).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, no wasted words. Efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with one parameter and no output schema, the description is adequate but lacks details about the returned payload content. Could be more informative for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the description adds no additional meaning beyond the schema's description of 'id' as 'TikTok video id'. Baseline of 3 applies as schema does the work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Retrieve') and resource ('TikTok video details') for a given video id, which is distinct from sibling tools like tiktok_profile or tiktok_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives or when not to use it. The description only states what it does, not the context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, but the description is brief and does not disclose behavioral traits such as pagination behavior, authentication requirements, rate limits, or data freshness. It only states the basic retrieval action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the verb 'Retrieve'. Every word serves a purpose, no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with no output schema, the description is adequate but lacks details about the return format, behavior when params are omitted, or how the 'Spotlight' materials differ from other lists.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% description coverage (both page and limit are described). The description adds no additional parameter context beyond what the schema provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves TikTok Top Ads Spotlight materials handpicked by TikTok Creative Center, using a specific verb+resource. It distinguishes from sibling tools like tiktok_top_ads_list by noting the curation aspect.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives (e.g., tiktok_top_ads_list, tiktok_top_ads_analysis). The description only states what it does without context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states the tool returns suggestions but does not disclose behavioral traits such as authentication needs, rate limits, or the nature of the suggestion algorithm. The description is too minimal to inform the agent about side effects or constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at two sentences, with no redundant information. It directly states the action and the source.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of many sibling tools, the description is adequate but minimal. It lacks information about the output format (no output schema) and does not help the agent understand when this tool is the best choice among alternatives.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters. However, the description adds no additional meaning beyond the schema. It does not explain valid values for 'scenario' or the impact of 'count'. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Retrieve TikTok Top Ads suggestions') and explicitly identifies the resource ('TikTok Creative Center'). It distinguishes this tool from siblings like tiktok_top_ads_list by specifying it returns 'suggestions' rather than full ad data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus other TikTok top ads tools (e.g., tiktok_top_ads_list, tiktok_top_ads_recommend). The description lacks any indication of context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the tool is credential-free and returns normalized candidates, implying read-only behavior. However, it omits details like rate limits, result ordering, or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, two sentences, and front-loaded with the core action. Every sentence provides valuable information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema and the complexity of 8 parameters, the description provides a high-level purpose but lacks details on return format, pagination, or ordering. It is adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with all 8 parameters described. The description does not add additional meaning beyond the schema, as it only repeats the purpose rather than elaborating on parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs autocomplete for TripAdvisor locations and places, using a specific verb and resource. It distinguishes from sibling tools like tripadvisor_search by focusing on typeahead functionality, but does not explicitly differentiate from tripadvisor_search for general queries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool vs alternatives such as tripadvisor_search or tripadvisor_hotels. The description lacks explicit context on usage scenarios or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It mentions 'public credential-free GraphQL listing data', indicating no auth required, but lacks disclosure on pagination behavior, error handling, or rate limits. Partial transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys purpose and key attributes. However, it includes slightly verbose phrasing ('normalized...from public credential-free GraphQL listing data') that could be trimmed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 13 parameters (many filters) and no output schema, the description is too brief. It fails to explain return format, how filters combine, or common error scenarios. More context is needed for effective tool use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already provides parameter documentation. The description adds no extra meaning beyond what the schema offers, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Search'), the resource ('TripAdvisor hotels'), and the output ('listing results'). It distinguishes from siblings like tripadvisor_search (general) and tripadvisor_place (single place details).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit usage guidance is provided. The description does not indicate when to use this tool versus alternatives like tripadvisor_search or tripadvisor_autocomplete, nor does it mention any prerequisites or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must fully disclose behavior. It only states the return type (summary profile) and source (public business page). It does not mention input requirements (e.g., valid slug), error handling, or that the operation is read-only. For a simple read tool, more transparency is expected.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the verb and resource. Every word contributes meaning, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (one required parameter, no output schema, no nested objects), the description provides the core purpose and return type. However, it lacks details on behavioral expectations (e.g., idempotency, data freshness) that would make it complete for reliable agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema defines one parameter 'slug' with the description 'Trustpilot business slug'. The tool description does not add further semantic meaning beyond the schema. With 100% schema coverage, a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'Trustpilot business profile', and mentions it parses from the public business page. It distinguishes itself from sibling tools like 'trustpilot_business_reviews' by focusing on the profile summary, but does not explicitly contrast with alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is provided on when to use this tool versus siblings like trustpilot_business_search or trustpilot_business_reviews. The usage is implied by the function description, but no when-not-to-use or alternative cues are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavioral traits. Only mentions 'normalized' results, but omits auth requirements, rate limits, or any side effects. Minimal behavioral insight.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence plus an explanation of return source. No fluff, but could benefit from slightly more structure (e.g., bullet points). Highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with 4 params fully described in schema and no output schema, description states source and normalization. Could hint at response structure, but overall adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all 4 parameters with descriptions, so the tool description adds no extra value beyond what's in the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it searches Trustpilot business units and returns normalized results. Differentiates from sibling tools like trustpilot_business (single unit lookup) and trustpilot_category_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., trustpilot_business for specific ID lookup, trustpilot_business_reviews for reviews). Lacks any when/when-not instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only says 'returns open/close status' but does not mention authentication needs, rate limits, error handling, or what happens for invalid markets.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two short sentences front-loading the purpose. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description provides the essential purpose and an example. However, it does not specify the output format (e.g., boolean or string) or clarify what 'status' includes.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, baseline 3. The description adds 'such as US' as an example but does not enumerate valid markets or provide format details. Adequate but minimal.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'returns' and the specific resource 'Yahoo Finance open/close status for a market such as US'. It distinguishes from sibling yahoo_finance_* tools by focusing solely on market open/close status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like yahoo_finance_market_summary or yahoo_finance_ticker_quote. The description merely states what it does without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses that data availability depends on Yahoo providing it, and restricts to ETF/mutual fund symbols. However, it does not mention other behavioral traits such as rate limits, read-only nature, or what happens if no data is found.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long and directly conveys the purpose without any extraneous information. It is appropriately front-loaded and concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter, and the description covers the core purpose. However, without an output schema, it would benefit from mentioning the structure of the returned data (e.g., a list of events with dates and amounts).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter 'symbol', with a schema description already specifying 'Yahoo Finance symbol such as SPY'. The description adds no additional semantic guidance beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool returns capital gain events for ETF or mutual fund symbols. It specifies the resource (capital gains) and the verb (returns), and implicitly distinguishes from other yahoo_finance_ticker_* tools, though it could be more explicit about what constitutes a capital gain event.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like yahoo_finance_ticker_dividends or yahoo_finance_ticker_earnings. No when-not-to-use or prerequisite information is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Minimal behavioral info beyond what the name implies. No annotations provided, and the description does not mention output format, pagination, rate limits, or authorization needs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences with no redundant information. Efficiently communicates core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description is adequate but lacks details about 'normalized' entries and potential limitations, especially given many related YouTube tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter 'id', so description adds no additional meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it retrieves the shorts tab and returns normalized short-form video entries, distinguishing it from sibling tools like youtube_channel_videos.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives such as youtube_channel_videos or youtube_search. Does not mention prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the data is credential-free and from Agoda's own content source, which is helpful. However, it does not detail potential limitations such as stale data, partial responses, or error behavior for invalid IDs, leaving some behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences, each adding value: purpose, return fields, and data source/credential status. No fluff, though 'Get Agoda activity detail' and 'Returns full activity detail from Agoda' are slightly redundant, so not a perfect 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter tool with no output schema, the description is adequate: it lists return fields and notes the public nature of the data. However, it omits details about response structure, image URL formats, or reliance on a prior search (only in schema), leaving moderate gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameter is fully described in the schema as a numeric activity id from a prior search. The tool description does not add any additional parameter semantics, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and the resource ('Agoda activity detail'), and enumerates the specific content returned (title, description, duration, categories, images). It distinguishes itself from sibling search tools like agoda_activities_search by focusing on detail retrieval for a single activity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives. It does not mention that an activity_id from a prior search is required or point to the search tool. The need for a prior search is only implied via the schema's parameter description, not the tool description itself.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. While it mentions pagination and output fields, it omits behavioral details such as sorting order, rate limits, or whether reviews are in reverse chronological order, which are critical for an API tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loads the core purpose, and every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description should compensate by detailing return structure. It only mentions reviewer name and location, missing essential fields like rating, date, and text. Pagination details (page size, total results) are absent, leaving significant gaps for agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters adequately. The description adds no semantic value beyond confirming pagination context; baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and resource 'host reviews', explicitly mentions output includes reviewer name and location, and distinguishes from similar sibling tools like airbnb_room_reviews by specifying 'host'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (when you need host reviews) but does not provide explicit guidance on when to use this tool vs. alternatives like airbnb_room_reviews, nor does it mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that data is 'credential-free public AniList data' and paginated, indicating read-only behavior. However, no annotations are provided, so the description partially compensates but lacks details on rate limits or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with the action and resource, followed by details. No redundant text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description adequately explains response contents (name, role, occupations, image) and pagination. Lacks total count info but sufficient for a simple listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%; the description adds no extra meaning beyond the schema's parameter descriptions. It implies pagination control via page and per_page but does not enrich semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and resource 'anime's staff', and specifies return fields (name, production role, occupations, image). It implicitly distinguishes from siblings like anime_character, but does not explicitly differentiate from anime_character_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The description does not mention when to choose this over anime_character or anime_title_characters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for behavioral disclosure. It only mentions the source API and normalized metadata, lacking details on rate limits, authorization, error handling, or whether the lookup is read-only. Significant gaps exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise with two sentences, front-loading the purpose. It is efficient but could include more context without harming conciseness, such as noting the output format.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given three parameters and no output schema, the description provides the basic purpose and API source. However, it does not explain what 'normalized show metadata' includes, nor does it cover parameter interactions or limitations. Adequate but leaves gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of parameters with descriptions, so the description does not need to add much. However, it adds no additional meaning beyond what the schema already provides, such as parameter constraints or formatting hints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Apple Podcasts show details using the iTunes Lookup API. The verb 'retrieve' and resource 'show details' make the purpose specific, and it distinguishes from sibling tools like apple_podcasts_search and apple_podcasts_show_episodes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining show details by ID, but provides no explicit guidance on when to use this tool versus alternatives such as apple_podcasts_search or apple_podcasts_show_episodes. No exclusions or conditions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It does not disclose rate limits, data freshness, authorization needs, or pagination behavior beyond 'one page'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with purpose, no redundant words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description explains the tool's basic function but lacks details on output structure, error handling, or pagination limits. Adequate for a simple retrieval tool but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds value by clarifying mutual exclusivity of 'id' and 'app_id' parameters, which is not evident from schemas alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves App Store reviews (verb+resource) and specifies it returns one page. It is distinct from siblings like appstore_ratings, though not explicitly differentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description advises providing either 'id' or 'app_id', which is helpful but does not mention when to use this tool versus alternative app store tools or any prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It adds 'normalized' and optional free-text search behavior, but omits pagination behavior, required parameter dependencies, and result shape details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with front-loaded domain/resource naming. Every sentence contributes meaningful information and there is no waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 7 params, no output schema, and no annotations, the minimal description leaves gaps in return-value detail and pagination. It is adequate for basic selection but not full invocation understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description only echoes the search_text behavior already described in the schema without adding new parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Returns'), identifies the resource ('guest reviews for a Booking.com hotel'), and signals normalized output. This clearly distinguishes it from sibling tools such as booking_attractions_reviews and tripadvisor_reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or alternative guidance is provided. The phrase 'hotel reviews' implies domain context, but it does not exclusions or comparisons with siblings like booking_attractions_reviews.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description mentions 'normalized article cards' but lacks details on return format, pagination, authentication, or rate limits, leaving behavioral traits unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, front-loaded and efficient. Minor improvement possible by consolidating into one sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with two optional parameters and no output schema, the description is adequate but lacks details on return structure or pagination, leaving it somewhat incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds no new meaning beyond the schema's parameter descriptions (e.g., 'default all' for category).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns normalized article cards from CoinGecko Learn, distinguishing it from sibling tools like coingecko_news or coingecko_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The description implies it handles 'Learn articles,' but does not specify exclusions or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It states the tool 'searches stored Chrome Web Store item snapshots', implying a read-only, non-destructive operation. However, it does not explicitly confirm mutation behavior, response structure, or other behavioral traits (e.g., pagination, rate limits). The description adds some value but leaves gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence followed by inline enum lists, which is moderately concise but somewhat verbose due to listing enums. Front-loading is decent with the main action stated first. Some space could be saved by omitting or moving enums to the schema, but it remains readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 16 parameters and no output schema, the description covers the search scope and all filter options. It does not describe the return format or pagination behavior, but sibling tools of similar structure likely follow a consistent pattern. The description is complete enough for a search tool with well-documented parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 16 parameters. The description lists the enum values for item_type, sort, status, and manifest_version, which adds marginal value by providing inline sample values. However, it does not add meaning beyond what the schema provides for most parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'search' and the resource 'Chrome Web Store dataset' with the scope 'stored Chrome Web Store item snapshots'. It distinguishes from sibling dataset tools by focusing on Chrome extensions specifically, and lists enums for item_type, sort, status, and manifest_version, making the purpose very specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus other sibling tools like 'datasets_chrome_extensions_facets', 'datasets_chrome_extensions_item', etc. It does not mention alternatives, prerequisites, or context for choosing this search over other dataset search tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It honestly discloses the dataset's provenance and non-exhaustive nature ('crawled public catalog', 'not a full catalog'), which is valuable. It also lists sort options. However, it does not explicitly mention that this is a read-only operation, return format, pagination behavior, or any other operational quirks beyond what the schema already implies. It adds some context but leaves many behaviors undisclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: two sentences plus a sort list. It front-loads the core purpose in the first sentence and uses the second to add important context about data source and limitations. The sort enum feels slightly redundant with the schema but is still a useful inline reference. Overall, it is well-structured without wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 20 parameters, full schema coverage, and no output schema, the description provides the essential purpose and data source context. However, it lacks some context that would help an agent fully understand the tool, such as the output shape, examples, or relationship to other dataset tools (e.g., facets, item). It is adequate but not richly complete for a high-complexity tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides 100% parameter coverage with descriptive text for all 20 parameters, so the baseline is 3. The description's only parameter-related addition is repeating the sort enum, which is already fully documented in the schema. There is no extra semantic value added for parameters, so it stays at the baseline without earning a higher score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches a Goodreads books dataset, specifying the crawled public catalog in a search index and noting it is not a full catalog. This provides a specific verb (search), resource (Goodreads books dataset), and scope (partial crawled catalog), but it does not explicitly contrast with sibling tools like goodreads_search or datasets_goodreads_books_item, so it stops short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by defining the dataset source and limitation ('not a full catalog'), which suggests when to use this tool (search this crawled dataset) and hints that it may not suffice for full catalog needs. However, it gives no explicit when-to-use/when-not-to-use guidance or alternatives, so it relies on implication rather than clear direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the operation (returns counts) and lists valid facets, but does not explain how filters (e.g., q, status) affect the counts, whether counts are for the full dataset or filtered results, or any pagination/limits. This lacks essential behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences, front-loaded with the primary purpose and the facet enum. Every sentence earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 12 parameters and no output schema, yet the description does not explain the returned data structure or how filters interact with facet counts. It is not complete enough for an agent to fully anticipate tool behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description repeats the facet enum already present in the schema and adds no additional meaning about parameter semantics or format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the operation ('Facet') and resource ('PitchBook companies dataset'), and explicitly states it returns 'terms aggregation counts.' This distinguishes it from sibling tools like datasets_pitchbook_companies_search and datasets_pitchbook_companies_item.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for obtaining facet counts but does not explicitly state when to use it over search or item tools, nor any exclusions. The phrase 'Returns terms aggregation counts' implies usage for aggregation, but no direct alternatives are named.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It states that the response contains 'terms aggregation counts', which implies a read-only operation, but it does not explain the response structure, pagination, limits, or how filters like q and run_id interact with facets. The description lacks crucial behavioral details for an agent to reliably parse and use the result.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loads the core action, and lists the facet enum efficiently. Every sentence serves a clear purpose, and there is no wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is minimal for a tool with 8 parameters and no output schema. It does not explain the return format of 'terms aggregation counts' (e.g., buckets with keys and doc_count), nor how the facet tool relates to the search tool for exploration workflows. An agent would struggle to know what to expect in the response without external knowledge of typical Elasticsearch/OpenSearch facets.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of parameter descriptions, so the baseline is 3. The description adds no meaning beyond repeating the facet enum, which is already present in the schema. It does not explain how parameters like q, run_id, or year filters influence the facet counts, though the schema already defines these filters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns terms aggregation counts for the PitchBook limited partners dataset, distinguishing it from sibling search/item tools which return records. The facet enum is explicitly listed, leaving no ambiguity about the tool's purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for retrieving aggregation counts rather than raw data, but it does not explicitly state when to use this tool versus the sibling search or item tools. No exclusions or alternative usage guidance is provided, so the agent must infer context from the tool name and sibling names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral burden. It discloses that the directory is current, public, and includes sports and leagues. It does not describe response pagination, the exact shape of the directory, or any operational quirks; for a zero-parameter listing, this is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The substantive content is concise and front-loaded: it states what is returned and how the result is reused. The opening noun phrase 'DraftKings Sportsbook sports and leagues' is redundant with the tool name and adds no value, which slightly penalizes an otherwise efficienty structured definition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity of a zero-parameter public folder, the description covers the main use case: fetch the directory and feed league IDs into odds/futures calls. It lacks a description of the returned response structure (e.g., whether it's a flat list, how for each league is keyed), and there is no output schema to fill that gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters and 100% coverage, so the schema already communicates everything about parameters. Baseline is 4 for no-parameter tools, and the description adds the useful relationship: league IDs are used as league_id by /draftkings/sportsbook/odds and /futures.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the resource: DraftKings Sportsbook's current public sport and league directory, using 'Returns' as the verb. It distinguishes the resource from event/odds tools by stating its league IDs are consumed by odds and futures endpoints. It does not explicitly contrast against sibling 'draftkings_featured_leagues', which keeps it from a perfect clarity score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a concrete usage hint: league IDs returned here are accepted as league_id by the odds and futures endpoints, so an agent can infer when this directory call is the prerequisite. But it never names alternatives like draftkings_featured_leagues or says when not to use this tool, so the guidance is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral burden. The verb 'List' implies a read-only operation and the description usefully mentions live bidding state, but it does not disclose behavior around invalid ids, inactive streams, pagination, freshness, or authentication requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences with no filler. The first sentence states the primary purpose directly, and the second adds the important live auction/bidding context. The content is front-loaded and every sentence contributes.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter, low-complexity listing tool, the description covers the essential input, the result category, and a distinguishing output detail: live bidding state. It does not document output structure beyond that, but with no output schema present, the high-level behavior is mostly sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully documents the single required parameter: 'id' is described as 'eBay Live stream/event id', giving 100% schema description coverage. The tool description adds no extra parameter detail beyond matching the id to a stream, so the baseline score is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource ('List an eBay Live stream's featured items') and adds a clear outcome: returns currently featured/auction items with live bidding state. It is not explicit about how this tool differs from sibling tools like ebay_live_stream or ebay_live_streams_batch, so it stops just short of fully differentiating itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives such as ebay_live_stream, ebay_live_streams, or ebay_live_streams_batch. The agent must infer selection entirely from the tool name and nearby sibling names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It states the tool is a read operation that returns buyer reviews, which is transparent for a simple GET, but it omits details like pagination behavior, default sort order, or any API constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded, with two sentences that clearly state the function. The second sentence is slightly redundant with the first but adds the 'buyer reviews' detail, so minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of both annotations and an output schema, the description provides only high-level return information ('buyer reviews'). It does not describe the review content, sorting defaults, or how offset works, leaving gaps for a tool with three parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no parameter-specific meaning beyond the schema; it does not explain how 'sort' or 'offset' affect results.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('Etsy listing reviews'), clearly stating the tool retrieves buyer reviews for a single Etsy listing. This distinguishes it from sibling tools like etsy_shop_reviews, which target shop-level reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, exclusions, or how it differs from etsy_shop_reviews or other review tools, leaving the agent to infer usage from the name and parameter.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral disclosure burden. It openly covers credential-free/public data access, pagination, and the non-obvious behavior that page 1 of well-known lists may come from a faster live source while other pages fall back to the public list page. This is meaningful, non-obvious behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The content is compact and the valuable behavioral caveat appears in the final sentence, but the first sentence repeats essentially the same noun phrase as the second sentence ('Get a Goodreads Listopia list' vs 'Returns a Goodreads Listopia list'). This redundancy gives it a mid-tier conciseness score rather than a tighter 4 or 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter, credential-free read tool, the description adequately covers the resource type, input behavior, source behavior, and fallback path. It does not go deep into output shape or list discovery, but those are not necessary for basic invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with id and page already documented. The description's mention of 'by id' and 'paginated' somewhat mirrors the schema but adds little beyond it, such as how IDs are formatted or how to discover them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the action ('Get') and the specific resource ('Goodreads Listopia list, ranked book list'), and it notes retrieval is by id. This is sufficiently specific, though it does not explicitly differentiate itself from sibling tools like goodreads_lists or goodreads_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains what the tool does and mentions pagination, but it gives no guidance on when to choose this tool over alternatives, how to discover list IDs, or when another Goodreads tool would be more appropriate. No exclusions or alternative conditions are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses it fetches results, but does not specify read-only nature, auth needs, rate limits, or side effects. Adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise at two sentences, no unnecessary words. The first sentence names the API, the second describes the action efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema, the description is mostly complete. It explains the action and parameter, but lacks details on the format of search results (e.g., tickers, companies). Minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter 'q', and the description mentions 'provided keyword' with an example, adding no extra meaning beyond the schema. Baseline score applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it fetches normalized search results from Google Finance for a keyword, using a specific verb and resource. It distinguishes from sibling tools like google_finance_quote or yahoo_finance_search by focusing on keyword search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like google_finance_company or google_finance_quote. The description does not provide context for selection among many finance-related siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states it returns category ids but does not disclose any behavioral traits such as rate limits, authentication needs, or side effects. Minimal information for a retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences that are front-loaded with the key action and output. No extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there are only two optional parameters, no output schema, and no annotations, the description is fairly complete for a simple list tool. It covers the purpose and output. However, it could mention that categories are specific to Google Play and that country/lang may affect results, but overall adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for both parameters (country and lang). The description does not add any additional meaning beyond what the schema already provides, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Retrieve'), the resource ('Google Play app categories'), and the output ('category ids found in the Google Play apps navigation'). It is specific and distinguishes from sibling tools like googleplay_app or googleplay_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, contexts, or exclusions. Among many siblings, there is no differentiation help.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states 'Returns public profile details' without specifying permissions, rate limits, or what constitutes 'public profile details'. Minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no redundant information. Front-loaded with the verb and resource, efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so the description should elaborate on return values. It generically says 'public profile details' without listing fields (e.g., biography, follower count). Incomplete for a tool with no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema describes the single parameter 'username' as 'Instagram username', and the description adds no additional meaning. With 100% schema coverage, baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Retrieve'), the resource ('Instagram user profile'), and the input ('by username'). It distinguishes from sibling tools like instagram_post and instagram_reels which handle posts and reels respectively.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for profile retrieval but does not explicitly state when to use this tool versus alternatives. No mention of prerequisites or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the fallback mechanism (tries PCSX first, then SmartApply) and notes it is credential-free public ATS JSON. However, it does not mention error handling or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with the main action first, followed by parameter details and behavioral notes. It is concise with no superfluous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Lacks output schema; description only states 'Credential-free public ATS JSON' without detailing the return structure. Pagination details are implied but not fully explained. Adequate for a listing tool but incomplete on output format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value for 'tenant' and 'domain' by explaining their origins, but other parameters (limit, offset, query, location) are already well-described in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists an Eightfold job board with paging. It specifies the resource and action. However, it does not explicitly differentiate from sibling tools like jobs_eightfold_job, other than by the name 'board' which implies a list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives (e.g., other job board tools). It explains parameters but does not provide usage context or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description merely says 'returns technical names' without disclosing behavior like read-only nature, response format, or any side effects. Minimal disclosure beyond basic purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences effectively communicate the tool's purpose with no unnecessary words. Efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with one optional parameter and no output schema, the description is adequate but lacks details on default behavior when country is omitted and what 'technical names' entail. Could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (country parameter described as 'Two-letter country code'), but the description adds only the phrase 'technical names' which is not in the schema. This adds marginal context but doesn't significantly enhance understanding of the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves JustWatch age certifications for a country, specifying it returns 'technical names,' which differentiates it from sibling tools like justwatch_genres or justwatch_providers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for a country but provides no explicit guidance on when to use or not use this tool versus alternatives. The optional country parameter is mentioned but not clarified for default behavior.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It only states 'credential-free public,' which hints at authentication requirements but omits details such as default behavior when country is omitted, response structure, error handling, or rate limits. This is insufficient since it is not a simple identity tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences; the first states the action and resource, the second adds key qualifiers ('credential-free', 'public', 'for a country'). No wasted words, but slight improvement could be made by front-loading the purpose more directly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the many justwatch sibling tools, the description successfully identifies the scope (providers catalog by country). However, it lacks completeness regarding return format, default country handling, error scenarios, and any additional context that would aid an agent using the tool. With no output schema, more detail would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of parameters (just 'country' with description 'Two-letter country code'). The description adds context by linking it to the provider catalog, but does not clarify the optionality or behavior when omitted. Baseline score of 3 is appropriate as schema already defines the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get JustWatch providers' and specifies it returns the 'credential-free public JustWatch provider catalog for a country.' This verb+resource combination and the added context effectively distinguish it from many justwatch sibling tools that deal with titles, offers, or episodes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving provider catalogs by country, but does not explicitly state when to use this tool versus alternatives like justwatch_search or justwatch_provider_titles. No guidance on when not to use or prerequisites is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states it is a lookup, omitting details on authentication, rate limits, error handling, or return structure. For a read-only operation, this is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence (22 words) that immediately states the tool's purpose, followed by an illustrative example. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description should explain what a 'title' includes or any pagination/error behavior. It does not, making it incomplete for an agent needing to interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, setting a baseline of 3. The description adds value for the 'id' parameter by providing example formats (tm..., ts...), but adds nothing beyond schema for 'country' and 'language'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a JustWatch title using a raw GraphQL id, distinguishing it from search or other lookup tools. Examples of ids (e.g., tm92641, ts287292) clarify the input format.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when a raw id is available, but does not explicitly contrast with sibling tools like justwatch_search or justwatch_title. No when-not-to-use or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries full burden. It explicitly states the tool is credential-free and returns public data, indicating a read-only, no-auth operation. It also specifies the output is a settled historical row, providing clear behavioral context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence of 14 words, efficiently conveying core purpose and behavior. However, it omits some details (e.g., 'normalized settled' meaning) that could aid understanding without adding length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given one required parameter and no output schema, the description provides adequate baseline info: returns one row, public, credential-free. But it lacks details on error handling, rate limits, and the structure of the returned row, which would be helpful for complete context among many Kalshi sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter 'ticker', which is described as 'Kalshi historical market ticker'. The description adds that it returns a normalized settled row for that ticker, but this is more about the output than parameter meaning. It does not significantly enhance parameter semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it returns one normalized settled historical market row, specifying the resource (historical market detail) and action (returns). Distinguishes from siblings like kalshi_historical_market_history by emphasizing a single row, but does not explicitly differentiate from all similar tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like kalshi_historical_market_history or kalshi_historical_markets. No prerequisites or exclusions described. The description merely states functionality without contextual usage advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'credential-free public market-data JSON' suggesting read-only public access, but does not explain pagination behavior, idempotency, rate limits, or what constitutes a 'multivariate event row'. This is insufficient for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, but the first sentence ('Kalshi multivariate events.') is redundant with the tool name. The second sentence provides the core functionality. It could be more tightly structured by removing the tautology.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description is too brief. It does not explain what 'multivariate events' are, how the cursor works, or what the response structure looks like. Among many Kalshi sibling tools, more context is needed to aid selection and correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the parameter schema is complete. The description adds no additional meaning to the 'cursor' or 'limit' parameters (e.g., format of cursor, default values). Baseline 3 is appropriate as schema covers technical details but description provides no extra context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized Kalshi multivariate event rows from public market-data JSON. It distinguishes from siblings by noting that the regular events endpoint excludes these rows, making the tool's unique purpose explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (when needing multivariate events not available via the regular endpoint) and notes it is credential-free. However, it does not explicitly state when not to use it or compare with other Kalshi tools beyond the regular events endpoint.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Only states 'Credential-free public data' but lacks details on read-only nature, rate limits, pagination behavior, or output structure. Insufficient for a tool with no output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with purpose. Slight redundancy between first two sentences, but overall efficient. Could be trimmed without loss.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool is simple with 3 params and no output schema. Description conveys core function but omits return format, error handling, and behavioral constraints. Adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all parameters. Description adds minimal additional meaning beyond 'for a credit role' which overlaps with schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'Get' and resource 'person's filmography'. Distinguishes from siblings like letterboxd_member and letterboxd_film by focusing on filmography. Purpose is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies use for filmography by credit role, but no explicit guidance on when to use vs alternatives like letterboxd_member. Does not mention exclusions or context cues.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description provides minimal behavioral disclosure: it mentions credential-free public data, but lacks details on pagination, rate limits, or what happens with invalid queries. The agent needs more context to understand side effects or constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with purpose, and contains no unnecessary words. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description should compensate by hinting at the result format. It does not mention what the output looks like (e.g., list of items, metadata). Additionally, it does not explain the 'type' parameter or the 'limit' default. The description is too brief for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description does not add any additional meaning beyond the schema parameter descriptions; it simply restates the purpose without elaborating on parameter usage or defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches Letterboxd and specifies the types of items searched (films, people, lists, tags). It distinguishes itself from sibling tools like letterboxd_film (specific film) or letterboxd_popular (popular items) by being a general search tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for broad search queries on Letterboxd, but does not explicitly state when to use this tool versus other Letterboxd tools (e.g., for a specific film or person). No when-not-to-use or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full burden. It only says 'returns detailed information' without specifying what that includes, side effects, or permissions. Minimal behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, no extraneous text. Highly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema is provided, and the description does not elaborate on the return structure. For a tool returning 'detailed information', more context is needed. Lacks completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of parameters with a description for the 'id' field. The tool description adds no additional meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get Linkedin Showcase Page Info' and specifies it returns detailed information by ID, distinguishing it from siblings like linkedin_company and linkedin_product.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool versus alternatives. The purpose is clear enough for inference, but no when-not-to-use or alternative mentions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It states the tool is credential-free and returns normalized data, but does not disclose error handling, rate limits, or behavior for invalid slugs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with clear structure: action first, then returned data and credential info. No redundant words, front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple lookup with one parameter, the description is mostly complete. It covers purpose, return data, and authentication. However, it could specify the format of the slug and error handling to be fully adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'slug' has a schema description that is identical to the tool description's mention. Since schema coverage is 100%, the description adds no additional meaning beyond the schema, earning a baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it gets a Metacritic TV show and lists the returned data fields. It is specific enough to distinguish from movies and games, but does not explicitly differentiate from the sibling tools for TV show reviews (metacritic_tv_critic_reviews, metacritic_tv_user_reviews).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like metacritic_browse or the review-specific siblings. The description lacks any context about prerequisites or use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It adds the constraint that it returns one player's stats and specifies the group enum values, but it does not disclose the return format, data source, rate limits, or error behavior. The read-only nature is only implied by 'Get'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and mostly front-loaded, but the first two sentences are redundant: 'Get MLB player season statistics' and 'Returns one player's MLB season statistics' state essentially the same information. The third sentence about the group enum is useful, but the redundancy prevents a higher score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively simple with three well-described parameters, and the description covers the essential input requirements. However, with no output schema and no annotations, it does not explain what the returned statistics will look like or any potential variations. It provides enough to invoke the tool correctly, but lacks richer context about the output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, providing a baseline of 3. The description adds value by explicitly enumerating the valid values for the 'group' parameter ('hitting', 'pitching', 'fielding'), which the schema does not list. It also reinforces that the tool focuses on season statistics, but does not add further detail beyond the schema for 'id' or 'season'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource ('Get MLB player season statistics') and clarifies that it returns one player's stats, which helps distinguish it from team or league stats. However, it does not explicitly name alternative sibling tools like mlb_team_stats or mlb_league_stats, so some differentiation is implicit rather than explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'Returns one player's MLB season statistics' implies this tool is for single-player season stats, but there is no explicit guidance on when to use it versus alternatives, nor any stated exclusions. The agent must infer usage context from the tool name and sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It adds useful context by noting the data is public and sourced from Pinterest's ideas pages, and discloses the return contents. However, it doesn't mention pagination behavior for the 'page of pins,' any auth requirements (though 'public' implies none), or error/edge-case behavior. This is moderate transparency but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the purpose, and contains no redundant or filler content. Every sentence adds value: one defines the action, the other details the response and data source.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema, the description does a good job explaining what is returned (metadata fields and a page of pins) and notes public data. Minor gaps remain: no mention of pagination for the pin feed or error responses, but overall the description is reasonably complete for this low-complexity tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage for the single `id` parameter, with a clear description referencing the categories list. The tool description itself doesn't add further parameter semantics beyond what the schema already provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a Pinterest 'Ideas' category's detail feed, with a specific verb and resource. It mentions the return contents (metadata and pins) and cites the source for IDs, which hints at sibling differentiation from the categories list tool. However, it doesn't explicitly name alternatives like pinterest_board or pinterest_search for when to use those instead.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives. It only implies that the ID comes from GET /pinterest/categories, but doesn't state when to choose this over pinterest_board, pinterest_pin, or pinterest_search. No exclusions or alternative tool names are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It states the tool returns public CLOB price-history points but does not mention side effects (e.g., read-only nature), authentication requirements, rate limits, or error handling for invalid token IDs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loading the purpose. It is concise and avoids fluff, though it could be slightly more structured by explicitly listing the required token_id.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and the presence of 5 parameters, the description is adequate but minimal. It does not explain the nature of 'CLOB price-history points' or how parameters like fidelity and interval affect the output, leaving some ambiguity for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the descriptions of all 5 parameters already exist. The description adds no additional meaning beyond the schema; for example, it does not clarify the relationship between 'fidelity' and 'interval' or how they interact.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves price history for a specific Polymarket token, using the verb 'Get' and specifying 'public CLOB price-history points'. This distinguishes it from siblings like polymarket_token_price (current price) and polymarket_token_midpoint (midpoint).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives like polymarket_token_price or polymarket_token_orderbook. Usage context is implied by the name and mention of 'history', but no direct guidance on when not to use or specific prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states the tool performs a search and returns results, but does not disclose behavioral traits such as read-only status, rate limits, pagination details, or authorization requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the action, and contains no unnecessary words. Every sentence contributes to understanding the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description does not explain return values or output structure (no output schema). It lacks details on sorting, result limits, or how to interpret the matching items. Given the tool has 5 parameters and no output schema, the description is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the input schema already describes all parameters. The description adds no extra semantic value beyond what is in the schema; it merely restates the search action. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs a full-text search on Product Hunt for products, users, or launches. It uses a specific verb ('search') and resource ('Product Hunt'), and distinguishes from sibling tools like producthunt_product (specific product) and producthunt_category_products (category listings).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this is a general search tool but does not explicitly state when to use it versus alternatives like producthunt_product or producthunt_category. No exclusionary guidance or mention of alternative tools is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It correctly implies a read operation ('get', 'returns') but lacks details on potential side effects, rate limits, or authentication requirements. The mention of 'public stingray detail API' adds some transparency but overall minimal depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loading the purpose. Every sentence adds value: first states what the tool does, second explains input options. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers input usage and API source, but lacks output detail. Without an output schema, agents would benefit from knowing what fields are returned (e.g., address, price, etc.). 'Normalized Redfin public property details' is vague. Adequate but incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage. The description adds value by explaining the relationship between parameters (url as primary, property_id with optional listing_id for completeness) and provides a usage pattern. This goes beyond the schema's individual descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a Redfin property and returns normalized details. It mentions the primary input methods (URL or property ID), which helps understand the tool's purpose. However, it doesn't explicitly differentiate from sibling tools like redfin_search or redfin_estimate, though the specificity of 'property' is implicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains how to invoke the tool (listing URL or property ID) but does not provide guidance on when to use this tool versus alternatives like redfin_search or redfin_similar. No 'when to use' or 'when not to use' information is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It mentions sorting by value, CIK identifier, and credential-free access, but does not disclose rate limits, pagination, or potential empty results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences efficiently convey purpose, result content, sorting, and access method. No redundant text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so description should detail return format more. It lists fields but not structure (e.g., array of objects). Lacks error handling explanation. Adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for cik and limit. The description adds 'by CIK' and 'sorted by value' context, but adds no significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns institutional holdings (13F-HR) for a manager by CIK, listing the fields and sorting. However, it does not explicitly differentiate from other SEC tools like sec_filing or sec_company_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'Credential-free public SEC data' implies no authentication needed, but there is no explicit guidance on when to use this tool versus alternatives like sec_financials or sec_insider.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions that pages are 'normalized static' and body is 'cleaned text,' but does not disclose if there are any side effects, rate limits, or required authentication. The description is minimal in behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only two sentences, front-loaded with the core purpose, and avoids unnecessary detail. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description provides essential info: the endpoint type and return format. However, it omits details about pagination behavior (beyond schema defaults) and field structure. Still, it is sufficiently complete for a simple listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with all three parameters described. The description adds no extra meaning beyond the schema; it only repeats the tool's purpose. Baseline 3 is appropriate because the schema does the work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (List), the resource (Shopify pages), and provides specifics about the endpoint (public /pages.json) and output format (cleaned text only). This distinguishes it from sibling tools like shopify_page (singular) or shopify_products.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool vs alternatives (e.g., shopify_page for a single page or shopify_collections for collections). It lacks any when-to-use or when-not-to-use context, despite the large sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries burden. It notes 'credential-free public JSON' implying read-only and open access, but lacks details on rate limits, data freshness, or potential side effects. Adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, 20 words, front-loaded with key information. No wasted words, efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and simple parameters, the description adequately covers what the tool returns. It lists the main fields, sufficient for a single entity retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter 'id' described as 'Numeric SofaScore team id'. The description does not add extra meaning beyond the schema, earning a baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the verb 'Returns' and the resource 'one team's detail', listing specific fields like identity, manager, venue, and primary competition. It distinguishes from sibling tools by focusing on core team detail rather than events or players, though not explicitly compared.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like sofascore_search or sofascore_team_events. The description only mentions it's credential-free, but does not help an agent decide between tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses that data comes from a 'credential-free public JSON' API, indicating no authentication required. However, it does not describe the output structure, pagination, or any other behavioral traits like rate limits or data completeness. This is adequate for a simple read tool but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences with no wasted words. It front-loads the key information and is easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema), the description is mostly complete. It explains what the tool does and the source. However, it could clarify what 'full squad' entails (e.g., active players, all squad members, etc.) to improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with a single parameter 'id' described as 'Numeric SofaScore team id'. The description adds minimal value beyond confirming the parameter's purpose. Since schema coverage is high, the baseline is 3, and the description does not significantly enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a team's full squad, with a specific verb ('Returns') and resource ('team's full squad'). It distinguishes from siblings like sofascore_player (individual player) and sofascore_team (team info) by focusing on squad retrieval. However, it could be more explicit about how it differs from other team-related tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus its siblings. It does not mention alternatives, prerequisites, or when not to use it. The agent must infer usage from the name and context, which is insufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It does reveal that the data is public and sourced from SoundCloud's own API, which implies a read-only, authentication-free operation, and it usefully lists playback/likes/comment/repost counts. However, it doesn't disclose absence of audio streams, pagination, rate limit, or any side-effect expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences and wastes no words. The primary scoping ('Search SoundCloud tracks. Returns tracks matching a query') comes first, and the rest is a compact, useful list of returned data.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple query+limit search tool, the description provides adequate context for an agent to call the tool successfully. Though there is no output schema, it lists the major fields returned. It doesn't need to detail every field or describe internal API mechanics in this situation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of the parameters, so the baseline is 3. The description adds no extra meaning beyond the schema for 'limit' or 'query'; it describes return fields rather than parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the specific action and resource: 'Search SoundCloud tracks' and enumerates what is returned. It is distinct enough in that it is a keyword-search tool, but it doesn't explicitly draw the boundary against sibling tools like soundcloud_track and soundcloud_user_tracks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternative SoundCloud tools. The description doesn't state that detail retrieval should use soundcloud_track or that user-scoped retrieval should use soundcloud_user_tracks, so the agent must infer the correct usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that data comes from 'Spotify Web Player private Pathfinder responses,' indicating a non-official data source, which is useful. However, it lacks information on authentication, rate limits, side effects, or response structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, both front-loaded with the core purpose and a key detail about the data source. No extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description should explain what the returned data contains. It merely says 'returns related artists' without detailing the structure. Additionally, it does not clarify that at least one of uri or id is required.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters have detailed descriptions in the input schema (100% coverage). The tool description does not add any additional semantic information about parameters, such as how to choose between uri and id or their precedence.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the action ('Retrieve') and the resource ('related artists'). It distinguishes from sibling tools like spotify_artist by specifying that it returns related artists, not the artist's own details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., spotify_artist_albums, spotify_artist_playlists). The description does not mention prerequisites or conditions for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the anonymous credential fetching, which is good. But it lacks details on rate limits, pagination behavior, or error handling, which would help the agent anticipate behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only two sentences, front-loaded with the core action, and every word adds value. No fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (9 parameters, no output schema), the description is insufficient. It does not explain return structure, pagination (offset/limit), or the purpose of boolean parameters like include_audiobooks, which are essential for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the input schema already documents all parameters. The description adds no additional meaning beyond 'search term' for the required parameter 'q', so it meets the baseline but does not enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search Spotify playlists' which is specific and matches the tool name. It also mentions normalized results and anonymous credential handling, distinguishing it from sibling tools like spotify_playlist (single playlist) and other search tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions that no caller-supplied tokens are needed, which is useful context. However, it does not explicitly state when to use this tool vs alternatives like spotify_search or spotify_playlist, leaving room for ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It only states 'Retrieve' (read) and 'Returns normalized...', but does not disclose pagination behavior, rate limits, or any side effects. Minimal behavioral context beyond basic purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences with no fluff. The first sentence front-loads the key action and resource, making it immediately clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no required parameters, no output schema, no nested objects) and 100% schema coverage, the description is fairly complete. It explains what the tool returns and the source, though it could briefly mention pagination behavior of the offset/limit parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all parameters are documented in the schema. The description adds no additional meaning about parameters, such as their impact on output or usage hints. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Retrieve Spotify Podcasts categories' with a specific verb and resource. It also mentions 'normalized Spotify podcast category sections and items from Spotify's all-categories browsePage Pathfinder response', which distinguishes it from sibling podcast tools like spotify_podcasts_charts or spotify_podcasts_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as other Spotify podcast tools or other categories tools. It does not mention exclusions or context-specific usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only states it 'Returns normalized related Spotify shows and episodes', which hints at transformation but does not disclose side effects, authorization needs, rate limits, or error behavior. The lack of detail on what 'normalized' means or the response structure leaves gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (one sentence plus a brief return statement) with no wasted words. It front-loads the main action and immediately clarifies the output, making it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is fairly complete given the tool's simplicity. It mentions the key output ('normalized related Spotify shows and episodes') without an output schema. However, it could be more specific about the data structure or fields returned, especially to differentiate from similar recommendation tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage for the single parameter 'uri' (described as 'Spotify show URI' in schema). The description does not add any additional meaning beyond what the schema already provides. With high schema coverage, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves 'Spotify podcast recommendations' and specifies the resource ('Spotify podcast recommendations') with a specific verb ('Retrieve'). It distinguishes itself from sibling tools like spotify_podcasts_show and spotify_podcasts_show_episodes by explicitly mentioning 'recommendations' and 'normalized related Spotify shows and episodes'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, when to use, or when not to use. Given the many sibling tools (e.g., spotify_podcasts_show, spotify_podcasts_search), explicit usage context is missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Discloses the source service (Spotify's Web Player user-profile service) and default behavior. However, it does not mention authentication needs, rate limits, or side effects. Since it's a retrieval, it is likely read-only but not explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences. First sentence states purpose, second sentence gives input guidance and default. No fluff or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Explains what is returned (metadata and preview playlists) and the source, but lacks detail on output structure or edge cases (e.g., invalid username). Without output schema, more description of the return format would be helpful. Adequate but incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. Description adds value by grouping username, uri, url as alternative identifiers and stating the default behavior (official profile). The integer limits are well-described in the schema, so no additional detail needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the action (Retrieve) and resource (Spotify public profile) and mentions it returns 'normalized public profile metadata and preview playlists'. However, it does not explicitly distinguish from sibling tools like spotify_profile_followers or spotify_profile_playlists, which are more specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides input guidance (provide username, uri, or url; defaults to official profile) but does not explain when to use this tool over alternatives like spotify_profile_followers or spotify_profile_playlists. No explicit when-to-use or when-not-to-use advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that it returns 'normalized public playlists' but does not mention any behavioral traits such as rate limits, authentication requirements, data freshness, pagination behavior (despite offset/limit parameters), or what 'normalized' means. It is missing important context for an agent to safely and effectively use the tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief, with two sentences. The first sentence states the core purpose, and the second adds detail on input parameters and default behavior. There is no unnecessary information, but it could be slightly more structured (e.g., bulleting parameters).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and 5 optional parameters, the description provides the essential purpose and input guidance. However, it lacks details on expected output format, error conditions, and behavioral notes (e.g., pagination). It is minimally viable but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, providing a baseline of 3. The description adds value by explaining the relationship between username, uri, and url, and the default behavior when none are provided. However, it does not elaborate on offset and limit beyond what is in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Retrieve' and the resource 'Spotify public profile playlists'. It specifies that it returns normalized public playlists from Spotify's Web Player user-profile service, and distinguishes from similar tools like spotify_profile or spotify_playlists_search by focusing on a user's public playlists.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions that users can provide username, uri, or url, and defaults to Spotify's official profile, which implies basic usage. However, it does not explicitly guide when to use this tool versus sibling tools like spotify_profile (user info) or spotify_playlists_search (search all playlists), nor does it state exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It mentions that the tool fetches anonymous credentials and does not require caller-supplied tokens, which is useful. However, it lacks details on rate limits, pagination behavior, or what 'normalized' means.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, no unnecessary words. Efficient and directly conveys the tool's purpose and key behavioral trait about authentication.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, so the description should explain return structure. It only says 'returns normalized results' but doesn't specify format or fields. With 11 parameters, the description does not explain how they affect results. Incomplete for a complex search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% coverage with descriptions for all 11 parameters. The description adds no extra parameter-level information beyond what the schema already provides. Baseline score of 3 appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it searches Spotify catalog across multiple content types, distinguishing it from more specific searches like spotify_albums_search or spotify_tracks_search. It explicitly lists the content types covered.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this general search vs specialized searches like spotify_albums_search or spotify_artist_albums. No when-not-to-use or alternatives mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description reveals that the tool fetches anonymous credentials at request time, indicating no auth needed. However, it does not disclose rate limits, error handling, or response structure beyond 'normalized results'. With no annotations, more behavioral context would be beneficial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences conveying key information: purpose and a notable behavior (no auth). No wasted words, but could be more structured. Adequately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 9 parameters and no output schema, the description covers the core purpose and one behavioral trait. However, it lacks explanations of how parameters interact (e.g., offset vs top_results) and does not describe return format. Moderately incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All 9 parameters have schema descriptions, so the description adds no extra parameter meaning. The description's mention of 'search term' merely repeats the schema. Baseline score of 3 is appropriate as schema coverage is 100%.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Search Spotify tracks' with specific verb and resource. The description mentions normalized results and anonymous credentials, which adds clarity. However, it does not explicitly differentiate from sibling tools like spotify_search or spotify_albums_search, leaving room for confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Mentions that caller-supplied tokens are not required, which is helpful context. But it lacks guidance on when to use this tool versus alternatives (e.g., spotify_search for broader search). No exclusion criteria or prerequisites are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must disclose behavior. It notes credential-free, cursor pagination, and aggregate behavior. Lacks details on error handling, rate limits, or invalid appid scenarios, which would enhance transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences: first sentence states purpose, second explains pagination and aggregate, third notes credential-free. Front-loaded and no fluff. Could be slightly more concise but well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 8 parameters and no output schema, the description covers key aspects: pagination, aggregate, and credential-free access. It does not explain all parameters beyond schema, but that is acceptable given high schema coverage. Minimal but adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining the cursor parameter's role in pagination and when aggregate data populates, which is beyond the schema's basic descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists reviews for a Steam app with pagination and aggregate data. The verb 'List' and resource 'reviews for a Steam app' are specific. However, it does not differentiate from similar sibling tools like datasets_steam_reviews_search, so not a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit pagination instructions: aggregate only on first page, pass cursor back for subsequent pages. Also notes credential-free usage. But lacks when-to-use vs alternatives or when-not-to-use hints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that the tool is credential-free and returns specific fields. However, it does not mention error behavior, rate limits, or whether it is read-only. The term 'Faceted' is mentioned but not explained. For a tool without annotations, this is adequate but could be more detailed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the main purpose. It is concise and without redundancy. Each sentence provides useful information (search, pagination, authentication). It could be slightly more structured but is effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given moderate complexity (6 parameters, no output schema, no annotations), the description partially explains return values but omits details like default pagination size, allowed sort_by values, and how faceting works. It is adequate for simple use but incomplete for advanced usage scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds limited value beyond the schema: it mentions 'start/count paging and sort_by' (already in schema) and lists return fields (not in schema). It does not add syntax, defaults, or constraints for individual parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a 'Faceted, paginated Steam store search' and lists the returned fields (appid, title, release date, etc.). It identifies the resource (Steam store) and the action (search with pagination and sorting). However, it does not differentiate from sibling tools like 'steam_search' or 'steam_app', which may also search or retrieve Steam data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions pagination (start/count), sorting (sort_by), and that it is 'credential-free'. It implies usage for public Steam store searches but does not provide explicit guidance on when to use versus alternatives, nor does it specify when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It uses the verb 'Get' implying a read-only operation and lists the content categories returned (venue, attractions, timing, availability flags, classification). However, it does not describe error behavior, authentication needs, or what 'normalized' entails, leaving some behavioral ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is remarkably concise, consisting of two short sentences. It front-loads the action ('Get a Ticketmaster event') and immediately adds valuable detail about the return contents. There is no redundant information or wordy filler, making it highly efficient for an agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (a single parameter and no output schema), the description is reasonably complete. It covers the tool's purpose and the expected return content. However, it could be improved by adding guidance on how to fetch an event ID and what happens for nonexistent events, but these are not critical gaps for a straightforward fetch operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema fully documents the only parameter 'id' with the description 'Ticketmaster event id', providing 100% coverage. The tool description adds no extra meaning or context about this parameter, such as how to obtain a valid ID or any format constraints. Thus, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: retrieving a single Ticketmaster event with normalized details. It specifies the resource (Ticketmaster event) and the scope (one event), which distinguishes it from sibling tools like ticketmaster_search_events. However, it does not explicitly name alternative tools or mention the 'by ID' mechanism, which would strengthen differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is provided on when to use this tool versus alternatives such as ticketmaster_search_events or ticketmaster_suggest. The description implies it is for fetching details of a known event, but it does not state prerequisites (e.g., having an event ID) or exclusions (e.g., do not use for searching). This leaves the agent without clear usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It mentions cursor-based pagination and that it returns top-level comments, but does not cover potential limitations, sorting, or whether authentication is needed. This is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences that front-load the core purpose. Every sentence adds value, with no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity and absence of an output schema, the description should hint at the return data structure (e.g., comment fields). It only mentions 'top-level comments' and pagination, leaving users uninformed about what is actually returned. This is a significant gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds minimal value beyond the schema, merely reinforcing that the id comes from a video URL and that cursor is for pagination. No new meaning is added.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves TikTok video comments, specifically top-level ones, and mentions cursor-based pagination. It effectively distinguishes from sibling tools like tiktok_post, tiktok_search, etc., by specifying its unique function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It lacks information about prerequisites, exclusions, or scenarios where other tools might be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that data is credential-free and from public TMDB, which is valuable. However, it does not describe potential errors, rate limits, or data freshness, and the behavior is straightforward (read).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the action, and every sentence adds value (purpose, return fields, credential note). No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 parameter, no output schema, no annotations), the description adequately covers what it does, what it returns, and a key behavioral note (credential-free). It could mention error handling or ID format, but overall it is complete enough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes the 'id' parameter as 'TMDB movie id' with 100% coverage. The description adds no additional semantics beyond the schema, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get a TMDB movie' and lists specific return fields, effectively defining the tool's purpose. However, it does not explicitly differentiate from sibling tools like tmdb_search or tmdb_movie_list, though the name and context imply it's for a single movie detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as tmdb_search or tmdb_movie_list. The note about credential-free public data is helpful but does not address usage context with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description states it returns normalized public reviews without credentials, indicating read-only operation. However, no details on rate limits, pagination behavior, or response format. With no annotations provided, the description carries the burden but misses some behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences effectively convey purpose and key input requirement. No redundant information; every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 10 parameters and no output schema, the description is insufficient. It does not explain pagination, sorting, filtering, or return format, which are critical for correct usage. The tool is more complex than the description suggests.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% description coverage, so baseline is 3. Description adds value by noting 'Pass either id or url', but does not elaborate on other parameters. Minimal extra meaning beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Get TripAdvisor reviews' with specific verb and resource. It distinguishes from sibling tools (e.g., tripadvisor_place, tripadvisor_hotels) by focusing on reviews. The mention of 'normalized' and 'credential-free GraphQL' adds specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like tripadvisor_place or tripadvisor_hotels. The description only says 'Pass either id or url' but does not explain when to choose which, nor when not to use the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It mentions 'returns normalized TripAdvisor place listings' but does not disclose safety (e.g., read-only nature), rate limits, authentication requirements, or pagination behavior. The term 'normalized' is undefined, leaving behavioral uncertainty.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: first states the action and resource, second details the output. No redundant language. Information is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 20 parameters, no output schema, and complex filters, the description is insufficient. It does not explain how to use filters, interpret results, or handle large result sets. The absence of output schema makes the return format unclear.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so all parameters have descriptions. The description does not add additional meaning or examples beyond what the schema already provides. Baseline score applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Search TripAdvisor places' and enumerates return types: hotels, restaurants, attractions, and supported attractions. Differentiates from siblings like tripadvisor_hotels, tripadvisor_place, and tripadvisor_autocomplete by specifying it returns 'normalized place listings' across multiple categories.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description implies use when searching for TripAdvisor places but does not explicitly state when to use this tool versus specific tools like tripadvisor_hotels or tripadvisor_place. No exclusion criteria or alternative recommendations are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description is the sole source of behavioral info. It indicates the tool returns a directory, but does not disclose if authentication, rate limits, or pagination apply. For a simple parameterless tool, the disclosure is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is just two sentences, front-loading the purpose ('Get TrustMRR categories') and then detailing what is returned. Every word is informative, with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has zero parameters and no output schema, the description explains the return fields (slug, label, description, keywords). It does not specify the output format (e.g., array), but for a simple list retrieval, this is largely sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no parameters, so schema coverage is 100%. The description adds no parameter details, which is acceptable since none exist. Baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Get TrustMRR categories' with a clear verb and resource, and specifies the return structure (slug, label, description, keywords). Although it does not explicitly contrast with sibling tool trustmrr_category (singular), the plural name implies it returns all categories, providing adequate differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lacks any guidance on when to use this tool versus alternatives like trustmrr_category or trustmrr_startups. No conditions, exclusions, or use cases are mentioned, leaving the agent to infer applicability.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description mentions parsing from public page, implying web scraping, but doesn't disclose rate limits, auth needs, or potential for site changes. Discloses date_from/date_to are 'currently rejected by upstream', a useful caveat.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, clear first sentence. Second sentence repeats 'Returns paginated Trustpilot business reviews' unnecessarily, causing slight redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 9 parameters, no output schema, and no annotations, the description is minimal. Does not explain pagination details, return format, or any error handling. Schema descriptions are good, but overall completeness is adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds no additional meaning beyond the schema parameter descriptions (e.g., 'slug', 'stars', 'verified').
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'Get' and resource 'Trustpilot business reviews', with source 'parsed from the public review page'. Distinct from sibling tools like trustpilot_business and trustpilot_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., trustpilot_business for business info, trustpilot_business_search for finding businesses). Lacks 'when-not' or prerequisite information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey the tool's behavioral traits. It mentions the return structure but does not disclose whether the operation is read-only, requires authentication, has rate limits, or any other side effects. For a tool with no annotations, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences, with the first stating the core purpose and the second listing the return data. Every word adds value, and it is front-loaded with the action. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately explains what the tool returns: category metadata, company cards, and side rails. It also hints at pagination via the page parameter, though it does not explicitly state that company cards may span multiple pages. For a simple tool with two parameters, this is largely complete, but a brief mention of pagination or authentication would improve it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters have descriptions in the schema (slug and page). The description adds no additional meaning beyond what the schema already provides. Since schema coverage is 100%, the baseline of 3 is appropriate, and no bonus points are earned.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get Trustpilot category detail' with a specific verb and resource, and lists the returned components (category metadata, company cards, side rails). It distinguishes itself from siblings like trustpilot_categories (which lists categories) and trustpilot_category_search (which searches categories) by focusing on a single category's detailed page.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus its siblings. With multiple trustpilot category-related tools available, the description fails to specify that this is for retrieving detailed information about a specific category, while trustpilot_categories or trustpilot_category_search might be more appropriate for browsing or searching.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden, and it does add some behavioral context: the phrase 'Sourced from Yahoo Entertainment's own server-rendered homepage' indicates a scraping-based read operation rather than an API. However, it does not disclose behavior such as feed freshness, number of stories returned, pagination, or whether the feed is cached, which an agent might need to interpret results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences, each adding distinct value: the resource, the return fields, and the data source. Minor redundancy ('Yahoo Entertainment' appears three times) prevents a perfect score, but there is no wasted content and the purpose is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool it is a zero-parameter, no-output-schema feed retrieval, the description covers the essentials: what is returned (four fields) and where it comes from (server-rendered homepage). An agent can invoke it correctly with no further information; only minor details like result count or update cadence are absent, and those are non-critical for a no-input tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters and an empty input schema, so the baseline is 4 and the description has nothing to explain. The description correctly implies this is a no-argument feed fetch, and no parameter semantics are needed or missing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Returns') and a precise resource ('Yahoo Entertainment's homepage editorial story feed'), and enumerates the returned fields (title, destination URL, category, thumbnail). It clearly identifies itself as the homepage feed, which is distinct from siblings like yahoo_entertainment_article and yahoo_entertainment_category, though it never names them explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to use this tool versus the many alternatives. There is no mention that yahoo_entertainment_article should be used for a single story or yahoo_entertainment_category for category-specific stories, so an agent must infer the right selection from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states what is returned but does not disclose error behavior, rate limits, data freshness, or any constraints beyond the parameter. This is minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with 10 words, perfectly front-loaded with the tool's purpose. No unnecessary information is included.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description is incomplete. It doesn't explain return format, time range, or limitations. For a tool with one parameter, more detail about the output structure would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter 'symbol' described as 'Yahoo Finance symbol such as AAPL'. The description adds context that the tool returns dividends, splits, and capital gains for that symbol, but does not enhance parameter-specific meaning beyond the schema, earning a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Yahoo Finance corporate actions. Returns dividends, splits, and capital gains for a symbol.' It uses a specific verb ('Returns'), specifies the resource ('corporate actions'), and lists exact data types, distinguishing from sibling tools like yahoo_finance_ticker_dividends and yahoo_finance_ticker_splits.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (when needing combined corporate actions) but does not explicitly mention when to prefer individual tools like yahoo_finance_ticker_dividends or yahoo_finance_ticker_splits. No alternatives or exclusions are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It only mentions 'Returns normalized OHLCV points' without explaining what 'normalized' means, how data is truncated, or if there are rate limits. The behavior around parameter precedence (period vs start/end) is implied but not clarified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no extraneous words. The first sentence provides the core purpose, the second adds usage constraint. Every word serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 11 parameters, no output schema, and no annotations, the description is insufficient. It does not explain default interval, the meaning of 'normalized', or how to specify multiple symbols. The description is too brief for the complexity of the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all 11 parameters. The description adds minimal value beyond the schema, only noting 'Use either period or start/end'. This is a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Yahoo Finance historical prices' and 'Returns normalized OHLCV points for a symbol', which is a specific verb-resource pair. It distinguishes from sibling tools like yahoo_finance_ticker_quote (current price) and yahoo_finance_download (raw data) by focusing on normalized historical data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes 'Use either period or start/end', which provides some guidance on parameter selection but does not explicitly state when to use this tool over alternatives like yahoo_finance_ticker_quote or yahoo_finance_ticker_dividends. No exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden. It implies a read-only operation ('retrieve', 'returns'), but does not disclose authentication needs, rate limits, or output structure. Minimal but not misleading.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no extraneous information. Every word adds value. Front-loaded with the action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite simplicity, the description omits what 'full profile details' includes. Without an output schema, the agent lacks critical context about return data, which could affect downstream usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a thorough parameter description listing multiple ID formats. The tool description adds no additional meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it retrieves a YouTube channel profile, which is distinct from sibling tools that fetch videos, playlists, or comments. The verb 'Retrieve' and resource 'channel profile' are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool compared to siblings like youtube_channel_videos or youtube_channel_playlists. The agent must infer context from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While it states the tool is read-only and returns data, it doesn't mention idempotency, rate limits, error handling, or any potential side effects. The description is minimal, offering only basic functionality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of two clear sentences. Every word serves a purpose, making it easy for an AI agent to quickly understand the tool's function without extraneous detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (single parameter, no output schema, no nested objects), the description is largely complete. It covers the core function and expected output. Minor omission: no mention of error cases (e.g., invalid video ID), but for a straightforward list operation this is acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for the single parameter 'id', which is well-described as 'YouTube video ID (11-character code)'. The description adds no new semantic meaning beyond implying the video ID is needed. Hence baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'List transcript languages' and the resource 'for a YouTube video'. It provides a concise definition that distinguishes this tool from siblings like youtube_transcript (which likely retrieves the transcript itself) and youtube_captions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. For example, it doesn't suggest using it before calling youtube_transcript to check available languages. The description is purely declarative without usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Mentions using GraphQL payload but fails to disclose behavioral traits like read-only nature, rate limits, authentication needs, or data freshness. Only describes return structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, first is direct verb+resource, second adds valuable detail. No wasted words, but could be slightly more structured (e.g., bullet points for optional sections).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers return structure with optional sections, but lacks behavioral context (e.g., whether it requires authentication, is read-only, rate limits). Without output schema, description provides adequate but not complete guidance for a straightforward lookup tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with zpid described as 'Zillow property id'. Description adds no additional meaning beyond the schema for the parameter, so baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool gets a Zillow property by zpid and returns normalized public property details with optional typed sections. Distinguishes from siblings like zillow_search and zillow_autocomplete which serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implicitly indicates usage for retrieving a specific property by ID, but no explicit guidance on when to use this versus sibling tools like zillow_search or zillow_autocomplete. No when-not or alternative context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description bears full burden. It states the tool returns 'public calendar month hints parsed from Airbnb room bootstrap data', indicating a read-only operation. However, it does not disclose potential side effects, authentication needs, or rate limits, which is acceptable for a simple retrieval tool but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, with the first sentence stating the primary purpose and the second adding detail. It is front-loaded, concise, and contains no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description is adequate but lacks details on the return format or what 'calendar month hints' entail. More context on the output structure would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers the single parameter 'id' with description 'Room id', achieving 100% coverage. The description adds no additional meaning beyond this, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets the Airbnb room calendar and returns 'public calendar month hints'. The verb 'Get' and resource 'Airbnb room calendar' are specific, and it distinguishes itself from sibling tools like airbnb_room (room details) and airbnb_room_reviews (reviews).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing calendar data, but does not explicitly state when to use this tool versus alternatives like airbnb_room. No exclusion or prerequisite information is provided, relying on the tool's name and context for differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Lacks annotations, so description must carry burden. Mentions 'normalized' and 'public web search results', but doesn't explain what normalization means, pagination, or authentication needs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise, two sentences, no waste. Front-loaded with purpose. Could be expanded but efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite 11 parameters and no output schema, description is brief. Doesn't explain bounded map search or results structure. Incomplete for a complex tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so description adds no additional parameter meaning beyond the schema descriptions. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'Search' and resource 'Airbnb stays', and distinguishes from siblings like 'airbnb_room' by indicating it returns normalized search results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies use for searching stays, but no explicit guidance on when to use vs. alternatives like 'airbnb_room' or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only states what is returned. It does not disclose read-only nature, authentication needs, rate limits, or potential side effects. For an unannotated tool, more transparency is expected.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the action and clearly states the output. Every word is necessary; no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains the output (total count and histogram) but does not clarify parameter dependencies or default behavior. For a tool with 4 optional parameters, more context about how they interact (e.g., needing at least id or app_id) would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Parameter descriptions in the schema already explain each field (id, lang, app_id, country). The description does not add meaning beyond the schema, but the schema coverage is 100%, so baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves the App Store ratings histogram, specifying the return includes total ratings count and the 1-5 star histogram. This distinguishes it from sibling tools like appstore_app (app details) and appstore_reviews (individual reviews).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for fetching rating distribution, but lacks explicit guidance on when to use this tool versus alternatives (e.g., appstore_reviews for text reviews). No exclusions or prerequisites mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; the description only states it retrieves suggestions. It does not disclose behavioral traits such as rate limits, authentication requirements, or any side effects. For a read-only operation, minimal disclosure is expected but more context (e.g., return format limitations) would improve transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, each serving a purpose: first states the action, second describes the output. No extraneous information, front-loaded with the verb. Efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description is adequate but minimal. It does not specify the structure of suggestions (e.g., array of strings), potential errors, or limits (e.g., max 10 suggestions). For a simple suggest tool, this may suffice, but more completeness would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for 'term' and 'country'. The description adds minimal nuance ('partial keyword' aligns with 'term'), but does not further clarify parameter constraints like valid country codes or maximum term length. Baseline score of 3 is appropriate given full schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Retrieve App Store search suggestions' and specifies the output 'Returns suggested search terms'. It uses a specific verb ('Retrieve') and identifies the resource ('App Store search suggestions'), distinguishing it from sibling tools like appstore_search or amazon_suggest.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for partial keyword autocomplete, but lacks explicit guidance on when to use this tool versus alternatives (e.g., appstore_search for full results, or google_suggest for web). No 'when not to use' or alternative recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It adds the behavioral detail that reviews are 'normalized', which is useful, but it does not disclose pagination behavior, response format, or whether it requires a prior product_id. It is not misleading, but it leaves significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of two short sentences. The first sentence is a fragment but the second clarifies it. Every word earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple review-retrieval tool with fully described parameters, the description is mostly adequate. However, it lacks usage guidance and does not describe the shape or contents of the returned reviews, which is important since no output schema exists. It is a minimum viable description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema fully documents all three parameters. The description does not add any parameter-level meaning beyond what the schema already provides, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: returning normalized guest reviews for a Booking.com attraction. It uses a specific verb ('returns') and resource ('attraction reviews'), distinguishing it from sibling tools like booking_hotel_detail or booking_reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention that product_id should come from a prior attraction search or how this tool differs from hotel review tools. No exclusions or alternative references are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does not disclose whether the operation is read-only, requires authentication, has rate limits, or any side effects. The description only states what it returns, lacking behavioral context beyond the basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is composed of two concise sentences with no wasted words. It front-loads the core purpose ('Box Office Mojo release group detail') and immediately follows with the action and parameter guidance. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema and annotations, the description provides a basic understanding of what is returned ('normalized market release rows grouped by region') but lacks details on the structure, any limitations, or usage caveats. It is adequate but not fully comprehensive for a tool with moderate complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter descriptions, but the description adds value by explicitly stating the mutual exclusivity constraint: 'Pass exactly one of id, path, or url.' This clarifies the intended usage beyond the schema which marks all parameters as optional with no constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'normalized market release rows grouped by region from a public Box Office Mojo release-group page.' The verb 'Returns' and resource 'release-group page' are specific, and the tool name 'boxofficemojo_release_group' distinguishes it from siblings like boxofficemojo_release and boxofficemojo_title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus other Box Office Mojo tools. The only usage instruction is 'Pass exactly one of id, path, or url,' which is parameter-level advice, not contextual usage guidance. Sibling tools include many boxofficemojo_* options, yet no alternative selection criteria are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits but only states it returns normalized comparison rows. No mention of read-only nature, authentication, rate limits, or what 'normalized' implies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. Front-loaded with tool name and action. Efficient for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate given no parameters or output schema, but given many sibling tools and no annotations, more context about the output format or typical use cases would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has 0 parameters, so baseline is 4 per rules. Schema description coverage is 100% trivially, no additional param info needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool returns normalized comparison rows from Box Office Mojo's public showdowns page. The verb 'Returns' specifies it's a retrieval operation, and the plural 'showdowns' distinguishes it from the singular 'showdown' tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides no guidance on when to use this tool versus similar siblings like boxofficemojo_showdown, boxofficemojo_brands, or others. No context on prerequisites or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'normalized release rows' but does not disclose behavioral traits such as rate limits, pagination, data freshness, or whether the data is cached. The output format is vaguely described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is concise and front-loaded with the main purpose. It wastes no words, but could be slightly more structured (e.g., separating purpose and output format).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has one parameter and no output schema. The description provides enough context for a simple tool: it specifies the source (Box Office Mojo domestic yearly chart), the output (normalized release rows), and the scope (domestic yearly). However, it does not explain what 'normalized release rows' are, slightly reducing completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% coverage for the single year parameter with a clear description. The description does not add additional meaning beyond the schema, but the schema itself is sufficient. Baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it is for domestic yearly box office data, returning normalized release rows from Box Office Mojo's calendar-grosses chart. The resource and verb (returns domestic yearly box office) are specific, and it distinguishes from siblings like boxofficemojo_year_worldwide (worldwide) and boxofficemojo_weekend_domestic (weekly).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for retrieving domestic yearly box office data, but does not explicitly state when to use this tool versus alternatives (e.g., boxofficemojo_date_domestic or boxofficemojo_weekend_domestic). No when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the source (public HTML) and a potential error (503 on challenge pages), but lacks details on rate limits, authentication, or result structure beyond normalization.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, no wasted words, with the first sentence immediately stating purpose. Very concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description covers the essential behavior and a key error condition, but omits details on pagination, response format, and how to handle other errors. Adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with each parameter described. The description adds the locale defaults, which are already in the schema, so it provides no additional meaning beyond what the schema offers.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches Brave image results, uses a specific verb-resource pair, and distinguishes itself from sibling tools like brave_search and brave_videos.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool over alternatives like bing_images or google_images. It only describes its own behavior without comparative context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description indicates it's a read operation by stating it 'returns' disclosures. With no annotations, this is adequate. It also mentions defaults for country and lang. However, it does not disclose any potential errors, authentication requirements, or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: two sentences that front-load the purpose and then detail the return content and defaults with no extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with three well-documented parameters and no output schema, the description adequately explains what is returned and the default parameter values. It could mention the return format (e.g., JSON) but is otherwise complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers all three parameters with descriptions, but the description adds value by specifying defaults for 'country' and 'lang' ('us' and 'en' respectively), which the schema does not include.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves privacy disclosures for a Chrome Web Store item and lists the specific data returned (data-use statement, collection flag, standard declarations, privacy-policy link). However, it does not explicitly differentiate from sibling tools like chromewebstore_item or chromewebstore_permissions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as chromewebstore_item or chromewebstore_permissions. There are no prerequisites, context, or exclusions mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It explains basic functionality and return fields but does not disclose authentication needs, rate limits, error handling, or pagination behavior beyond the num parameter.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: first states purpose, second lists return fields and defaults. It is front-loaded, concise, and contains no superfluous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description covers return fields and defaults. However, it lacks details on pagination (how to get more reviews), error cases, or prerequisites. It is adequate but not exhaustive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter descriptions. The description adds defaults for num, country, and lang, and reinforces the id format. However, it does not add significant meaning beyond the schema for other parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the verb 'Retrieve' and the resource 'Chrome Web Store item reviews'. It lists the exact data returned (author, star rating, text, dates, version), and the tool name distinguishes it from sibling review tools for other platforms.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for Chrome Web Store reviews but does not explicitly state when to use this tool versus alternatives. It provides defaults for num, country, lang but lacks guidance on when not to use it or alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behaviors. It mentions 'normalized rows' and vs_currency support, but does not state if the operation is read-only, any rate limits, or pagination behavior beyond the limit parameter. The description is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no wasted words. It front-loads the core purpose and adds a second sentence for parameter context. Every sentence serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list endpoint with no output schema, the description provides the essential resource and parameter support. However, it lacks details on return format or filtering capabilities, leaving some gaps. Adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters have schema descriptions (100% coverage). The description adds value by referencing the 'documented vs_currency enum', implying a known set of values beyond the schema. This aids understanding beyond schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'normalized CoinGecko category rows' from the public categories page. It distinguishes itself from siblings by specifying the resource (categories vs coins, chains, etc.). The verb 'returns' is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus other CoinGecko tools (e.g., coingecko_category_coins, coingecko_markets). The description mentions vs_currency support but does not explain context or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It states the tool returns 'derived price-chart metrics' and is 'not investment advice or real-time trading data', but it does not specify whether the operation is read-only, what metrics are derived, or any limitations on the data freshness. This leaves some ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph of three sentences, which is concise and to the point. No superfluous information is present, though it could be better structured with separate lines for usage and disclaimers.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, yet the description does not describe the return format or the specific 'derived metrics' (e.g., moving averages, volatility). Given the complexity of chart analysis, this is a significant gap. Additionally, it does not explain how the 'range' parameter affects the output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for all 4 parameters, so the schema already conveys their meanings. The description adds minor value by mentioning the 'vs_currency enum' and that data comes from 'public chart JSON', but it does not explain the 'range' parameter or 'include_annotations' beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs 'coin chart analysis' and returns 'derived price-chart metrics'. It specifies the data source (CoinGecko public chart JSON), distinguishing it from nearby tools like coingecko_coin (likely basic coin info) or coingecko_markets (market data).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions support for the 'vs_currency enum' and includes a disclaimer about not being real-time trading data, but it does not explicitly guide when to use this tool versus the many sibling tools in the Coingecko family, such as coingecko_coin, coingecko_markets, or coingecko_chains.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It does disclose that the data is 'Public data sourced from Costco's own product backend' and lists the return fields, which gives some transparency about the nature of the operation. However, it does not mention error behavior, potential latency, or whether the stock status is real-time, leaving some gaps for a simple read tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short, consisting of two sentences. It is front-loaded with the main action and immediately lists the return fields. There is minor redundancy in repeating 'Costco product's detail', but overall it is efficient and scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema), the description adequately informs the agent of the return contents by listing the fields. The data source is also mentioned. It does not explain how to obtain the product id, but the schema's parameter description covers that, so the description is complete enough for its complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% coverage for the id parameter with a description mentioning it comes from search results or product URLs. The tool description adds no additional meaning about the parameter, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Get a Costco product's detail.' It enumerates the specific fields returned (title, description, manufacturer, image, price, stock status, and rating), making it obvious this is for basic product information. This distinguishes it from sibling tools like costco_product_reviews and costco_product_availability, which cover other aspects.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus its siblings such as costco_search or costco_product_availability. It neither names alternatives nor describes scenarios where this tool is preferred. The only context is the data source statement, which is not usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It states the primary behavior (returns terms aggregation counts) and enumerates valid facets, which is helpful. However, it doesn't disclose how filters interact with the facet computation, response format, or any limitations like default sizes or unsupported combinations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with the main action. It uses a clean code block for the facet enum, making allowed values easy to scan. Every sentence earns its place without redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The core behavior and allowed facets are explained, and the schema covers parameters. However, there is no output schema, and the description doesn't outline the response shape beyond vague 'counts', nor does it clarify how optional filters (q, genre, country) affect the aggregation. This leaves gaps for an agent needing to predict the tool's output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description lists the facet enum values, but the schema's facet parameter already includes the same enum list, adding no new meaning. The other parameters' meanings are fully captured in the schema, so the description doesn't elevate understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool facets the Apple Podcasts shows dataset and returns terms aggregation counts. It lists the specific facet enum values, distinguishing it from sibling search and item tools like apple_podcasts_show or datasets_apple_podcasts_shows_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains what the tool does but provides no guidance on when to use it versus alternatives (e.g., datasets_apple_podcasts_shows_search). It doesn't mention use cases, prerequisites, or exclusions, leaving the agent to infer from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully convey behavior. It mentions returning 'chart-ready' aggregates and a days enum, but does not explicitly state read-only nature, rate limits, pagination, or data freshness, leaving important behavioral traits undisclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (two sentences) with front-loaded purpose and essential details (aggregate list, days enum). Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the description covers the tool's purpose and parameters, it lacks detail on the return format or structure. With no output schema, the agent may need more info about what 'chart-ready' means and how results are organized, though the tool is relatively simple.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter descriptions, but the description adds meaningful context by naming the aggregate categories (coverage, adoption, rating, etc.) and noting 'chart-ready' output, which helps interpret the parameters beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get Chrome Web Store dataset metrics' with a specific verb and resource, and lists the types of aggregates (coverage, adoption, rating, permission, privacy, recent-change) which distinguishes it from sibling tools like search, item, changes, facets, history, and trending.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide explicit guidance on when to use this tool over alternatives (e.g., for aggregated metrics vs. searching or retrieving individual items). It implies use for metrics but lacks direct comparison or context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It mentions that the tool 'returns terms aggregation counts', but does not disclose whether the operation is read-only, destructive, or any required permissions. There is no mention of pagination, rate limits, or response structure, which is insufficient for a tool with 22 parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only two sentences plus enumerations, front-loading the core purpose. Every sentence is informative—first sentence states the action and resource, second clarifies the return type. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 22 parameters and no output schema, the description does not explain the return format beyond 'terms aggregation counts'. It lists facet and filter enums, which is helpful, but does not describe how filters affect aggregation or what the output structure looks like. This is minimally adequate for a facet tool but lacks depth.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds enum values for 'facet', 'region_type', and 'property_type' which partially overlap with schema descriptions. It does not add significant new meaning beyond listing available options.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Facet' and resource 'US housing markets dataset', specifying it returns 'terms aggregation counts'. It enumerates the facet fields and provides enum values for region_type and property_type, which distinguishes it from sibling tools like datasets_housing_markets_search and datasets_housing_markets_item.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly indicates the tool's purpose (aggregation counts), but does not explicitly state when to use it versus alternatives like search or item tools. There is no guidance on exclusions or prerequisites. However, the purpose is clear enough for an agent to infer appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description only states basic action without revealing behavioral traits like read-only nature, error handling, or data completeness. Minimal disclosure beyond the verb.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with verb and resource, no redundancy. Every word serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema, the description is adequate but lacks details on return structure, error cases (e.g., invalid slug), or any additional behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%. Description adds context about the dataset source (`numbeo-cities`), which goes beyond the schema's parameter description. However, no further semantic enrichment for the slug parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it retrieves a Numbeo city record by slug from a specific dataset (`numbeo-cities`). This distinguishes it from sibling tools like `datasets_numbeo_cities_search` which search across multiple cities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage when you have a city slug, but does not explicitly state when to use this vs. `datasets_numbeo_cities_search` or `datasets_numbeo_cities_facets`. No when-not or alternative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the burden. It adds context about the data source (crawled public profiles, discovered from PitchBook's public sitemap) and that it is stored in a search index. However, it does not disclose pagination behavior, result format, or staleness implications beyond the crawl mention.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with three sentences that each add value: purpose, data source context, and sort options. It is front-loaded and contains no fluff or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 11 parameters and no output schema, the description provides enough context about what the tool searches and the data source. However, it does not describe return values or pagination limits beyond what the schema already contains. It is minimally sufficient but lacks rich behavioral context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description repeats the sort enum but does not add meaning beyond what the schema already provides. The schema descriptions are self-explanatory for all 11 parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches the PitchBook investors dataset, specifies the resource (investor profile catalog) and action (search). It distinguishes from siblings like datasets_pitchbook_investors_item and pitchbook_investor by emphasizing it searches a dataset, not a specific item.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. It does not mention when to prefer facets, item, or singular lookup tools. The usage is implied by the name and description but no exclusions or alternatives are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses that the operation returns terms aggregation counts (a read-only analytical operation), but does not mention pagination, multiple facet support, default behavior, or any error conditions. Some value is added beyond the trivial, but it is not deep.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences total, with front-loaded purpose. The enum lists make it longer but are necessary for informing valid values. There is minor redundancy with schema enums, but overall it is efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 26 parameters and no output schema, the description is too minimal. It does not explain how facets interact with filters, whether multiple facets can be requested, or what the response structure looks like beyond 'terms aggregation counts'. This is insufficient for such a complex tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with each parameter described. The description repeats the facet enum and price_tier enum, which are already in the schema, but adds no new semantic information about parameters. Baseline of 3 applies since schema handles param semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description states a specific verb ('Facet') and resource ('PlayStation games dataset'), and clarifies the outcome as 'Returns terms aggregation counts'. This clearly distinguishes it from sibling tools like datasets_playstation_games_search and datasets_playstation_games_item.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for aggregation/faceting rather than search or item retrieval, but does not explicitly name alternatives or state when not to use it. It provides the facet enum, giving some context for when this tool is appropriate, but lacks exclusionary guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It only states 'returns one crawled record' but does not disclose any behavior like rate limits, error responses, or field names. Minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with verb and resource, no fluff. Perfectly concise for a simple retrieval tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description could describe return fields or common usage scenarios. It is minimally adequate but not thorough. With sibling tools, more context would help.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents the parameter. The description adds the dataset enum value context but no extra meaning beyond that. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it retrieves a single PlayStation game by product_id from a specific dataset. Distinguishes from siblings like datasets_playstation_games_search (which retrieves multiple results) and datasets_playstation_games_facets (aggregations).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage: use when you have a product_id to fetch one record. No explicit when-not or alternative recommendations. For a single-item retrieval tool, this is adequate but lacks guidance on edge cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the return type (terms-aggregation counts) and the one-facet constraint, but doesn't provide details on response format, pagination, permissions, or edge cases. Some useful context is provided, but it's not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences with no fluff, but the dataset name is repeated across the first two sentences. Otherwise, it's well-structured and front-loaded with the action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the description covers the core purpose, the facet enum, and the scoping relationship to search. It could mention the return structure more explicitly, but it's largely complete for an aggregation tool with four parameters documented by the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so each parameter is already documented. The description adds no new parameter-level information beyond what the schema provides, so it earns the baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it facets the SEC institutional positions dataset and returns terms-aggregation counts. It mentions the facet enum and scoping to search filters, which distinguishes it from the related search tool, though it doesn't explicitly name the sibling.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'scoped to the same filters as search' implies when to use this tool for faceted counts, but it doesn't explicitly state when to choose this over the search tool or other alternatives. Usage context is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description is the only source. It discloses that the tool returns terms aggregation counts and lists valid facet, price_tier, and review_tier enums. However, it does not explain how the many filter parameters interact with the aggregation, return format, or any limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with purpose, but the phrase 'for the Steam games dataset' is repeated in the first two sentences, adding minor redundancy. The enum list is long but necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having a large set of filter parameters and no output schema, the description does not explain how filters relate to the facet aggregation or what the response structure looks like. An agent would be able to call the tool but lacks context on combining filters, multiple facets, or pagination, making it incomplete for a 27-parameter tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All 27 parameters are fully described in the schema (100% coverage), so baseline is 3. The description adds no extra semantic detail; its enum lists (facet, price_tier, review_tier) duplicate the property descriptions in the schema already.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states it facets the Steam games dataset and returns terms aggregation counts, which is a specific verb+resource+outcome. It distinguishes from sibling search tools by focusing on facet aggregations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use vs alternatives; the description just says 'Facet the Steam games dataset' without explaining when to choose this over datasets_steam_games_search. Usage is implied by the term 'facet' and the list of facet enums, but no exclusions or alternatives are named.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states it returns one record, but does not disclose read-only nature, error handling, rate limits, or what happens if the username is not found.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the core action, no wasted words. Efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema, the description covers the basic purpose and dataset id. However, it lacks details about the return format or any edge cases, making it adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and the schema already describes the username parameter. The description adds 'by username' which is redundant. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'an X user from the dataset', specifying it returns one record by username from dataset id 'x-users'. This distinguishes it from sibling tools like datasets_x_users_search and datasets_x_users_facets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving a single user by username, but does not explicitly state when to use this tool versus alternatives like datasets_x_users_search, nor does it provide exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavioral traits. It mentions 'returns normalized details' but omits specifics like authentication, rate limits, side effects, or response structure. The term 'normalized' is vague.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loaded with the action ('Get eBay item details'), and includes no unnecessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool, the description provides a basic outline but lacks details about what 'normalized details' include. Without an output schema, more specificity (e.g., fields, examples) would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter 'item_id' with a description 'eBay item ID'. The description does not add further meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Get eBay item details' with a clear verb and resource, and it distinguishes from sibling tools like ebay_search (which searches for items) and ebay_seller (seller info). It focuses on retrieving a single item's details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you have an item ID but does not explicitly state when to use this tool vs alternatives like ebay_search or ebay_seller. No guidance on prerequisites or context is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the burden. It adequately indicates the operation is a read/get action and mentions the output includes normalized detail and each host's feedback summary. Additional behavioral context (not found behavior, auth requirements, response format quirks) is missing, but for a simple single-resource lookup this is acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very compact: two sentences front-load the main action ('Get an eBay Live stream') and then specify what is returned. Every sentence adds meaningful detail without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter lookup tool, the coverage is adequate in the sense of core functionality and returned data. But with no output schema, no siblings mention, and no usage boundaries, an agent might not know when to choose this over the closely related ebay_live_streams or ebay_live_streams_batch. Still, for such a minimal interface, the shortfalls are mild.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully documents the only parameter ('id') with description 'eBay Live stream/event id'. The tool description doesn't add semantic detail beyond this, but with 100% schema coverage, the baseline of 3 applies and no extra compensation is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Get an eBay Live stream', and clarifies it returns normalized detail for a single stream/event including host feedback. This distinguishes it from list/batch siblings like ebay_live_streams and ebay_live_streams_batch, though it doesn't explicitly name them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'single eBay Live stream/event' implies this tool is for retrieving one specific stream rather than listing all streams or batch fetching. However, there is no explicit when-to-use guidance, no mention of alternatives like ebay_live_streams, and no exclusions, leaving some inference up to the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does state that the tool returns specific fields and implicitly indicates a read-only retrieval operation. However, it does not mention any potential side effects, authentication requirements, rate limits, or error behavior, which would be useful for an agent to fully understand the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded, with two sentences that clearly state the action and the output. However, it is slightly redundant as 'Etsy listing detail' appears in both sentences, which could be merged into a single more efficient sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with a single required parameter and no output schema, the description adequately lists the key returned fields, and the input schema defines the ID parameter. While it lacks usage context and edge-case handling, it is sufficiently complete for an agent to understand and invoke the tool correctly for a straightforward listing lookup.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the 'id' parameter clearly described as 'Numeric Etsy listing id'. The tool description adds no additional parameter-level detail beyond what the schema already provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get Etsy listing detail' and enumerates the returned fields (title, price, images, materials, tags, and shop), making the tool's purpose easy to understand. However, it does not explicitly differentiate it from sibling tools like etsy_listing_reviews or etsy_shop_listings, which also deal with listing-related data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for retrieving a single Etsy listing's details by ID, but it provides no explicit guidance on when to use this tool over alternatives such as etsy_search or etsy_shop_listings. There is no mention of exclusions or recommended use cases, leaving the context to be inferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for behavioral disclosure. It only states that it returns search results; it does not explain pagination behavior, ordering, authentication requirements, rate limits, or whether results include full listing details. This is a significant gap for a search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exactly two short sentences that immediately convey the tool's purpose and scope. There is no redundant or irrelevant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool with no output schema, the description explains the core functionality but omits details about the result structure, pagination behavior, or any constraints. Given the minimal complexity, this is adequate but not comprehensive; an agent may need to inspect actual results to understand the format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema describes all three parameters with 100% coverage, including types, defaults, and descriptions (e.g., 'Search keywords', 'default 36, max 100'). The description adds no additional parameter-level information, so it meets the baseline but provides no extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches Etsy listings and returns results across multiple shops, using a specific verb ('Search') and resource ('Etsy listings'). The phrase 'across shops' distinguishes it from shop-specific tools like etsy_shop_search and etsy_shop_listings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this versus alternatives is provided. The phrase 'across shops' implies it is for general keyword search across the entire marketplace, but it does not mention that shop-specific searches should use etsy_shop_search or that specific listing details should use etsy_listing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It only states that the tool 'returns buyer reviews' but does not mention pagination behavior, sorting, default ordering, potential errors, or whether rating data is included. This is a clear gap for a tool without annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences that clearly state the action, result, and input format. There is no wasted wording, and key details are front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with three well-documented parameters, but the description lacks contextual details such as what a review contains, how results are ordered, or any notes about pagination beyond the schema. Given no output schema and no annotations, the description is minimally sufficient but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% parameter coverage with descriptions for id, limit, and offset. The description's mention of accepting a numeric shop id or shop name adds no new meaning beyond the schema, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get'), identifies the resource ('Etsy shop reviews'), and clarifies the accepted input ('numeric shop id or shop name'). It clearly distinguishes from sibling tools like etsy_listing_reviews by specifying 'shop' reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when one needs buyer reviews for an Etsy shop, but it does not explicitly provide when-to-use guidance or mention alternative tools (e.g., etsy_listing_reviews for listing-specific reviews). No exclusions are stated, but no proactive guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It mentions email is conditional, but lacks disclosure on authentication needs, rate limits, or error handling (e.g., user not found). Some behavioral info given, but significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences, front-loaded with the main purpose. Each sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so description should fully explain return data. It mentions profile, social links, and conditional email, but is vague on what 'profile' entails (e.g., name, bio, avatar). Adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with the parameter 'username' described as 'GitHub username'. The description adds no additional semantics beyond the schema, which is adequate but not enhanced.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool retrieves a GitHub user profile and specifies what is returned (profile, social links, conditional email). It distinguishes from sibling tools like github_user_repos or github_user_events by focusing on profile data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like github_search_users or github_user_repos. The description does not provide context for selection among the many GitHub-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions pagination ('Returns a page') but lacks details on rate limits, authentication requirements (public API assumed), error behavior for non-existent users, or what 'page' means. With no annotations, the description should disclose more behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with an additional clarifying sentence. No superfluous words, and it efficiently conveys the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema, the description hints at the return format (page of accounts) but does not specify what fields are returned or pagination details. It is adequate for a simple listing tool but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with descriptions for all three parameters (username, page, per_page). The description adds no additional semantic meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists a GitHub user's followers and specifies it returns public accounts. The verb 'list' and resource 'followers' are precise, and it distinguishes from siblings like github_user_following (which lists who the user follows).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance. While the name implies usage for listing followers, it does not mention alternatives or context like prerequisites (e.g., username existence) or compare with similar tools like github_user for user details.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It only states that it retrieves similar apps from a specific cluster, but fails to mention any behavioral traits such as read-only nature, authentication requirements, rate limits, or error handling for invalid app_ids. This lack of detail is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—two sentences with zero waste. It front-loads the action and resource, making it easy for an agent to quickly grasp the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description misses details about what the returned data looks like (no output schema) and how the 'Similar apps' cluster is defined. Given the moderate complexity (5 params, many sibling tools), the description is adequate but leaves gaps in understanding for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (all 5 parameters are described in the schema). The tool description adds no additional parameter information beyond what the schema already provides, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the verb 'Retrieve' and the resource 'similar Google Play apps', and pinpoints the source as the 'Similar apps' cluster on an app details page. This distinguishes it from sibling tools like googleplay_app (single app details) or googleplay_search (search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you have an app id and want similar apps, but does not explicitly state when to use this tool versus alternatives like googleplay_search or appstore_similar. No exclusions or alternative recommendations are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states it is 'public unauthenticated,' implying safety. It does not disclose rate limits, result format, or failure modes. Some transparency is provided but missing key behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, totaling 18 words, with no redundant or irrelevant information. It is highly concise and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The schema fully documents parameters, but no output schema exists. The description mentions 'autosuggest query completions' but does not specify the format (e.g., array of strings). Missing details on response structure and default behaviors beyond schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds no parameter-specific meaning beyond the schema; it merely repeats the purpose. No additional semantics are provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool suggests Google search queries and returns autosuggest completions from the public unauthenticated endpoint. It explicitly names the resource ('Google autosuggest query completions') and distinguishes itself from sibling suggest tools for other platforms.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool vs alternatives like google_search or other platform suggest tools. It does not mention that it is for autocomplete only, not full search, or note any advantages (e.g., no auth required).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Mentions 'credential-free public' source, indicating no auth required. But no disclosure of rate limits, error handling, or data freshness. With no annotations, more detail would be beneficial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise at two sentences. No redundant information, front-loaded with purpose. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema provided, and the description gives no indication of what fields are returned (e.g., title, year, rating). This lack of return value context limits the agent's ability to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema already provides descriptions for both parameters (100% coverage). The description adds the critical constraint 'exactly one of id or url', which is not in the schema and enhances understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns 'normalized IMDb title metadata', specifying the resource and action. It distinguishes from sibling search tools but does not explicitly differentiate from other title-specific tools like imdb_title_credits.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit instruction to pass exactly one of id or url, which is helpful. However, it lacks guidance on when to use this tool versus alternatives like imdb_title_awards or imdb_search.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description fails to disclose safety, permissions, rate limits, or error behavior. It only mentions output content partially.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences convey purpose, output, and a key usage rule without any redundancy. Every sentence adds essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Describes output broadly but lacks detail on structure, pagination, or limits. Given no output schema, more detail would help, but it covers the basics for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds critical constraint 'Pass exactly one of id or url', which prevents misuse. This adds significant value beyond schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'normalized public IMDb release date rows and alternate titles', specifying a unique resource. It distinguishes from sibling tools like imdb_title or imdb_title_credits by focusing on release info.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Only provides a parameter rule ('Pass exactly one of id or url') but no guidance on when to use this tool versus other IMDb tools or context about prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It states the tool returns normalized metadata and offers, but does not explicitly confirm it is read-only, nor does it disclose any authentication requirements, rate limits, or error handling. The description is functional but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. The description front-loads the verb and resource, then provides a clarifying example. It is efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters and no output schema, the description mentions the output type ('normalized metadata and offers') but does not give any specifics about the return structure. A more complete description would list example fields or common return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds the id format `tse[0-9]+` which is already in the schema, and implies country/language are for filtering offers, but does not add new semantic meaning beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'get' and the resource 'episode by raw id', with a concrete example of the id format. It distinguishes from sibling tools like 'justwatch_title_by_id' or 'justwatch_season_episodes' by specifying this tool is for episodes by raw id.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives, such as searching for episodes by title or season. The description does not mention prerequisites, preferences, or exclusions, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses parameter constraints (type values, limit defaults/clamps) but omits response structure, pagination, rate limits, or authentication requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two sentences with no wasted words. The first sentence front-loads the purpose, and the second efficiently covers parameter constraints.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and full schema coverage, the description covers the essential purpose and parameter rules. However, it lacks response format details and differentiation from similar sibling tools like justwatch_popular, limiting completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description restates type and limit constraints already in the schema, adding negligible new semantics beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Get new JustWatch titles. Returns newly available movies and shows.' It uses a specific verb and resource, distinguishing it from sibling tools like justwatch_popular or justwatch_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus alternatives. It fails to mention prerequisites, when-not-to-use, or compare with siblings like justwatch_popular, which also returns titles.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It only states the function without disclosing important behaviors such as error handling for invalid IDs, rate limits, or whether the operation is read-only. Basic transparency is lacking.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences. It front-loads the purpose and provides a concrete example with zero waste. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters but no output schema, the description should hint at the return format. It says 'Returns similar titles' but omits details about the structure (e.g., array of IDs, objects with titles, scores). This is adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, providing baseline 3. The description adds value by giving an example ID format (tm92641), which clarifies the id parameter beyond its regex pattern. However, it does not elaborate on country, language, or limit beyond what the schema already offers.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Get similar JustWatch titles' with an example ID format. It is specific about the resource (JustWatch titles) and the action (getting similar ones). The tool is distinct from siblings like justwatch_search (which searches broadly) and justwatch_title (which retrieves details).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for finding similar titles when an ID is known but provides no explicit guidance on when to use this tool versus alternatives (e.g., justwatch_title_analysis). There are no exclusions or prerequisites mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It states it returns flags from market-data JSON, implying read-only behavior. For a simple status endpoint, this is adequate. Does not mention any side effects or limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose. No extraneous information. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless tool with no output schema, the description is complete: it explains what the tool does and the type of data returned. Given the complexity (low), no further details are needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so schema coverage is 100%. Baseline for 0 params is 4. Description adds context about what is returned (public exchange and trading active flags), which is helpful.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns exchange status with specific flags (public exchange and trading active). It uses verb 'Returns' and resource 'Kalshi exchange status'. Among many Kalshi siblings, it is distinct as a simple status tool, though not explicitly differentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternative Kalshi tools (e.g., kalshi_event, kalshi_markets). No when-not-to-use or prerequisites mentioned. Agent must infer from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description only mentions credential-free access and normalized output. Does not disclose rate limits, data freshness, error handling, or pagination behavior. For a data retrieval tool with no annotations, more transparency is needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two efficient sentences with no filler. The first sentence restates the name, but the second provides critical information about normalization and credential-free access.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema; description partially compensates by mentioning 'normalized Kalshi candlesticks' but lacks field details. Parameters are documented, but return structure is too vague for a data retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All 6 parameters have schema descriptions, so baseline is 3. Description adds no extra meaning beyond what schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it returns candlesticks for one Kalshi market, distinguishing it from siblings like kalshi_market or kalshi_event_history. The verb 'returns' and object 'normalized Kalshi candlesticks' are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when to use or when not to use compared to other history tools. Mentions 'credential-free' but lacks guidance on selecting this over siblings like kalshi_historical_market_history.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description fully bears the burden. It mentions that results are 'normalized' and from 'public orderbook JSON,' but it does not explain the return structure, any side effects, authorization requirements, or rate limits. Minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
A single 17-word sentence that is front-loaded and contains no filler. Every word contributes to the purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description is moderately complete. It states the output (normalized yes/no bid levels) but does not describe the output structure or format, leaving an agent without full context. Adequate but improvable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (ticker described as 'Kalshi market ticker'). The description adds that it is 'one' ticker and from public data, but this adds minimal meaning beyond the schema. Baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns normalized yes/no bid levels for one Kalshi market ticker from public orderbook JSON. It distinguishes from sibling tools like kalshi_markets_orderbooks (plural) by specifying 'one' ticker.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives (e.g., kalshi_market or kalshi_markets_orderbooks). The purpose implies it is for a single market orderbook, but no when-not-to or exclusion criteria are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It adds useful context with 'Credential-free public Letterboxd data,' indicating no authentication required. However, it does not disclose behavior for invalid slugs, rate limits, or output format, leaving gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences. The key action ('Get films similar') is front-loaded. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 2 parameters and no output schema, the description is adequate but not complete. It explains the basic purpose and credential-free nature, but does not describe the output format (e.g., expected fields like slug or title) or handle edge cases. The limit parameter is noted in schema, but pagination context is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description does not add additional meaning beyond the schema; it repeats that the tool returns similar films but does not elaborate on slug format or limit behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get films similar to a Letterboxd film' and 'Returns films Letterboxd recommends as similar to the given film.' It uses specific verbs and resources, distinguishing it from siblings like letterboxd_film or letterboxd_popular, which serve different functions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is provided on when to use this tool versus alternatives. The description implies usage when you need similar films, but it does not mention when not to use it or provide context on choosing between siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It states the tool is read-only and public, but lacks details on rate limits, error handling, or pagination. Adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with purpose, no unnecessary words. Efficiently communicates core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 params and no output schema, the description covers purpose and method enum but leaves out information on the structure of returned history points, which may require clarification for proper interpretation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description lists the allowed values for 'method' but adds no new meaning beyond the schema's parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'returns' and resource 'forecast history points' for a specific Metaculus question, distinguishing it from related tools like metaculus_question_forecasts or metaculus_question_metadata.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives such as metaculus_question_forecasts. It only mentions 'credential-free public page data' but does not specify conditions or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It indicates a read operation ('Returns') and mentions 'latest' values, but lacks details on side effects, permissions, rate limits, or data freshness. It provides basic transparency but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—two sentences that front-load the core purpose and then detail the method parameter. Every sentence adds value without unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 parameters, no output schema), the description is fairly complete: it specifies the output (labels and latest forecasts) and the input options. It could mention the format or error cases, but overall it provides sufficient context for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explicitly listing the enum values for the 'method' parameter (recency_weighted, unweighted, single_aggregation), which the schema only describes as 'Aggregation method'. This helps the agent select valid inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns multiple-choice option labels and latest option-level forecast values for one Metaculus question, distinguishing it from other metaculus tools by specifying the type of data (options and forecasts) and scope (one question).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention exclusions or context. It only describes functionality, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, so description carries the burden. It discloses public credential-free access and outlines return contents. However, it omits potential rate limits, latency, data freshness, or error behaviors, which are important for a browsing tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (three sentences) and front-loaded with the core purpose. Each sentence provides distinct information (grid listing, pagination, region/language, credential-free). No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately explains the return structure (per-item details and filter facets) and pagination. However, missing details like default ordering, sorting options, and empty result handling leave some completeness gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with three parameters. The description adds meaningful context beyond the schema: 'l' as text language, 'cc' as country code for currency, 'page' as 1-based and 'next_page' for pagination. This helps agents understand parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it browses the PlayStation Store all-games grid, listing what it returns (price, platforms, media, filter facets). However, it doesn't explicitly differentiate from 'playstation_search' or 'playstation_category', which are sibling tools for more specific queries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Describes pagination (page parameter, next_page) and region/language parameters (cc, l), but lacks guidance on when to use this browsing tool versus alternatives like playstation_search. No explicit when-not-to-use or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that data is credential-free and public, but does not cover rate limits, caching, data freshness, pagination, or other behavioral traits. The description is too brief to fully compensate for the lack of annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no unnecessary words. The first sentence states the core function, and the second adds relevant details about the return structure and parameters. It is front-loaded and every sentence is concise and purposeful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is no output schema and no annotations, the description adequately explains what is returned (shelves with titles and prices, plus a flattened list) and the parameters. However, it lacks details on output format, field names, defaults, or limits, leaving some gaps for a tool with no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and both parameters have descriptions. The description adds context that 'cc selects the store region (and price currency)' and 'l the text language', which slightly extends the schema descriptions but does not add significant new meaning beyond what is already in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets PlayStation Store deals shelves, specifying the resource ('deals shelves') and the output structure (list of shelves with titles and per-item price, plus a flattened deduplicated list). It differentiates itself from siblings like playstation_browse and playstation_search by focusing on deals.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions optional parameters for region and language, and states it is 'credential-free public PlayStation Store data', implying no authentication is needed. However, it does not explicitly state when to use this tool versus alternatives like playstation_browse or playstation_search, nor does it provide exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It mentions results are 'normalized similar events' and 'credential-free', but does not explain how similarity is determined, whether inputs are required, or any potential side effects or limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no unnecessary words. The purpose is front-loaded and the source is specified. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 7 optional parameters and no output schema, the description is too brief. It does not explain the relationship between parameters (e.g., which are typically used together) or the notion of similarity, leaving the agent to infer proper usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and each parameter has a basic description, but the tool description adds no extra meaning beyond what is in the schema. The description's note about 'returns normalized similar events' is more about output than input semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool finds similar Polymarket events, names the data source ('Gamma events/similar JSON'), and the name 'similar' distinguishes it from other Polymarket tools like polymarket_events or polymarket_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when similar events are needed, but does not explicitly state when to use this tool versus alternatives like polymarket_events or polymarket_search. No exclusion criteria or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions it's 'credential-free Gamma JSON' and explains differences between feed types (e.g., breaking returns high-movement rows). However, it lacks details on rate limits, data freshness, or whether writes are possible. With no annotations, this is acceptable but not fully transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. The key information (purpose, feed enum, differences) is front-loaded. The structure is optimal for an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema or annotations, the description covers the tool's purpose, parameter details, and feed-specific behavior. It could mention common response fields or pagination behavior, but for a listing tool it is fairly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds meaningful context: lists all feed enum values, clarifies that cursor is a keyset from a prior response, and specifies limit defaults and max. This goes beyond the schema's short descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists Polymarket homepage feed rows and explains the feed enum values. However, it does not explicitly differentiate from sibling tools like polymarket_events or polymarket_markets, making it slightly less distinctive.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives among the many Polymarket endpoints. The description implies it's for homepage feeds but doesn't advise when not to use it or mention sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that no authentication is required and it is not a trading endpoint. However, it does not describe behavior when token ids are unavailable, rate limits, idempotency, or other side effects. The phrase 'when token ids are available' implies conditional behavior but lacks full disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, using three sentences to convey purpose, data sources, and authentication requirements. It is front-loaded with the core action and efficiently adds detail without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a single parameter and no output schema, the description covers the basics: purpose, data sources (Gamma, CLOB), and auth requirements. However, it lacks details on the output format or structure, which would aid agent usage. The sibling list includes many similar tools, so additional context on when to choose this tool would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for the single required parameter 'id', which is well-documented as 'Polymarket market id'. The description does not add additional semantics beyond what the schema provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Polymarket market liquidity. It distinguishes itself from trading endpoints by noting it is not a trading endpoint and does not require authentication. However, among sibling tools like polymarket_market_detail and polymarket_clob_market, it does not explicitly differentiate its unique purpose beyond 'liquidity snapshot'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context that this endpoint is for public, non-authenticated data access and is not for trading. However, it does not specify when to use this tool versus other similar Polymarket tools, nor does it mention any prerequisites or scenarios where other tools would be preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full burden. It adds minor transparency by mentioning 'credential-free public Gamma markets JSON', implying no authentication needed. However, it does not disclose rate limits, sorting behavior, or pagination details beyond what the schema already indicates.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, consisting of two clear sentences. It efficiently conveys the tool's purpose and key output characteristic without extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description could do more to explain what a 'normalized market row' contains. The description is brief and leaves some ambiguity about the output structure, making it moderately complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description does not add extra meaning to the parameters (ascending, closed, limit, offset, order) beyond their schema definitions, so it meets the baseline but adds no additional value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List Polymarket markets' which is a specific verb+resource. It further explains it returns 'normalized market rows', and the tool's name and context distinguish it from siblings like polymarket_market_detail or polymarket_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives like polymarket_search or polymarket_market_detail. There is no mention of context, prerequisites, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes 'credential-free public search JSON' and enum values for status and sort, adding behavioral context beyond mere existence, but lacks details on pagination or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise with front-loaded purpose and essential value-add information in three sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers data source, output type, and key parameter constraints; lacks output structure but acceptable without output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and description adds enumerations for status and sort not in schema, enhancing parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches Polymarket events and returns normalized results, but does not explicitly distinguish from sibling tools like polymarket_events which may also return events.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives; no when-not or prerequisites mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It only states that it returns 'public CLOB order-book depth,' without detailing what the depth includes (e.g., bids/asks, levels), whether authentication is required, rate limits, or any side effects. This is minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences and 15 words, with no redundant information. Every word serves a purpose, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description partially compensates by stating it returns 'order-book depth,' but fails to specify the format (e.g., bid/ask arrays, levels). It is minimally adequate for a simple token-level tool but could be more informative.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter token_id described as 'Polymarket CLOB token id.' The description adds no additional meaning beyond the schema, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a Polymarket token order book, specifically 'public CLOB order-book depth for one Polymarket token id.' This verb+resource combination distinguishes it from sibling tools like polymarket_token_price (price) or polymarket_token_midpoint (midpoint), and the singular 'one token' contrasts with the plural polymarket_tokens_orderbooks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly indicates use when a single token's order book depth is needed, but it does not explicitly state when to use this tool versus alternatives like polymarket_tokens_orderbooks (for multiple tokens) or polymarket_token_spread. No when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description mentions pagination and GraphQL operation but omits behavioral traits like read-only nature, authorization needs, or rate limits. Minimal beyond what the name suggests.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-loading the purpose and key details (pagination, GraphQL). No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, so return format is not described. While simple, the description could specify what launch posts contain. Adequate for a basic retrieval tool but leaves gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for id, cursor, and order. Description adds 'pagination' context but does not significantly enhance parameter understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Retrieve Product Hunt product launches' with a specific verb and resource, distinguishing it from siblings like producthunt_product or producthunt_reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage via 'for a Product Hunt product' but lacks explicit when-not-to-use or alternative tool guidance. No exclusion criteria or comparison to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states the tool lists related products and returns cards, but does not mention that it is a read-only operation (non-destructive), any required authorizations, rate limits, or how 'related' is determined. Significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: first states purpose, second describes output. No redundant information or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description's mention of 'related product cards' is vague. Behavioral context is missing due to lack of annotations. However, for a simple listing tool, it is adequate but leaves room for more detail, especially among many similar siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no additional meaning to the parameters beyond what the schema already provides (id is product id, limit has default and max).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists related Shop.app products from a product page, using a specific verb and resource. It distinguishes from siblings like shop_app_product which likely returns a single product's details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by mentioning 'from a public Shop.app product page' but does not explicitly state when to use this tool versus alternatives like shop_app_product or shop_app_search. No exclusions or when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must cover behavioral aspects but only states it returns public retail locations. It omits details like authentication needs, read-only nature, rate limits, or response structure, leaving gaps for an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two clear sentences. Every word serves a purpose, and no unnecessary information is included.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (2 parameters, no output schema), the description is adequate but minimal. It could be improved by hinting at output details or common usage patterns, but it is not incomplete for a basic list tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds no extra meaning beyond the schema; it simply restates the parameters. No additional context or clarifications are provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists Shop.app shop locations for a merchant profile. It uses a specific verb and resource, and the name distinguishes it from siblings like shop_app_shop and shop_app_shop_products.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving locations but provides no explicit guidance on when to use it versus alternatives or when not to use it. Context suggests it's the correct tool for locations, but no exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral traits. It only mentions the limit default and maximum, but lacks details on rate limits, caching behavior, or input validation. This is minimal for a suggestion tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loading the purpose and adding a behavioral note about the limit. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description does not explain the return format (likely a list of strings). For a simple autocomplete tool, this may be acceptable, but the description could be more complete by hinting at output structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents parameters. The description adds the default limit value (10) and max (20), which is a minor addition over the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it suggests Shop.app searches and returns autocomplete suggestions. This distinguishes it from sibling tools like shop_app_search (which likely returns full search results) and shop_app_shop_typeahead (which is shop-specific).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly suggests use for autocomplete functionality, but does not explicitly state when to use this tool versus alternatives like shop_app_search or shop_app_suggestions. There is no 'when not to use' guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the transparency burden. It discloses that the endpoint is credential-free, which is a useful behavioral trait. However, it does not mention read-only nature, rate limits, or error handling for invalid handles.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences, no wasted words, and front-loaded with the verb and resource. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has only 2 parameters, no output schema, and no annotations, the description is minimally adequate. It states what is returned (normalized product detail) but lacks specifics about the output format or any constraints. Could be improved with example or field hints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters ('handle' and 'url'). The description reinforces that the handle is the product identifier but adds no additional meaning beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and resource 'Shopify product', and distinguishes itself by mentioning the specific endpoint ('credential-free product handle .js endpoint'), which differentiates it from sibling tools like shopify_products or shopify_product_recommendations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The description implies it is for retrieving a single product detail from Shopify, but does not mention exclusions or comparison with sibling tools like shop_app_product or shopify_products.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It adds useful context: 'credential-free' (no auth needed) and that an empty events list is a valid response. However, it omits details on rate limits, data freshness, or any other behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two sentences that front-load the purpose and include key details. No redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description is adequate. It covers the core functionality, valid sport values, and a note on empty responses. Missing details like pagination or limits are acceptable given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema describes `sport` as 'Sport key' (100% coverage). The description adds concrete enum values ('football', 'basketball', 'tennis'), which provides meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'currently live events for a sport' and lists the supported sport values. However, it does not explicitly distinguish itself from sibling tools like `sofascore_event` or `sofascore_round_events`, which limits differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description mentions 'credential-free' but does not explain context, exclusions, or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It mentions 'credential-free public JSON' and that an empty results list is valid, but it does not address rate limits, pagination, or response structure. This is insufficient for full transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no wasted words. It efficiently conveys the tool's purpose, data source, and valid response behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search with one parameter and no output schema, the description is reasonably complete. It specifies what is searched (teams, players, competitions) and that an empty result is valid. However, it could mention if results are ordered or any default limits.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'q' is fully described in the schema ('Free-text search query'). The description does not add additional meaning beyond the schema, so it meets the baseline for full schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool performs a 'universal search' for teams, players, and competitions, with a clear verb ('searches') and resource ('SofaScore's...JSON'). It distinguishes from siblings like sofascore_event and sofascore_team by being a general-purpose search across multiple entity types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for general search but does not specify when to use it over specific entity tools (e.g., sofascore_team, sofascore_event). No exclusions or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It correctly implies a read operation ('Retrieve') and notes a default behavior (CHARTS content shelf). However, it does not elaborate on whether the tool is purely read-only, potential side effects, or any rate limits or permissions needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no redundancy. The main action is front-loaded, followed by necessary detail about the return type and default behavior. Every sentence serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with optional parameters, the description is adequate but not thorough. It lacks details about the output format (since no output schema is provided) and doesn't address edge cases like invalid country codes or content IDs. Given the sibling set, it could benefit from brief comparisons.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (both parameters have descriptions). The description adds minimal value beyond the schema: it mentions the default value for content_id and uses similar language for country_code. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Spotify featured charts by country, with a specific verb and resource. It also distinguishes from general Spotify search tools by specifying 'normalized country hub content' and defaulting to the CHARTS shelf, though it does not explicitly differentiate from similar sibling like spotify_popular_by_country.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, such as spotify_popular_by_country or other chart tools. There are no usage constraints, prerequisites, or contraindications mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden. It only states the operation and source, without disclosing side effects, auth requirements, rate limits, or other behavioral traits. For a read operation, it's minimally acceptable but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: first for purpose, second for return details. No unnecessary information, front-loaded with the key action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists. The description mentions return format but not structure. With 6 optional parameters, the description lacks details on defaults or pagination behavior. Adequate but with gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 6 parameters. The description adds no further meaning beyond what the schema provides. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Retrieve'), the resource ('Spotify Podcasts home'), and the return type ('normalized sections and items'). It distinguishes this tool from siblings like spotify_home and other spotify_podcasts_* tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The description implies it's for the podcast home page, but doesn't contrast with similar tools like spotify_home or spotify_podcasts_categories.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It states the tool is 'credential-free' and 'public', but does not disclose rate limits, caching, or any potential side effects. It adds some value but could be more transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is mostly concise but has redundancy: 'Get...' and 'Returns...' say essentially the same thing. Could be tightened without losing meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description explains return contents and the 'cc' parameter well, but omits explanation of 'l' and lacks usage examples or prerequisites. Adequate for a simple tool but with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%. The description adds context for the 'cc' parameter (affects currency and sales ranking) but does not explain the 'l' parameter beyond the schema. Overall, marginal added value over schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves Steam's weekly top-sellers chart for a country, specifying the resource (top-sellers chart) and action (get). It distinguishes from sibling tools like steam_app or steam_search by being explicitly about the top-sellers chart.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for getting weekly top-sellers by country but does not indicate when to use this tool over others (e.g., steam_featured, steam_charts_most_played). No explicit alternatives or exclusions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses pagination and nested answers, which is useful, but does not mention rate limits, data freshness, error behavior, or default pagination values. Adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with a clear action verb. Minor redundancy between 'questions and answers' and 'product questions with their nested answers', but overall efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple list operation and fully described schema, the description provides key return information (paginated, nested answers). It could mention the required tcin parameter or defaults, but these are available in the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with each parameter described (page, tcin, per_page). The description adds no extra meaning beyond the schema, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'List' with a clear resource 'Target product questions and answers', distinguishing it from sibling target_reviews (reviews) and target_product (product details).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided for when to use this tool versus alternatives like target_reviews or target_product. The description only states what it does without any exclusions, alternatives, or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full transparency burden. It only discloses that the profile must be public and that visible biography and counts are returned. It does not cover behavior for private or nonexistent profiles, rate limits, authentication needs, or other side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. Every phrase earns its place by identifying the resource, the action, and the key return contents.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter, and the description gives a reasonable indication of return values (metadata, biography, counts). However, with no output schema, it could add more detail about username format, edge cases, or what 'counts' specifically include, making it only minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully describes the single 'username' parameter with 100% coverage, so the description adds little beyond restating that the tool looks up a Threads username. The baseline of 3 applies because the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Retrieve') and resource ('public Threads profile'), and clarifies the scope by mentioning 'public profile metadata', 'visible biography', and 'counts'. This distinguishes it from sibling tools like threads_profile_posts, which return posts rather than profile metadata.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context: it retrieves a public profile for a known Threads username. However, it does not explicitly state when to use this tool over siblings like threads_search or threads_profile_posts, nor does it mention alternatives or exclusions beyond 'public'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and description only states 'Retrieve posts' with no mention of side effects, rate limits, or other behavioral traits. As a read operation, it lacks disclosure of potential limitations or data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Concise two-sentence description, no verbosity, front-loads the primary action and resource efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, and description does not specify the structure or fields of returned posts. While parameter details are clear, the return value could be better described for agent planning.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so description adds little beyond what the schema already documents. Description mentions parameters but does not provide additional semantic context or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the action (retrieve) and resource (posts from a TikTok profile) with key parameter (secUid). Distinguishes from sibling tools like tiktok_post or tiktok_search by specifying profile posts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage for retrieving a user's posts but does not explicitly state when to use this tool over alternatives like searching posts or getting a single post. No when-not or alternative tool mentions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions 'cursor-based pagination' and 'count clamped to 50', which are behavioral traits not shown in annotations (none provided). However, it omits critical details such as what the tool returns (e.g., video metadata), potential authentication requirements, or any side effects. For a search tool, this is minimally adequate but could be richer.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two short sentences that front-load the core purpose. Every word is functional, with no fluff or redundant information. It is highly efficient and easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool with three parameters and no output schema, the description covers the basic action and key constraints (pagination, clamping). However, it lacks information about the response format (e.g., what fields are returned for each video) and any rate limits or authentication needs. This missing context reduces completeness for an agent relying solely on the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes all three parameters (keyword, cursor, count) with 100% coverage. The description's mention of 'cursor-based pagination' adds marginal context, but the clamping detail repeats the schema. With high schema coverage, the description adds little beyond the schema, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search TikTok videos' with the verb 'Search' and resource 'TikTok videos'. It specifies the method (by keyword) and pagination approach (cursor-based). This effectively distinguishes it from sibling tools like tiktok_search_hashtag and tiktok_search_user, which target different resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus the many other TikTok search tools (e.g., tiktok_search_hashtag, tiktok_search_user, tiktok_trending). It does not include any 'when-not' or alternative recommendations, leaving an AI agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. However, it fails to mention any details such as rate limits, caching, pagination, or the structure of the returned feed. This leaves the agent without critical information for correct invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two clear sentences and no redundant or extraneous information. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema, the description adequately states the action and result. However, it lacks information about the output format (e.g., list of objects with fields), which would help the agent understand what to expect. A simple addition specifying the returned data structure would make it complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so the schema coverage is 100% trivially. The description does not need to add parameter info. According to the scoring rules, 0 parameters yields baseline 4, and there is no missing information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves TikTok trending posts and returns the current trending feed, which is a specific action on a specific resource. It is distinguishable from sibling tools like tiktok_explore or tiktok_search that serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. Among many TikTok sibling tools, there is no mention of when to choose trending over explore, search, or specific hashtag tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description notes the tool is 'credential-free' and returns public data, implying no authentication needed and read-only behavior. However, it lacks details on error handling, rate limits, or side effects, which is significant since no annotations are provided.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that front-load the purpose and return content. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with 2 parameters and no output schema, the description covers the main return fields and notes public data. It does not elaborate on the filmography structure or limit parameter behavior (though schema covers limits), but overall it is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers both parameters (id, limit) with descriptions. The description adds value by listing the output fields (biography, birth date, photo, filmography) and mentioning 'normalized' data, which helps the agent understand what the tool returns.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a TMDB person and lists the returned fields (biography, birth date, photo, filmography). The name and description differentiate it from sibling TMDB tools like tmdb_movie or tmdb_search, but it doesn't explicitly contrast them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like tmdb_search. The description does not state prerequisites (e.g., needing a person ID) or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries the full burden. It lists return fields but does not disclose side effects, authentication needs, rate limits, or idempotency. For a read operation, this is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two focused sentences deliver the core purpose and content without fluff. The key verb 'Get' and resource 'TrustMRR startup detail' are front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description adequately covers what is returned. It lists key data fields, making it useful for an agent to decide if this tool meets the need.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameters, so baseline is 3. The description adds minimal value beyond confirming the slug identifies the startup. No example or format details are given.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves a single TrustMRR startup's full verified profile by slug, listing specific fields (e.g., revenue, MRR, growth, tech stack). This distinguishes it from multi-startup tools like trustmrr_startups, but it does not explicitly contrast with siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied: to get details for a specific startup when you know its slug. However, no guidance is given on when to use this versus alternatives (e.g., trustmrr_startups for lists, datasets_trustmrr_item for different data). The agent must infer from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It states 'Public data, sourced from Vinted's own server-rendered category page', which gives useful sourcing context, but it does not disclose pagination behavior, result structure, or rate limits. This is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively short but contains redundancy—the first sentence 'Vinted listings for a category.' is restated by the next sentence. The order values list is useful, but the repetitive opening wastes a sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description gives the essential purpose, filters, sort options, and data source, but leaves out return shape and pagination details. It is sufficient for basic invocation but not fully complete for a 5-parameter tool without an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents all five parameters. The description reiterates the order enum values and mentions price filtering, but adds little beyond the schema. It does not elaborate on id provenance or page semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Returns' and names the resource 'Vinted listings for a specific category', clearly distinguishing it from sibling tools like vinted_categories or vinted_item. The mention of optional price filtering and sort order adds useful scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage context is implied ('Returns Vinted listings for a specific category') but no explicit when-to-use vs alternatives is provided. The description does not mention exclusions or alternative tools such as vinted_brand, vinted_catalog, or vinted_item.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only lists output categories but does not mention that the tool is read-only, any authentication needs, rate limits, or side effects. The description lacks crucial behavioral context for an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the tool's purpose and lists the returned data concisely. No unnecessary words. Every part adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has only one parameter and low complexity. However, there is no output schema, so the description should provide more detail about the structure of the returned data. Also, it does not guide the agent on how to obtain valid sector keys (e.g., via yahoo_finance_sectors). Completeness is adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (the key parameter is well-described as 'Sector key such as technology'). The description adds little beyond 'for a sector key', which is already clear from the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns sector detail including overview, top companies, ETFs, etc., for a given sector key. It uses specific verbs and resource names, and the description distinguishes it from sibling tools like yahoo_finance_sectors (list sectors) and yahoo_finance_industry (industry details).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when one has a sector key and needs sector details, but it does not explicitly state when to use this tool versus alternatives like yahoo_finance_sectors or yahoo_finance_industry. No guidance on prerequisites or context is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description does not disclose behavioral traits such as being read-only, authentication needs, or rate limits, leaving the agent with insufficient transparency for a data retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The single-sentence description is concise and front-loaded with purpose, but lacks structured formatting like bullet points. It is efficient without being wasteful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description lists the returned modules (fund profile, top holdings, etc.) and specifies symbol types. It covers the essential context for a simple parameter and data retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter 'symbol' described as 'Yahoo Finance symbol such as SPY'. The description adds no further meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns 'fund profile, top holdings, equity/bond holdings, and sector weighting modules' specifically for ETF and mutual fund symbols, distinguishing it from sibling tools like yahoo_finance_ticker_info or yahoo_finance_ticker_quote.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for ETF and mutual fund symbols but provides no explicit guidance on when to use this tool versus alternatives, nor does it mention when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must fully disclose behavior. It indicates a read operation ('Returns current share-count fields'), but omits details about data freshness, response structure, pagination, or any side effects. This is insufficient for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, using two short sentences to convey the tool's purpose and resource. It is front-loaded with the key information (Yahoo Finance share counts) with no extraneous content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of having many sibling tools and no output schema, the description is minimal. It covers the basic purpose but lacks detail on the returned data fields, assumptions, or prerequisites. A more complete description would include what constitutes 'share-count fields' or mention if the symbol must be valid.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single 'symbol' parameter described as 'Yahoo Finance symbol such as AAPL'. The description adds no further meaning beyond the schema, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns current share-count fields from Yahoo key statistics for a given symbol. It distinguishes itself from many related yahoo_finance_ticker_* siblings by specifying 'share counts', making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives or when not to use it. Usage is implied by the description (when you need share counts), but no context or exclusions are provided, resulting in an average score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the disclosure burden. It explains the source (server-rendered homepage) and the output fields, implying a read-only operation. However, it doesn't mention freshness, pagination, number of stories, or any rate limiting.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, all informative: the first identifies the resource, the second lists output fields, the third gives a sourcing detail. No filler or unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter homepage feed, the description covers the essentials: what it is, what fields are returned, and the source. It doesn't specify whether the feed is current or archived, how many stories are returned, or whether the response is paginated, but these are minor gaps for this simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0 parameters, there is no schema detail to supplement. The description is appropriately explicit about what is returned, so an agent knows what to expect without needing parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns Yahoo Health's homepage editorial story feed with specific fields (title, destination URL, category, thumbnail). It distinguishes itself from yahoo_health_article and yahoo_health_category by being a homepage feed, though it doesn't name them explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this is for fetching the Yahoo Health homepage feed without parameters, which distinguishes it from article/category tools. However, it doesn't explicitly state when to choose this over yahoo_health_article or yahoo_health_category, nor does it mention alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It discloses the data source ('Yahoo's own server-rendered video-search page'), the implicit read-only nature, and a concrete list of returned fields (title, destination page URL, source domain, description, thumbnail, duration). It does not cover pagination or ordering but these are minor for a single-query search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with the essential purpose. The second sentence restates part of the first ('Yahoo's video-search results') while adding valuable return-field detail, so the redundancy is minor and the overall size is appropriate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, low-complexity tool with a single required parameter and no output schema, the description provides enough context: it states the purpose, lists the return fields, and names the source. The lack of pagination or result-limit details is a small gap but not a significant one for a video-search query tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully documents the only parameter, q, with the description 'Search query', so schema coverage is 100%. The tool description adds no extra semantic detail about query format, escaping, or non-normalization, but the baseline of 3 applies because the schema carries the documentation burden.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the action ('Search'), the resource ('Yahoo video results'), and enumerates the returned fields. It does not explicitly differentiate from sibling video-search tools like bing_videos, google_videos, or duckduckgo_video, but it is unambiguous about the engine and content type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states what the tool does but gives no guidance on when to select this tool over alternatives such as yahoo_search, google_videos, or bing_videos. There is no mention of preferred use cases, exclusions, or fallback conditions, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It adds useful context by mentioning page-based pagination, the output fields, and that data is sourced from Yahoo Tech's server-rendered section pages. It does not discuss edge cases, invalid categories, rate limits, or pagination end behavior, so it is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the essential task in the first sentence. It does not waste words, though 'Yahoo Tech section story stream' and 'Yahoo Tech section's editorial story feed' are slightly redundant.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so the description appropriately names the returned story fields: title, destination URL, category, and thumbnail image. With only two parameters and a simple feed task, the description provides enough context for an agent to call the tool correctly, though examples of valid category values would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers both parameters fully: 'category' is described as a Yahoo Tech section and 'page' as a 1-based page number defaulting to 1. The description reinforces that 'category' selects a section feed and that pagination exists, but it does not add materially new parameter semantics or enumerate valid category values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool returns a Yahoo Tech section editorial story feed and enumerates the fields returned for each story. It is specific enough to differentiate from article-level or home-feed siblings, though it does not explicitly name a sibling to distinguish against.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes the general use case clear: retrieving a Yahoo Tech category/section story feed. However, it does not explain when to prefer this over related siblings like yahoo_tech_home or yahoo_tech_article, nor does it state any exclusions or alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the burden. It discloses the backend (Yelp Android app), credential-free access, and non-business scope, which add transparency beyond the schema. However, it does not describe failure behavior (e.g., invalid address handling) or return format details beyond listing fields.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the core purpose. Every sentence adds value: backend distinction, credential-free fact, and non-business scope. No redundant words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description lists output fields (coordinates, city, state, zip, county), which is helpful. However, it does not explain the exact response shape, possible absence of results, or error handling. Given the tool's simplicity and one parameter, it is adequate but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers the single parameter (address) at 100% with a description. The tool description repeats the term 'free-form address' but adds no new parameter-specific semantics. Baseline 3 is appropriate since schema fully documents the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Geocode a free-form address') and the output (structured location data: coordinates, city, state, zip, county). It also distinguishes from siblings by noting 'via Yelp's real Android app backend' and 'Not business-scoped,' which sets it apart from yelp_business and generic geocoding tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives like geocoding_search or yelp_business. It notes 'Not business-scoped' as a negative scope, but gives no exclusions or alternative tool names. Usage context is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It mentions pagination via 'page of comments' but does not explain how pagination works (e.g., continuation_token returns next page, first page if empty). It does not mention rate limits, authentication requirements, or behavior for videos with no comments. The description is minimal in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, each serving a distinct purpose: stating the action and specifying the return format. It is front-loaded with the key function and contains no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks detail about the response structure (e.g., fields like author, text, likes, reply nesting) and does not mention pagination semantics beyond 'page of comments.' For a comment retrieval tool with no output schema and potentially nested replies, the description is minimally adequate but leaves gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: both parameters are well-described. The description adds 'top-level & replies,' which clarifies the type of comments returned but is already partially implied. This provides minimal added value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Retrieve') and the resource ('video comments (top-level & replies)'). It specifies the scope (for a specific YouTube video) and implies pagination ('Returns a page of comments'). It distinguishes itself from sibling YouTube tools like youtube_video or youtube_search by focusing on comments.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used when 'a specific YouTube video' is known via its ID. However, it does not explicitly state when to prefer this tool over alternatives like youtube_video (which may include comments) or other comment tools. No guidance on when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It states it returns suggestions from a public API, but does not disclose rate limits, caching, or the exact return format. It provides basic transparency but lacks detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only two sentences, front-loaded with the primary action, and contains no superfluous information. Every word serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one required parameter and no output schema, the description is mostly complete. It specifies the source and scope. However, it could mention the return format (e.g., array of strings) for full completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the parameter description 'Suggestion prefix' already clarifies semantics. The tool description adds no new parameter-level information, matching the baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Retrieve' and the resource 'Amazon search suggestions', specifying it returns typeahead keyword suggestions. It distinguishes from sibling suggest tools by naming 'amazon.com' and the typeahead nature.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like `amazon_search` or other suggest tools. The description only explains what the tool does, without context on when it is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description adds context: 'Credential-free public anime data' discloses no auth needed, and 'Returns normalized entries' hints at structure. Does not cover pagination or rate limits, but adequate for a read-only search.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with action ('Search anime'), then details. No redundant words. Well-structured and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters, no output schema, and no annotations, the description explains the return format (titles, scores, etc.) and data source. Missing mention of pagination behavior, but overall adequate for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameters with descriptions. The description adds no parameter-level info beyond what's in the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search anime' and 'Searches anime by free-text query', specifying the verb and resource. It distinguishes from sibling tools like anime_character_search or anime_rankings by indicating general anime search with normalized entries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. Does not mention when not to use or provide exclusions. Siblings are listed but not addressed in description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description indicates a read-only operation but lacks details on pagination, error handling, or response structure. Adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with the core action. No extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool, the description covers purpose and input. Lacks mention of output format but still sufficient given no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all parameters (100%), so baseline is 3. Description does not add additional meaning beyond the schema's existing parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Verb 'Retrieve' and resource 'apps by developer ID' are clearly stated. Distinguishes from sibling tools like appstore_search or appstore_list by specifying a specific developer artist ID input.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as appstore_search or appstore_app. No exclusion criteria or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral disclosure burden. It does state the core behavior ('Returns normalized Booking.com hotel search results'), but it does not explicitly confirm read-only status, mention pagination behavior via the page param, result limits, or explain what 'normalized' means. Adequate but thin for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the primary action. There is minor redundancy: 'Search' appears in the first sentence and 'search results' in the second, and 'Booking.com hotels' is stated twice. Overall it is efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool with full schema coverage, the description is adequate but minimal. It lacks context on pagination (despite the page param), what 'normalized' results contain, and how this tool relates to sibling booking_hotel_detail for follow-up lookups. With no output schema or annotations to compensate, the description carries more weight than it fully addresses.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds only 'destination and date range,' which is largely redundant with the existing schema descriptions for query, checkin, and checkout. It provides no additional meaning for the other four parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Search Booking.com hotels.' It clearly differentiates from sibling tools like booking_flights_search, booking_attractions_search, and booking_hotel_detail by scoping to hotel search results. The mention of 'destination and date range' further clarifies the tool's function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when the tool applies (searching Booking.com hotels by destination and dates), but it names no alternatives or exclusions. An agent must infer when to prefer this over similar tools like expedia_properties_search or airbnb_search, and there is no guidance on following up with booking_hotel_detail.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It describes the fetch and extraction process, including that enrichment-only fields return null, but lacks details on performance, caching, failure modes, or any side effects. This is adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loading the purpose and then detailing what is extracted. It is efficient with no wasted words, though it could be slightly more structured (e.g., bullet points).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description partially explains the output (normalized brand profile with fields like title, colors, logos, etc.). However, it lacks details on error handling, caching behavior, or the exact structure of the response, making it moderately complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so each parameter is documented in the schema. The description adds context about the output (e.g., enrichment fields returning null) but does not significantly enhance understanding of the parameters beyond the schema's descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Retrieve', the resource 'brand data by domain', and the action of fetching homepage and Web App Manifest to extract a normalized brand profile. It distinguishes itself from sibling tools which are focused on specific platforms (e.g., Amazon, Airbnb) by being a general web brand retrieval tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving brand data from a domain but does not explicitly state when to use this tool versus alternatives. There is no exclusionary guidance or mention of when not to use it, leaving the agent to infer from sibling tool names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'normalized global market metrics' but does not disclose specifics like data freshness, rate limits, or whether it's a read-only operation. Minimal behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short, front-loaded sentences with no wasted words. The purpose is immediately clear, achieving high conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no parameters, the description should elaborate on what 'global market metrics' entail (e.g., market cap, volume). Without this, the agent lacks information to interpret the tool's return value, making it incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With zero parameters and schema coverage at 100%, the baseline is 4. The description adds value by describing the output as 'normalized global market metrics,' which provides meaning beyond the empty input schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'global market metrics' from CoinGecko, specifying the resource and action. Among siblings like coingecko_coin and coingecko_markets, this distinguishes itself as a broad snapshot, fulfilling the purpose clarity dimension.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining a global market snapshot but provides no explicit guidance on when to use this tool versus alternatives like coingecko_global_charts or coingecko_markets. Lack of when/when-not guidance reduces clarity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral disclosure burden. It usefully indicates that records are stored in a search index and describes available filters, but it does not state that the operation is read-only, nor does it describe the response format, pagination behavior, or any ordering defaults. This is a moderate but incomplete disclosure for a search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured: it opens with the core purpose, then states the data source, summarizes filter categories, and lists key enums. Each sentence contributes useful information without excessive verbosity, though it could be slightly tighter by avoiding the repetition of enum values already present in the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main capabilities for a 19-parameter search tool, but it omits important contextual details such as the shape of the response, pagination constraints (e.g., page * page_size <= 10000), and how this tool relates to sibling Box Office Mojo dataset tools. It is adequate for basic search usage but leaves notable gaps given the lack of annotations and output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides detailed descriptions for all 19 parameters with 100% coverage. The description adds a high-level grouping of filter dimensions but does not explain parameter semantics beyond what the schema already states. It repeats enum values that are already in the schema, so the added value is minimal.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Search the Box Office Mojo dataset.' It further clarifies the scope ('theatrical box-office records from public Box Office Mojo charts and title pages') and the search-index nature, which distinguishes it from sibling tools like datasets_boxofficemojo_item and datasets_boxofficemojo_facets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage through its focus on search and filtering, but it does not explicitly state when to use this tool versus alternatives such as datasets_boxofficemojo_item or datasets_boxofficemojo_facets. No exclusions or alternative recommendations are given; the context 'stored in a search index' provides limited guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for behavioral disclosure. It states returns 'aggregation buckets' but does not clarify read-only nature, authentication requirements, rate limits, or parameter interaction effects. The enum note linking to search endpoint provides some context but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two concise sentences. The first sentence front-loads the purpose and output, while the second efficiently lists enums. Every word serves a purpose; no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the tool's complexity (15 parameters, no output schema), the description fails to explain the return format of buckets, how filters interact with faceting, or whether the tool supports pagination. Critical details for correct invocation are missing, making it incomplete for an autonomous agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds minimal semantic value—only listing some enums beyond the schema's descriptions. For example, the schema already defines 'sort' enum values; the description merely notes alignment with search endpoint. No extra meaning for most parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('facet'), the resource ('Chrome Web Store dataset'), and the output ('aggregation buckets'). The explicit listing of facet enum values and item type enum further clarifies the tool's scope, distinguishing it from sibling facet tools for other datasets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining aggregation buckets but does not provide explicit when-to-use or when-not-to-use guidance. It fails to differentiate from sibling tools like search or item retrieval, nor does it suggest alternatives for specific needs. The mention of enum matching with the search endpoint is helpful but insufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries full burden. It discloses that coverage varies per city and that a city appears once ranked by at least one family. However, it doesn't mention pagination constraints, rate limits, or whether the operation is read-only (though assumed).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact (4 sentences) and front-loaded with purpose. Each sentence adds meaningful information without fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 14 parameters and no output schema, the description covers the dataset purpose and data coverage but does not explain return values or behavior (e.g., response format). Adequate but not complete for a complex tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline 3. The description adds value by explaining the sort enum values and the dataset's composite nature, but most parameters (e.g., min/max indices) are self-explanatory from their names. No additional semantics beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches the Numbeo cities dataset, explains it's a composite of 7 index families, and defines when a city appears. This distinguishes it from sibling tools like datasets_numbeo_cities_item or datasets_numbeo_cities_facets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for searching/filtering cities but does not explicitly state when to use this tool versus alternatives like datasets_numbeo_cities_facets or other dataset search tools. No when-not or exclusions provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden for disclosing behavior. It adds provenance (discovered from PitchBook's public sitemap) and clarifies advisor types, but does not mention that the operation is read-only, whether there are rate limits, or how results are ordered by default. The sort enum is listed in both the description and schema, so it adds limited additional value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four sentences and generally compact. It front-loads the primary purpose and then adds context. There is minor redundancy (both the first and second sentences start with 'Search/Searches'), but overall it is efficient and free of unnecessary filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 10 parameters and no output schema, the description provides essential domain context and sort options, but does not describe the return format or pagination behavior beyond what the input schema already states. The mention of 'profile catalog' implies result content, but more detail on response structure would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the description does not need to explain parameters. It does provide helpful domain context by defining what an advisor is (service provider — e.g., investment bank, lender), which aids in interpreting the service_type parameter. However, this is supplementary rather than essential.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: searching the PitchBook advisors dataset. It specifies the resource (advisor/service provider profiles) and the action (search), distinguishing it from related tools like datasets_pitchbook_advisors_item and datasets_pitchbook_advisors_facets by describing it as a search over a catalog.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context about the data source (crawled public PitchBook sitemap) and that it searches a catalog, which implies typical usage for finding advisors. However, it does not explicitly state when to use this tool versus alternatives (e.g., datasets_pitchbook_advisors_item for single profiles) or provide exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosing behavior. It notes the output is terms aggregation counts and lists valid facet enums, but it does not describe the response structure, whether filters interact with faceting, or any operational constraints. Adequate but sparse.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose and key enum values. Every word earns its place; no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description is incomplete. It fails to explain the structure of the returned aggregation counts, how filter parameters like q or run_id affect results, or any pagination/limits. A bare-minimum faceting tool would benefit from more detail on output shape and interaction with filters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema provides full parameter descriptions. The description adds no additional parameter semantics beyond repeating the facet enum, which is already in the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'Facet PitchBook investors dataset' and specifies it returns terms aggregation counts. This distinguishes it from sibling item and search tools for the same dataset, and the resource is explicitly named.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for getting aggregated counts rather than individual records or searches, but it does not explicitly state when to prefer this over the sibling search/item tools or provide exclusions. Context is clear but not fully differentiated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool returns distribution counts and uses search filters. It does not mention authentication, rate limits, or side effects, but for a read-only facet this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two clear sentences, front-loading the purpose and providing essential details without extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple facet tool with full schema coverage and no output schema, the description adequately covers the dataset, facet fields, and filter behavior. It could optionally describe the output format but is complete enough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds context by linking parameters to search filters and listing facet enum values, but the schema itself already documents the parameters comprehensively.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool facets the Product Hunt makers dataset and returns distribution counts. It specifies the dataset id and the available facet fields, distinguishing it from search and item retrieval tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when distribution counts are needed rather than items, stating that it honors the same filters as search. However, it does not explicitly provide when-not-to-use guidance or name alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must bear full burden. Only states it 'returns a normalized Discogs label profile' with listed fields. No disclosure of rate limits, data freshness, error behaviors, or whether the operation is safe/mutating. For a read tool, minimal but missing details about pagination or size limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, highly concise. Front-loaded with purpose, lists return fields efficiently. No redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given single parameter, no output schema, and no annotations, the description adequately covers what the tool does and returns. Could be slightly more complete with explanation of 'normalized' or example usage, but sufficient for a simple lookup tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (only one param 'id' with description 'Discogs label id'). Description adds no additional meaning beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Get a Discogs label profile' with explicit verb (Get) and resource (Discogs label profile). Distinguishes from siblings like discogs_label_releases which retrieves releases, not profile. Provides specific return fields: profile text, contact info, parent label, sub-labels.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Mentions 'credential-free', implying no auth needed, which is a usage hint. However, lacks explicit guidance on when to choose this tool over alternatives like discogs_label_releases or discogs_search. No when-not-to-use or context for sibling differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It states 'Returns' and 'public,' which implies a read-only operation and scope. It also makes clear the output is limited to navigation identifiers, avoiding confusion with tools that return odds or markets. It does not cover auth needs, rate limits, or error behavior, but these are less critical for a simple public lookup, so 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loads the main purpose with a clear verb followed by the use case. It is well organized and easy to parse. The last sentence repeats 'public sport and league' from the previous sentence, which is minor redundant that keeps the score below excellent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description does mention the high-level categories returned (sport, league, event navigation identifiers), which helps the agent understand what to expect. It doesn't specify exact field names or how the identifiers work when navigating, and it doesn't explicitly distinguish this tool from many DraftKings siblings. This is adequate but not complete for a tool with no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description for event_id is 'Numeric DraftKings event id,' and the tool description repeats exactly the same language without adding new details. Schema coverage is 100%, so the structure already documents the parameter thoroughly. The description does not add meaning beyond that, hence the baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: it returns public sport, league, and event navigation identifiers for a numeric DraftKings event id, which distinguishes it from odds-focused or market-focused entities. It is not a tautology and gives a specific resource. However, it does not explicitly disambiguate from the closely named 'draftkings_event' tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear use case: 'Use it to associate an event with DraftKings Sportsbook's public sport and league navigation.' This gives the agent a definite context for selecting the tool. It does not include explicit exclusions or name any alternative tools, but no exclusions are needed for such a targeted lookup.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the burden of behavioral disclosure. It implies a read-only operation by describing the public Teams page, but it does not mention response format, pagination, rate limits, or whether auth is required. For a low-risk list endpoint, this is acceptable but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short, mostly front-loaded, and gets to the core behavior quickly. The opening noun phrase restates the tool name somewhat, but the rest of the description is efficient and the allowed values list is useful for enforcement.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter, no-output-schema tool, the description covers enough: what the tool returns, the source page, the league scope, and the valid league values. It leaves the return shape underdescribed, but an agent can correctly select and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents the league parameter with 100% coverage, including the allowed values. The description adds little beyond restating those values, which is fine but not additive.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Returns' and the resource 'teams listed on DraftKings Sportsbook's public Teams page for one league.' It is specific about scope, but it does not explicitly call out sibling tools like draftkings_team or draftkings_leagues, so differentiation relies on the plural 'teams' and 'for one league.'
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: use this tool to get teams for exactly one supported league, with the allowed league values spelled out. It does not state when not to use it or name alternatives for getting a single team or a list of leagues.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral disclosure burden. It indicates the tool returns facets (a read operation), but does not describe input requirements, response structure, or any constraints. This is minimal but not misleading.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: two short sentences with the key action front-loaded. The parenthetical list of facet types adds helpful detail without waste. Every word contributes value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and an opaque input parameter, the description is incomplete for an agent to invoke confidently. It lists facet types but not the response structure or how to build the 'option' payload. Mention of 'Stays search' gives some context but not enough for practical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one parameter 'option' with a vague description 'Property filters payload'. Schema description coverage is 100%, so the baseline is 3. The tool description does not elaborate on how to construct this payload or what values it should contain, so no additional meaning is added.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool returns sort and filter facets for Expedia Stays searches, listing specific facet types. It is distinct from sibling tools like expedia_properties_search, which performs searches rather than returning filter options.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'available for a Stays search' implies the tool is used to retrieve filter options before running a search, but it does not explicitly state when to use it versus alternatives like expedia_properties_search. No when-not-to-use guidance or alternative tool names are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of disclosing behavioral traits. It only says 'Search' and 'Returns normalized results,' which implies read-only behavior but does not explicitly state it. It also omits any mention of prerequisites (e.g., using a location ID), rate limits, error handling, or pagination, leaving the agent underinformed about side effects and operational constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loaded with the main action ('Search Expedia Stays properties'), and contains no redundant information. Every clause adds useful context: the resource, the normalized result, and the key inputs (destination and date range).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with an opaque object parameter and no output schema, the description is incomplete. It does not explain the expected structure of the 'option' payload, how to specify the destination (city name vs. location ID), what 'normalized' means in terms of response format, whether pagination or sorting is supported, or any integration with sibling tools like expedia_locations_search or expedia_properties_filters. The agent would likely need to probe or guess to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema describes the only parameter 'option' as 'Property search payload,' which is vague. The description adds value by specifying that the search is for a free-text destination and date range, giving the agent some idea of what to include in the payload. However, it doesn't detail the exact structure of the option object or mention other possible fields (e.g., number of guests, filters), so parameter meaning is only partially clarified.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Search Expedia Stays properties' with a specific verb and resource, and clarifies that it returns search results for a free-text destination and date range. This clearly distinguishes it from sibling tools like expedia_properties_detail, expedia_properties_filters, and expedia_properties_reviews, which serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: when a search for hotel properties is needed based on a free-text destination and date range. It does not explicitly mention alternatives or exclusions, but the implied usage is strong and unambiguous given the sibling tool names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description discloses the rate limit (10 requests per minute for unauthenticated users) and implies read-only behavior. However, it does not mention authentication effects, pagination behavior, or response structure beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences, front-loading the core purpose and adding a critical rate limit note. Every sentence adds value, no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description is too brief for a search tool with 5 parameters. It lacks information on default results, sorting options (no enum values), pagination defaults, and what the response contains. The rate limit is helpful but insufficient for an agent to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% parameter description coverage, so the description adds no additional meaning beyond what is in the schema. No examples or syntax hints are provided for the query parameter or other fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches public GitHub repositories and specifies the use case of market/competitive discovery, effectively distinguishing it from sibling tools like github_search_users or github_repo.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for searching public repos but does not explicitly guide when to use this tool versus alternatives like github_search_users or github_org_repos. The rate limit note provides some context but no direct comparison.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations present, so description carries burden. It mentions conditional behavior ('when Google Finance has statement data') and output type, but lacks disclosure on mutation, rate limits, or authentication. Minimal transparency beyond core function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-loading purpose and output type with no superfluous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given single parameter and no output schema, description covers output format and condition. Could be more complete by specifying which financial statements (income, balance sheet) are included, but adequate for basic usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and description adds no additional meaning beyond 'Quote identifier such as AAPL:NASDAQ' already in schema. Baseline score 3 applicable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verb 'returns' and resource 'normalized annual and quarterly financial rows', clearly indicating it retrieves financial statements for a quote. It distinguishes from siblings like google_finance_quote which returns current quote data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage when financial statements are needed, but no explicit guidance on when to use this vs alternatives, nor any exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It indicates a read operation ('returns...') and specifies output as 'normalized related instruments'. However, it does not mention any potential side effects, rate limits, or the exact nature of 'normalized'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief (two sentences) and front-loaded with the tool's purpose. The first sentence could be merged for conciseness, but overall it is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description is mostly adequate. However, it lacks details on the output format (e.g., array of tickers) which would aid completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the only parameter 'quote' has a clear schema description. The tool description adds no additional information beyond what the schema already provides, meeting the baseline for full coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'normalized related instruments' for a quote, using 'Google Finance' as the source. This distinguishes it from siblings like google_finance_quote (which returns the quote itself) and other tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus alternatives, such as google_finance_search or google_finance_ticker. No rationale or usage context is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries the full burden. It mentions 'normalized offers' but does not disclose any behavioral traits like performance, error handling, or response structure. The description is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, 18 words, front-loaded with the verb and resource. No unnecessary information, every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple lookup tool with well-described parameters. However, without an output schema, the description could elaborate on what 'normalized offers' entails. Still, it covers the essential context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds value by clarifying that the id is 'raw' and the countries are 'comma-separated two-letter codes'. It also introduces the concept of 'normalized offers' which is beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get', the resource 'JustWatch episode offers', and the exact input requirements (raw episode id, one to five country codes). This distinguishes it from siblings like justwatch_episode_by_id or justwatch_title_offers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this vs alternatives such as justwatch_episode_by_id or justwatch_title_offers. It does not provide context for when this tool is appropriate or not.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It describes output (candlesticks, grouped by market) but does not disclose potential behavioral traits like rate limits, data freshness, error handling, or pagination. The credential-free aspect is noted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys key information: what is returned, grouping, single event scope, and data source. It is concise without unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 6 parameters and no output schema, the description is adequate but not complete. It explains the basic output but does not cover return format, edge cases, or how to interpret the data. For a complex financial data tool, more context would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, so the schema already explains parameters like event_ticker and period_interval. The description adds no new parameter details beyond the schema, meeting the baseline but not exceeding it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns normalized Kalshi candlesticks grouped by market for one event, with specific context of being credential-free public data. This distinguishes it from sibling tools like kalshi_market_history and kalshi_historical_markets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool over alternatives. It mentions 'credential-free' which implies no authentication needed, but lacks guidance on when not to use it or specific trade-offs compared to other historical data tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Mentions 'credential-free public' but no annotations exist. Does not disclose rate limits, behavior for >25 tickers, or whether returns are paginated. Insufficient for a multi-market data tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences front-load key info: batch, candlesticks, up to 25, credential-free. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Lacks output schema, but describes what is returned (candlesticks). Covers constraint (25 tickers) and auth context. Minor gaps: no pagination info or response structure details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with descriptions. The description adds 'up to 25 market tickers' and 'normalized candlesticks' which provide context beyond schema, but baseline is 3 since schema already documents parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it returns normalized Kalshi candlesticks for batch market history up to 25 tickers. Distinct from siblings like kalshi_market_history (single market) and kalshi_historical_market_history (historical single market).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied ('batch' vs 'market' singular) but no explicit guidance on when to choose this over sibling tools like kalshi_market_history or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that data is from public pages, and that the endpoint fails on authenticated responses or Cloudflare challenges. However, it lacks details on rate limits, pagination behavior, or what 'normalized' entails, leaving gaps in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loading the core purpose and adding a valuable behavioral note. Every word serves a purpose, with no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity and lack of output schema, the description covers data source, failure modes, and basic functionality. However, it omits pagination details (e.g., how to get next page) and the meaning of 'normalized,' which are useful for an agent. Still, it is fairly complete for a simple list endpoint.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for both parameters (limit and topic), so baseline is 3. The description adds no additional meaning beyond what the schema already provides (e.g., limit's default/max, topic's slug format).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns 'normalized Metaculus question rows' from public data, distinguishing it from sibling tools like metaculus_question (singular) which likely fetches a single question. The verb 'returns' and resource 'Metaculus questions' are specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions it uses 'credential-free public page data' and 'fails closed on authenticated API responses,' implying it is for public-only access. However, it does not explicitly guide when to choose this tool over alternatives like metaculus_category_questions or metaculus_project_questions, nor does it provide exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose safety or side-effect behavior (e.g., that it is read-only, error conditions, or data freshness). It only lists the output fields, leaving the agent to infer that it's a safe read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the action, and no redundant information. Every word contributes to describing the tool's output.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter read tool, the description covers the purpose, the input from the schema, and the expected output contents. It doesn't mention error handling or data limitations, but given the low complexity, this is acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides full coverage of the single 'id' parameter with a clear description ('Numeric MLB game id'), and the tool description adds no additional parameter-specific context. Baseline of 3 applies for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Get' and clearly identifies the resource ('MLB game feed') and its scope (status, teams, score, innings, probable pitchers, decisions, team box-score totals). This differentiates it from sibling tools like mlb_game_boxscore and mlb_game_play_by_play.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies its usage (when you need a compact game feed) and lists the included data, but does not explicitly state when to use this tool over alternatives like mlb_game_boxscore or mlb_game_play_by_play, nor does it mention exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only adds 'ranked' and 'across both leagues', but omits details on sorting order, pagination, auth requirements, or output structure. This is minimal and insufficient for a tool without annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences with no redundancy. The first sentence front-loads the purpose, the second clarifies output scope, and the third fills a gap in the schema. Each sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description must explain return values. 'Returns ranked MLB season stat splits across both leagues' is vague about output structure and what stats are included. While parameters are clear, the missing details on response format and ranking criteria leave significant ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers all parameters but the 'group' description is terse ('Stat group'). The description adds crucial enum values ('hitting', 'pitching', 'fielding') that are absent from the schema, significantly improving parameter understanding. Other parameters are well-described in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the resource: 'Get ranked MLB league statistics' and specifies it returns 'ranked MLB season stat splits across both leagues', distinguishing it from team/player-specific tools like mlb_team_stats and mlb_player_stats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for league-level stats by mentioning 'both leagues' and the group enum, but it does not explicitly state when to use this tool versus siblings or provide exclusions. The context is clear but lacks explicit alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It merely states what data is returned and does not disclose any behavioral traits such as rate limits, error handling, data source, or whether it covers active/retired players. There is no explicit read-only declaration beyond the verb 'Get'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary action and followed by a concise list of return fields. No unnecessary words or repetition, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter lookup with no output schema, the description adequately enumerates the key return categories. It is reasonably complete but omits any mention of edge cases (e.g., invalid ID) or whether all historical players are included, which prevents a perfect score.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% coverage for the single parameter 'id' with its description 'Numeric MLB player id'. The tool description does not add any additional meaning about the parameter, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with the verb 'Get' and resource 'MLB player', distinctly listing the returned data (identity, bio, position, handedness, active status, current team). This separates it from siblings like mlb_player_stats and mlb_team_roster, which focus on stats and rosters respectively.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied but not explicit. The description suggests this tool is for biographical/identity info, but it does not directly state when to prefer it over alternatives like mlb_player_stats or mlb_team_roster. No exclusions or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility. It mentions the tool returns six indices and supports both current and historical snapshots. However, it does not disclose ordering, pagination, rate limits, or data freshness beyond 'continuously-updated'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences with no fluff. First sentence states action, second details output, third clarifies accessibility. Each sentence earns its place. Front-loaded with the verb 'Get'.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of many sibling tools, the description lacks guidance on when to choose this ranking tool vs city-specific or country-specific tools. Also, without an output schema, a brief description of the ranking structure (e.g., list of cities with scores) would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds context by clarifying that scope defaults to 'current' and period is required for historical, which matches the schema. It also enumerates the returned indices, adding value beyond parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves the global Numbeo cost-of-living city ranking and lists the indices returned. It also mentions current vs historical scope. However, it does not explicitly differentiate from sibling tools like numbeo_cost_of_living_country or numbeo_indices_rankings, though 'city ranking' implies broad comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description notes that data is credential-free and public, suggesting no authentication. It implies usage for getting global city rankings but does not explicitly state when to use this tool over siblings (e.g., for city-level vs country-level) or provide when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the burden is on the description. It states the tool is credential-free and returns specific fields, but does not disclose idempotency, error behavior, or any rate limits. Adequate for a read-only tool but could be more thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, then a brief param explanation and auth note. No wasted words; every sentence is informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description enumerates the returned fields (title, publisher, etc.), which is highly informative. It also notes the tool is public and explains parameter effects. Complete for a retrieval tool with 3 parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. Description adds value by explaining that 'cc' selects region/currency and 'l' selects language, beyond the schema descriptions. This helps agents choose parameter values appropriately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it retrieves PlayStation Store details for a concept/game hub and lists the returned fields. It distinguishes from siblings by focusing on a concept (aggregating editions) rather than a single product, but does not explicitly contrast with playstation_product or playstation_page.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides no guidance on when to use this tool versus its siblings (e.g., playstation_product for single product details, playstation_search for searching). Mentions credential-free public access but lacks explicit when-to-use/alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states it returns 'normalized tag rows'. It does not mention read-only nature, rate limits, authentication needs, or error handling for invalid ids.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. The core action is front-loaded. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter list tool with no output schema or annotations, the description covers the essential what and what it returns. Could mention return format or behavior for missing ids, but not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the description adds no extra semantic detail beyond the schema's 'Polymarket event id'. The phrase 'one Polymarket event id' merely reinforces, not enhances.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description explicitly states 'List tags for a Polymarket event' using a specific verb and resource. It clearly distinguishes from siblings like polymarket_market_tags by specifying 'event tags' versus 'market tags'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage: call when you have a Polymarket event id and need its tags. No explicit guidance on when to use vs alternatives like polymarket_event_detail or polymarket_market_tags, nor when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It describes a read operation returning a row from JSON but lacks detail on side effects, data freshness, or authentication. The information is minimal for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, each adding value: the first states the action, the second specifies the return type and input identifier. No waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description conveys essential information. It could be improved by describing the output structure, but it is still sufficient for a agent to understand its use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter 'condition_id' adequately described. The description echoes this parameter without adding new meaning, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get', the resource 'Polymarket rewards market', and specifies that it returns one row by market condition id. It distinguishes from sibling 'polymarket_rewards_markets' (plural) which likely returns multiple rows.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when a specific condition_id is known but does not provide explicit guidance on when to use this tool versus other Polymarket tools or when not to use it. No alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions data source and normalization but fails to explain pagination semantics, data freshness, rate limits, or authorization needs. The cursor parameter hints at pagination, but the description does not elaborate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the main purpose and efficiently lists enum values. While it contains some redundancy (e.g., 'Rewards market sort' could be omitted), it remains clear and reasonably concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description adequately covers the tool's purpose and parameter values but lacks details on response structure, error handling, and pagination behavior. It meets the minimum for a moderately complex tool but is not fully comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, setting a baseline of 3. The description adds value by explicitly listing the accepted values for order_by, position, and tag_slug enums, which goes beyond the schema's generic descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with 'List Polymarket rewards markets,' providing a clear verb+resource combination. It further specifies that it returns 'normalized public rewards-market rows used by Polymarket's /rewards page,' distinguishing it from sibling tools like polymarket_rewards_market (singular) and other polymarket listing tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for listing rewards markets via the /rewards page but does not explicitly state when to use this tool over alternatives or provide exclusion criteria. No guidance on prerequisites or non-use cases is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It adds useful behavioral context by disclosing the 503/Retry-After throttling behavior and clarifying that it returns normalized public entries. It does not explicitly state read-only nature, but 'search' strongly implies it.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences, front-loaded with the core purpose. Every sentence adds value: purpose, scope/return type, and error handling. No fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the schema covers all parameters and the description addresses error handling and return normalization, the tool is adequately explained for a search operation. However, it omits any discussion of pagination behavior or how results are ordered, which could be helpful for a 6-parameter tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds no parameter-specific meaning beyond what the schema already provides; it does not elaborate on 'q', 'sort', 'time', 'after', 'limit', or 'subreddit'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search Reddit posts' with a specific verb and resource, and adds scope via 'public Reddit content' and 'normalized public post entries'. However, it does not differentiate from sibling tools like reddit_subreddit_posts or reddit_domain_posts, which are also search-like tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, no exclusions, and no prerequisites. It only implies usage for searching Reddit posts, which is minimal guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It discloses that subscriber counts, icons, and banners are omitted due to anonymous page limitations, and it explains the 503 Retry-After throttling behavior, adding meaningful context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the purpose in the first sentence. The second sentence is somewhat redundant with the first, but the overall length is appropriate and no information is wasted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, so the description is responsible for explaining return values. It mentions 'public metadata' and 'sample posts' but does not enumerate which metadata fields are returned, leaving a gap for agents expecting specific fields. The throttling guidance partially compensates.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully covers both parameters: subreddit includes format guidance and limit includes defaults and clamping. The description adds no parameter-specific details, so with high schema coverage the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Reddit subreddit metadata, using a specific verb and resource. It also notes it returns sample posts, which somewhat distinguishes it from sibling tools focused on comments or posts, though no alternatives are named explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context about what the tool returns and its anonymous-access limitations, but it does not explicitly state when to choose this tool over siblings like reddit_subreddit_posts or reddit_subreddit_comments. Usage is implied rather than directly guided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the tool's search capabilities and free access but omits important behavioral details such as pagination limits, result count per page, rate limits, or what happens with no results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficient with two sentences, but the first two sentences are somewhat redundant (both state full-text search across EDGAR filings). The third sentence about free access is valuable. Could be slightly more concise by merging the first two sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description provides core semantics but lacks details on return structure, pagination behavior, and example usage. For a tool with 5 parameters, the description is informative but not fully complete for an agent to use without additional exploration.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds context that parameters are for filtering (form, date) and pagination, but does not add significant meaning beyond what the schema already provides. The mention of 'supports quoted phrases' for q is already in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it performs full-text search on SEC EDGAR filings, specifies the ability to filter by form and date with pagination, and highlights that it's credential-free and free where others gate behind paywalls, effectively distinguishing it from other SEC tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for full-text search of EDGAR filings but does not explicitly provide when-to-use or when-not-to-use guidance relative to sibling tools like sec_company_search or sec_filing. No alternatives or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full disclosure burden. It is transparent about pagination ('Returns one page'), the shape of reviews, and the aggregation details, which is useful for a read-only fetch. However, it omits broader behavioral traits such as rate limits, output size caveats, or how to correctly advance pages beyond the schema's 'page' description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and places the core behavior first, followed by the return payload and then the product_id clarification. It is dense but each sentence contributes meaningful information; minor gains could be had by simplifying the last sentence's phrasing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter read-only tool with no output schema, the description provides needed eligibility: the required parameter, the optional page parameter, and a full enumeration of return content including review fields and the rating rollup. It does not spell out the exact JSON structure, but an agent can call this tool with reasonable confidence.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema already documents both parameters at 100% coverage. The description adds real value by explaining that product_id is the Sephora productGroupID and that it equals the product_group_id returned by the /sephora/product endpoint, with a concrete example (P420652). This clarifies cross-tool provenance and reduces agent guesswork.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Returns one page of a Sephora product's full customer reviews' and enumerates the specific review fields plus the rating rollup, making the tool's purpose evident and distinct from neighboring Sephora tools at a glance. It loses a point because it never explicitly names sister tools like sephora_product_questions or sephora_product to contrast against.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the correct use case: when you need a Sephora product's customer reviews and rating summary. It does not explicitly state when to avoid this tool, which alternatives to prefer, or any search/filter exclusions, leaving usage guidance implicit rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description notes that the data comes from 'credential-free public JSON' (no authentication needed) and that an empty incidents list is valid before kickoff. However, it does not mention rate limits, error handling for invalid IDs, or data freshness expectations. Without annotations, more detail would be beneficial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at three sentences, front-loaded with the core purpose, and every sentence adds value (resource, contents, and special case). No unnecessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple one-parameter tool with no output schema, the description adequately covers the purpose, type of data returned, source, and a valid edge case. It does not cover error conditions or return structure, but these are minor gaps for a tool of this simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (one parameter with description 'Numeric SofaScore event (match) id'). The tool description adds no further detail about the parameter beyond what the schema already provides, so baseline score 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a match's incidents including goals, cards, substitutions, and period timeline from SofaScore's public JSON. It explicitly specifies the resource (match incidents) and distinguishes itself from siblings like sofascore_event_lineups or sofascore_event_statistics by focusing on incidents only.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives among the many SofaScore siblings (e.g., sofascore_event, sofascore_event_h2h). The agent is left to infer based on the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral disclosure burden. It does add value beyond the name: it says the data is public, sourced from SoundCloud's own JSON API, and that the full track list is returned. However, it does not disclose rate limits, authentication requirements, potential truncation/pagination for very large playlists, or failure modes, which a retrieval tool of this kind should hint at.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. The action and resource are front-loaded, the specific return fields follow, and the source/accessibility note ('Public data sourced from SoundCloud's own JSON API') earns its place by conveying authenticity and access assumptions. Efficient and well ordered.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no output schema, the description is close to complete: it names the input URL and enumerates the return content (owner, counts, track list with title/artwork/playback/likes). The only gaps are minor operational details like rate limits or whether very large playlists are paginated, which are not critical given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3 and the description is not required to compensate. The tool description does reinforce that the URL is for a playlist or album, matching the schema's 'playlist/album URL (a playlist's permalink_url)' definition, but it adds no additional syntax, format acceptable, or example. The schema already does the work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource ('Get a SoundCloud playlist or album's detail') and specifies the return payload: metadata plus full track list with owner, likes/reposts counts, and per-track title, artwork, playback/likes counts. It implicitly distinguishes itself from sibling tools like soundcloud_track and soundcloud_search by scoping to playlists/albums, but it never explicitly names an alternative or contrasts scope, so it doesn't reach a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No tool contains explicit when-to-use or when-not-to-use guidance, and it does not reference alternatives such as soundcloud_track, soundcloud_user_tracks, or soundcloud_search. The intended trigger is implied: you use this when you already have a playlist or album permalink URL, which is carried by the schema rather than the description. This is adequate but leaves the agent to infer when the sibling lookup tools are the right choice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does add real context by saying the data is "Public data sourced from SoundCloud's own JSON API", which signals no auth needed and a first-party source, and it scopes to a single profile. However, it discloses nothing about failure behavior for invalid/deleted profile URLs, rate limits, or staleness of data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three tight sentences each earn their place: the top-loaded verb and object, then the useful field list, then a brief sourcing note. There is no filler or redundant restating of the name or schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Because there is no output schema, the description's explicit list of returned fields is valuable and partially compensates. That said, the description omits any notes on malformed URL inputs, missing profiles, or how to form the expected URL beyond "full" — a moderate gap for a tool with a single input parameter.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline of 3 applies. The description reinforces that only a profile URL qualifies (as opposed to a track or playlist URL), but it adds no extra format requirements, examples, or validation detail beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: "Get a SoundCloud user/artist profile", and it enumerates the concrete return fields (bio, avatar, counts, verified status). The scope of "one profile" clearly distinguishes this from sibling tools like soundcloud_track, soundcloud_playlist, soundcloud_user_tracks, and soundcloud_search without needing to open their schemas.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: when you already have a full profile URL and want profile-level stats, you call this. However, it does not explicitly state when not to use it, nor does it name alternatives such as soundcloud_search for finding profiles without a URL, or soundcloud_user_tracks for seeing a user's tracks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must cover behavior. It describes a read operation (retrieve) and mentions the internal source (Pathfinder response), but does not explicitly state idempotency or side-effect-free nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with verb, no wasted words. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Describes return value (playlist metadata and items) and how to specify the playlist. Could be more specific about the relationship to search tools, but sufficient for a read operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are already well-described. The description adds the option of using either uri or id and the default behavior, but does not significantly enhance parameter understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves playlist details and mentions returning normalized metadata and items. It implies a specific playlist retrieval but does not explicitly differentiate from sibling tools like spotify_playlists_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides guidance on providing uri or id and mentions a default. However, no explicit when-to-use vs alternatives or prerequisites are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden. It discloses default enrichment behavior, the option to pass enrich=false, and that it uses a credential-free public JSON API. This adds meaningful context about what happens under different parameter states.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact at four sentences, with key information front-loaded. Minor redundancy exists between the first two sentences, but overall it is efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema and no annotations, the description covers what the tool returns, parameter effects, and public access. The omitted details about 'l' and 'cc' formats are adequately covered in the schema. The description is sufficiently complete for a straightforward chart retrieval.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining the enrich parameter's default behavior and the batch lookup mechanism, going beyond the schema's simple 'Attach game name and review summary' description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies the tool gets 'Steam's weekly most-played games chart' and lists the data fields (rank, appid, previous-week rank, peak players). It is clear and specific, though it does not explicitly differentiate from sibling tools like steam_charts_concurrent or steam_charts_top_releases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions the enrich parameter behavior but provides no guidance on when to use this tool versus other Steam chart tools. No alternatives or exclusions are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool is credential-free and public, which is useful. However, it does not mention rate limits, idempotency, or caching behavior. For a simple read tool, the disclosure is adequate but could be richer.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the action verb 'Get', and every word serves a purpose. It is highly concise with zero redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (two optional params) and no output schema, the description provides a solid understanding of what is returned (featured capsules, per-platform lists, spotlight, discount/price). It also clarifies the output format as JSON. Only minor improvement could be mentioning if the call is read-only.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (both params fully described). The description adds 'region' context but does not enhance meaning beyond what the schema already provides (language code and country code). Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as retrieving Steam store featured capsules, with specific mention of per-platform featured lists and spotlight capsules. However, it does not differentiate from the sibling tool 'steam_featured_categories', which could confuse an AI agent about which tool to use for featured content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for fetching featured capsules without authentication, but does not provide explicit guidance on when to use this tool versus alternatives like 'steam_featured_categories' or other Steam tools. No when-not-to-use or exclusion criteria are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the burden. It discloses that the post is 'public' and lists the returned data, which is useful. However, it does not describe error behavior, authentication needs, rate limits, or any other behavioral traits. This is adequate for a simple read operation but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact, with two sentences of 18 and 9 words. It is front-loaded with the verb and concise, with every sentence contributing necessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 2-parameter retrieval tool with no output schema, the description sufficiently covers what the tool does and what it returns. It lacks usage guidelines and edge-case behavior, but these are not critical for a straightforward retrieval. The completeness is good but not exhaustive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for both parameters, explaining 'Threads username' and 'Threads post code'. The description adds nothing beyond this, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Retrieve' with a clear resource 'public Threads post' and lists the exact return fields (text, author, canonical URL, preview image). This distinguishes it well from sibling tools like threads_post_replies and threads_profile_posts, which have different scopes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of exclusions, prerequisites, or named sibling tools. The description only states what the tool does, not when to choose it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for behavioral disclosure. It lacks information on rate limits, data freshness, authentication, pagination (though limits to top 100), or what happens on errors. The only extra behavioral hint is that revenue figures are verified through payment providers.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with zero waste. It front-loads the core purpose and crisply adds the data verification note. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list retrieval with one optional parameter and no output schema, the description covers the essential: what it returns (top 100, ranked by metric, verified data). It does not specify output format, but given the simplicity, it is nearly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning beyond the schema: it states the default value for 'metric' ('mrr') and implies it's a ranking metric. With 100% schema coverage and the description providing default info, it adequately compensates for the low parameter count.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'TrustMRR revenue leaderboard.' It specifies the scope: top 100 startups ranked by a selected metric. This distinguishes it from sibling tools like trustmrr_startup (single startup) or trustmrr_search (search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus other TrustMRR tools. It does not mention context, prerequisites, or alternatives. The user must infer usage from the name and purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It only states the tool returns categories grouped by top-level and implies public access, but provides no details on idempotency, rate limits, or other behavioral traits. The description is minimal beyond the function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exceptionally concise, with two short sentences. Every word serves a purpose, and there is no redundancy or unnecessary information. It is front-loaded with the action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, no output schema, low complexity), the description adequately states what is returned. However, it could improve by hinting at the structure of the returned data (e.g., whether it's a flat list or JSON object). The omission is minor but prevents a perfect score.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema coverage is 100%. The description does not need to add parameter meaning, but it does add context ('public', 'grouped by top-level'), which is acceptable. A score of 4 is baseline for no parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool retrieves Trustpilot categories, specifically 'the Trustpilot public category index grouped by top-level category,' using a clear verb-resource pair. This distinguishes it from siblings like trustpilot_category (which likely returns a specific category) and trustpilot_category_search (which searches categories).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, it does not mention that trustpilot_category should be used for a single category's details or trustpilot_category_search for searching. The description lacks explicit context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the behavioral burden, and it does add one useful signal: 'Public data sourced from Twitch's own GraphQL API,' implying no private data or auth constraints. It doesn't go further to mention rate limits, error cases, or whether the order/pagination is handled, leaving some behavior unexplained.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core action and resource, and every clause contributes value—roster contents, live status/viewer count, team metadata, and data source. There is no redundant or filler phrasing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with a single parameter and no output schema, the description covers the important return fields and source attributes. It doesn't mention error conditions or pagination, but that is a minor gap given the simple lookup nature of this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers the only parameter with a clear description (Twitch team slug from twitch.tv/team/{slug}), so the description adds no extra meaning for parameters. With 100% schema description coverage, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb and resource ('Get a Twitch team's roster') and lists the concrete output contents (member roster, live status, viewer count, team metadata), which clearly differentiates it from other Twitch tools like twitch_streams or twitch_channel. However, it does not explicitly name or contrast a sibling alternative, so it loses the point for explicit differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is easy to infer from 'Get a Twitch team's roster,' which implies you should call this when you need team membership or live-status data for a Twitch team. There is no explicit guidance about when NOT to use it or which sibling to prefer, so usage context is only implied rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the burden of behavioral disclosure. It usefully discloses that the data is public, sourced from Twitch's GraphQL API, and sorted by current viewers. However, it does not disclose the output shape, pagination behavior, or any details about the returned games/categories, leaving some behavior opaque.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and efficient: two meaningful sentences. It front-loads the core purpose, adds the key ranking detail in the second sentence, and closes with a useful provenance note about the data source. Every sentence earns its place with no waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, single-optional-parameter read-only endpoint with no output schema, the description covers the core behavior: what is returned, how it is ranked, and that it is public data. It stops slightly short of complete because it does not mention the general output fields an agent might expect, but this is a minor gap given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Semantic coverage of the input schema is 100%; the only parameter, 'limit', already has a clear description including default and max. The tool description itself adds no information about this parameter, so a baseline score of 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the operation ('Get Twitch's top games/categories') and the resource (top games/categories sitewide), with a specific ranking metric. It is clear and distinct for the most part, but it does not explicitly differentiate from sibling tools like twitch_streams or twitch_search, so it lacks the direct comparative distinction that would merit a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly communicates when to use it: when site-wide top Twitch games/categories by current viewers are needed. However, it does not explicitly state when not to use it, does not mention prerequisites, and does not point to alternatives among the many Twitch sibling tools, so the usage guidance is only implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It reveals authentication requirement (JWT), return format (buckets), and timezone (UTC). However, it omits potential rate limits, pagination, or limits on date range. Adequate but not comprehensive for a read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, first states purpose, second adds essential details about return type and timezone. No filler or repetition. Front-loaded effectively.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description adequately implies return type (buckets). Covers authentication and timezone. Missing details on result limits or pagination, but overall sufficient for a simple timeseries query tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all 5 parameters (100% coverage). Description adds context about chart rendering and UTC, but does not explain individual parameter semantics beyond schema. Baseline of 3 is appropriate as description adds marginal value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb ('Get'), resource ('current user's usage timeseries'), and return type ('JWT-authenticated request and credit consumption buckets for chart rendering'). It distinguishes from siblings like usage_overview and usage_endpoints by specifying timeseries data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives like usage_endpoints or usage_overview. Only implicit hint 'for chart rendering' suggests a use case, but no exclusion criteria or context for selecting this over other usage tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It describes the tool as retrieving public data, which implies a read-only operation, but it does not mention any potential side effects, authentication requirements, rate limits, or what happens if the username is invalid. The minimal behavioral information earns a score of 2.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of two short sentences that immediately state the tool's action and what it returns. Every word serves a purpose without redundancy. The structure is front-loaded with the verb, making the tool's function immediately clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one required parameter, no output schema, no nested objects), the description provides adequate context: it retrieves a profile and returns public details. However, it could be more complete by explicitly stating that only public profiles are accessible and what happens in error cases (e.g., username not found). The description is nearly complete for the tool's complexity, earning a score of 4.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage for the single parameter 'username' is 100%, with the description already providing 'X username' in the schema. The tool description adds 'Returns public profile details for an X username', which reinforces the parameter's purpose but does not add new semantic meaning beyond the schema. The description's mention of return content (visible counts, profile media) is about the output, not the parameter itself. A baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Retrieve an X profile' and specifies that it returns public profile details including visible counts and profile media. The verb-resource combination is precise and distinguishes this tool from sibling tools like x_post or x_profile_posts, which deal with different aspects of X.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. While the tool's purpose is clear, the lack of usage context (e.g., when to choose this over other social media profile tools) leaves room for ambiguity. A score of 3 is appropriate as it meets the minimum viable standard but lacks explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden and does add useful behavior context: it says the feed is sourced from Yahoo Autos's server-rendered section pages and uses page-based pagination. It does not describe behavior for invalid categories, missing pages, or rate/limit issues, but the basic read-only feed behavior is visible.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded: it states the purpose, the returned fields, pagination, and data source in three short sentences. The first sentence 'Yahoo Autos section story stream' is a bit redundant with the second, but the structure remains efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity tool with only two parameters, the description conveys the return fields, pagination, and data source. It is not fully complete because it does not tell the agent what valid category values look like, and there is no output schema to fill that gap or provide examples.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds little value for parameters: the required category parameter remains vaguely described as 'Yahoo Autos section' with no allowed values or examples, and page is only minimally covered by the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: it 'Returns a Yahoo Autos section's editorial story feed' and names the payload fields (title, destination URL, category, thumbnail image). This makes the tool clearly distinct from siblings like yahoo_autos_article and yahoo_autos_home without opening their schemas.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied: the tool is for section-level editorial feeds with page-based pagination. However, there is no explicit when-to-use or when-not-to-use guidance, and no alternative comparison such as 'for the Yahoo Autos home feed use yahoo_autos_home instead.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the behavioral disclosure burden. It does well by stating the output shape, page-based pagination behavior, and the fact that content is sourced from Yahoo's server-rendered section pages. It does not mention auth or rate limits, but the read-only feed nature is strongly and clearly implied.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loads what the tool returns before stating its source. There is minor redundancy in 'Yahoo Entertainment section story stream followed by a return. That repetition is minor and not worth penalizing a.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is no output schema, the description usefully enumerates the returned fields and note pagination. It does not explain accepted category values, default page counts, or behavior for invalid or missing sections, which leaves some uncertainty for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema description coverage is 100%, so the baseline is 3. The description adds little beyond the schema: 'section' maps to the category parameter, and 'page-based pagination' mirrors the page parameter, but it does not enumerate valid category values or explain page size behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific operation and resource: it returns a Yahoo Entertainment section's editorial story feed, including title, destination URL, category, and thumbnail image. It is clear and distinguishable from article/home tools by the repeated 'section' focus, though it does not explicitly name sibling alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is implied by 'Returns a Yahoo Entertainment section's editorial story feed' and the required category parameter. However, there is no explicit guidance about when to choose this over related tools like yahoo_entertainment_home or yahoo_entertainment_article, leaving the selection partly to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full burden. It mentions batch and symbol limit but omits behavioral traits like rate limits, error handling, output format, or data description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise at one sentence. It front-loads the batch capability, but the single-sentence structure lacks detail expected for a tool with a nested object parameter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the nested request object and no output schema, the description is incomplete. It does not explain the request structure, return format, or data contents, leaving significant gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The sole parameter 'request' is a nested object with only a minimal description. The schema coverage is 100% but the description adds no structure or example, leaving the agent to guess the required fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool downloads batch historical prices from Yahoo Finance for up to 25 symbols. It distinctively contrasts with single-symbol tools like yahoo_finance_ticker_history among siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies batch usage by specifying 'up to 25 symbols', suggesting use when multiple symbols are needed. However, it lacks explicit guidance on when not to use or alternatives for single symbols.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full weight. It mentions returns normalized items and continuation token but doesn't disclose permissions, rate limits, or side effects. Minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no redundancy. Front-loaded with action and resource. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool with 2 well-documented parameters, the description is largely sufficient. Lacks return format details but provides core functionality and pagination hint.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers both parameters fully, with detailed descriptions for 'id' and 'continuation_token'. Description adds no extra meaning beyond restating the token's existence. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it retrieves videos from a channel's Videos tab, distinguishing it from siblings like youtube_channel_shorts and youtube_channel_playlists. Verb and resource are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this vs. alternatives, but the purpose is implied. Lacks exclusions or alternative suggestions for other channel content types.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the burden. It mentions returning 'normalized videos' but does not disclose rate limits, authorization, error handling, or what happens when a tag has no results. The behavioral context is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact, with two sentences that front-load the core purpose and then add parameter usage details. No extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description does not specify the return format or fields of the normalized videos. It lacks details on pagination limits and error scenarios, leaving the agent underinformed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds value by explaining how to use the 'type' and 'continuation_token' parameters beyond their schema descriptions, such as 'Set type=shorts to use the Shorts tab'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Retrieve YouTube videos by tag', using a specific verb and resource. It distinguishes from sibling YouTube tools (e.g., youtube_search, youtube_video) by focusing exclusively on tag-based retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides guidance on using the 'type' and 'continuation_token' parameters, but does not explicitly compare to alternative tools or specify when to choose this over others like youtube_search.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It lists returned data but lacks details on error handling, rate limits, authentication, or any side effects. It does not contradict annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences that succinctly convey purpose and returned content. Every word is necessary, no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but the description lists key return data (pricing, availability, etc.). However, lacks structure details. Adequate for a simple retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already describes parameters adequately. The description adds no extra meaning beyond listing output content, thus baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Retrieve Amazon product details' with a specific verb and resource, and includes the scope (by ASIN on amazon.com). It distinguishes from siblings like amazon_search by focusing on a single product detail retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use (to get details for a specific ASIN), but does not explicitly state when not to use or mention alternatives. However, among siblings, the distinction is implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the output is 'related apps shown on the App Store product page', but it does not specify the structure of the returned data (e.g., full app details or just IDs), and it omits any mention of rate limits, authentication, or other behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at two sentences, front-loading the key action and expected output. Every word contributes value, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite low complexity (4 parameters, no output schema), the description fails to specify the format or structure of the returned 'related apps'. It does not explain how language and country parameters affect results, and it assumes the agent knows what 'You Might Also Like' implies. The lack of output schema increases the need for description completeness, which is only partially met.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides descriptions for all four parameters (100% coverage). The description adds a note that either 'id' or 'app_id' should be provided, but this is implied by the schema having none required. The description does not add significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves 'You Might Also Like' apps from the App Store product page. The verb 'retrieve' and specific phrase 'You Might Also Like' precisely define the tool's function, and it is easily distinguishable from sibling tools like appstore_search or appstore_app.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a basic instruction to provide either 'id' or 'app_id', but it does not offer guidance on when to use this tool versus alternatives like appstore_search or appstore_app. There is no mention of prerequisites, typical use cases, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It clearly states that the tool uses 'credential-free public data sourced directly from Cars.com's own public GraphQL API,' which informs the agent that no authentication is needed and the data is public. It also notes conditional fields like private-seller detail and CPO detail 'when applicable,' showing awareness of variable response shapes. It doesn't mention rate limits or error behavior, but for a read-only detail fetch this is a strong disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, dense sentence that packs in a comprehensive list of return fields without filler. It front-loads the core purpose and then details contents. While it's long, the tool itself returns a rich payload, so the length is justified. It could be improved by breaking the list into bullet points, but it is not wasteful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is no output schema and no annotations, the description compensates by thoroughly enumerating the expected return data: vehicle specs, pricing, equipment, history, seller notes, dealer info, and program details. It also covers data source and authentication context. The only missing elements are potential error cases and how to obtain the listing_id, but for a single-parameter detail tool this is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% coverage for the single parameter listing_id, including its UUID format and URL path context. The description adds no additional parameter semantics beyond the tool name itself. Per the baseline rule, a score of 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description leads with a specific verb-resource pair ('Get Cars.com vehicle listing detail') and then exhaustively enumerates the returned data fields (spec, pricing, history, dealer info, etc.), making the tool's purpose unmistakable. It also implicitly distinguishes itself from sibling tools like carsdotcom_search by focusing on detail retrieval for a single listing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives, nor does it mention that listing_id would typically come from a search tool like carsdotcom_search. It states the data is 'credential-free public data' which gives some context, but it never says 'use this when you have a listing_id' or excludes use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It lists returned fields but does not disclose behavioral traits such as rate limiting, error handling for invalid IDs, or that the ID must be 32 characters (only mentioned in schema). No mention of what 'normalized detail' means or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence followed by a list, which is reasonably concise. It front-loads the main action. However, the list could be more compact, and the defaults are mentioned inline instead of in a structured way. Overall efficient but not perfectly organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (3 parameters, no output schema), the description covers the key aspects: what it does, what data is returned, and defaults. It lacks mention of required parameter (schema covers that) and any edge cases, but is largely complete for its scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (all three parameters documented), so baseline is 3. The description adds value by stating the default values for 'country' and 'lang' (us and en), which is not in the schema. This improves usability.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Chrome Web Store item details, specifying the verb 'Retrieve' and the resource 'Chrome Web Store item'. It lists the data fields returned (name, rating, user count, etc.), distinguishing it from sibling tools like chromewebstore_search (which searches) or chromewebstore_reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you need details for a specific item by ID, but does not explicitly state when to use this tool versus alternatives like chromewebstore_search or chromewebstore_similar. No guidance on when not to use it or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. Mentions 'normalized' data and vs_currency enum support, but omits details on data freshness, rate limits, or safety profile. Adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with verb and resource. No wasted words. Efficiently communicates purpose and key constraint.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists; description lists returned elements but not structure. For a single-coin profile, this is minimally sufficient but could be more complete with return format or example.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline 3. Description adds that vs_currency is a documented enum (not in schema) and id is the coin id. Does not add significant meaning beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it returns a CoinGecko coin profile with specific elements (profile, market stats, links, categories) for one coin id. Distinguishes from sibling tools like coingecko_markets (list) and coingecko_search (search) by focusing on a single coin.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides a negative guideline ('not intended for real-time trading') but does not explicitly state when to use this tool versus alternatives like coingecko_coin_analysis or coingecko_markets. Lacks positive usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It mentions returns 'normalized profile stats and market rows' but lacks details on data limits, pagination, rate limits, or authentication needs. It provides some context but is not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences, front-loading purpose and adding a key note on vs_currency. Every sentence earns its place with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema is provided, and the description does not elaborate on what 'normalized profile stats and market rows' include. It is adequate but not complete for a tool with three parameters and no annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description does not need to add much. It only briefly notes vs_currency enum support, adding little value beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns normalized profile stats and market rows from a CoinGecko exchange page, using a specific verb and resource. It distinguishes from sibling tools like coingecko_exchanges by focusing on a single exchange detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description hints at vs_currency support but does not explicitly state when to use this tool vs alternatives like coingecko_exchanges or coingecko_markets. No specific usage scenarios or exclusions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description states it returns data from public website, implying read-only, but does not disclose side effects, rate limits, or authentication requirements. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first states the tool's output, second adds specific enum context. No unnecessary words, front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema; description does not specify return fields or structure. It mentions 'normalized exchange rows' but lacks details on what those rows contain. Adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all 4 parameters with descriptions. Description adds value by noting that 'vs_currency' supports a documented enum, which is not in the schema. Other parameters are standard pagination.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it returns normalized exchange rows from CoinGecko exchange tables, distinguishes from sibling 'coingecko_exchange' by specifying plural and 'exchange tables'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description lacks explicit when-to-use or when-not-to-use guidance. It implies usage via parameters like 'vs_currency' enum but does not contrast with alternatives like 'coingecko_markets'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the burden of behavioral disclosure. It mentions 'resolved' apps and 'search index' but does not state whether the tool is read-only, describe the return format, pagination limits, or any operational constraints. This leaves significant unknowns for an agent invoking the tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded: one clear purpose sentence followed by three compact enum definitions. Every sentence adds relevant information, and there is no redundant phrasing or unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 12-parameter optional search tool, the description covers the core scope and enums, which is helpful. However, it lacks any mention of return values, pagination behavior, or output structure, and since there is no output schema, these omissions leave gaps. It is minimally adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds meaningful value beyond the schema by clarifying that the platform filter applies only to iOS records and by framing the store parameter as covering resolved apps from both stores. This extra context is not present in the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool searches the apps-intelligence dataset, specifying that it covers resolved iOS App Store and Google Play apps. This specific verb-resource pairing distinguishes it from live store search tools like appstore_search and googleplay_search, and provides clear scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use cases through the 'apps-intelligence dataset' and 'resolved apps' phrasing, suggesting this is for querying a pre-built index rather than live stores. However, it does not explicitly name alternatives or state when to prefer this tool over appstore_search, datasets_apps_charts_search, or similar siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It states it 'Returns one crawled Goodreads author profile record,' which clarifies the output shape. However, it does not disclose potential errors (e.g., missing ID), read-only nature explicitly, or any rate limits. The additional context 'crawled' and 'from dataset' slightly enhances transparency beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (two sentences) and front-loaded with the action. However, the first sentence ('Get a Goodreads author from dataset') is partially redundant with the second sentence, which already specifies 'from dataset'. Still, it is tightly written and avoids unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter retrieval tool with no output schema, the description provides enough context: it names the dataset, the retrieval method, and the return type. It is complete for an agent to select and invoke correctly, though it could have clarified differences from the live `goodreads_author` tool or stated what happens when the ID is not found.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with the single `id` parameter fully described in the schema. The description adds no additional meaning beyond referencing 'id' and 'by id', so it falls to the baseline score for schema-sufficient parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Get') and resource ('Goodreads author from dataset'), and uniquely identifies the retrieval mechanism ('by id from dataset id enum value `goodreads-authors`'). It distinguishes this from live Goodreads tools like `goodreads_author` by emphasizing the crawled dataset source.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool is for fetching a specific author record by ID from the crawled dataset, which differentiates it from search/facet tools. However, it does not explicitly mention alternatives or conditions for when to use this tool over other Goodreads author tools, leaving usage guidance implicit rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool returns terms aggregation counts, which is a read-only aggregation behavior. However, it does not provide additional behavioral context such as how many terms are returned, whether counts are approximate, or any filtering effects. The description is not misleading but stays at a basic level.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded: it states the purpose in the first clause, then the return type, then the facet enum. Every sentence earns its place, with no wasted words. It is well-structured and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 18 parameters, 1 required, no output schema, and no annotations. The schema thoroughly documents all input parameters, but the description does not explain the output format beyond a high-level 'terms aggregation counts', nor does it clarify how filter parameters interact with faceting. Given the complexity, the description is minimally complete but leaves room for missing contextual guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds no parameter semantics beyond what the schema already provides; it merely repeats the facet enum which is already listed in the schema. All 18 parameters have descriptive entries in the schema, so the description does not compensate for any gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Facet' and the resource 'Goodreads books dataset', and explicitly says it 'Returns terms aggregation counts'. It also lists the exact facet enum values, distinguishing it from sibling tools like datasets_goodreads_books_search (full-text search) and datasets_goodreads_books_item (single item retrieval), as well as datasets_goodreads_authors_facets (different dataset).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for getting facet counts on the Goodreads books dataset but does not explicitly state when to use this tool instead of alternatives, nor any exclusions. It mentions the facet enum but lacks direct guidance on when to choose this over search or item tools. Usage is implied from the name and description rather than explicitly clarified.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description must carry behavioral disclosure. Only states it returns distribution counts and honors search filters. Lacks details on behavior like read-only nature, limits, response structure, or multiple facet support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences, front-loaded with key information, no fluff. Efficient structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple facet tool, but lacks output schema details and does not specify if multiple facets can be requested. For an agent, additional context on response format would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. Description adds that filters work like search tool and lists facet enums again, but no additional syntax or format details beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb (facet), resource (journalists dataset), and output (distribution counts). Distinguishes from search and item tools by specifying it returns aggregated counts honoring search filters. Lists valid facet enums.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage for aggregate counts rather than full search results, and mentions it honors same filters as search. However, does not explicitly state when not to use or compare to sibling facet tools for other datasets.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses the return type (one journalist) and error condition (404) but omits details like read-only nature, rate limits, or authentication. The transparency is adequate but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences with no redundant information. It directly states the action, the method, and error handling, making it efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple get tool with two required parameters and no output schema, the description is mostly complete. However, it does not describe the structure of the returned journalist object, which could be helpful. The error handling is well-covered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents both parameters. The description adds context by specifying the dataset enum value `journalists` and the need to use outlet ids from facets. This extra detail warrants a score above baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves a journalist from a specific dataset using outlet id and slug. It distinguishes itself from sibling tools like datasets_journalists_search (search) and datasets_journalists_facets (facets) by being a singular get operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as datasets_journalists_search. The description only includes error handling information (404) but no usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden but only states it returns a composite record. It does not disclose read-only nature, error handling, or any side effects, though the operation appears safe and straightforward.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—two short sentences with no redundant information, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While adequate for a simple retrieval tool, the description omits details about the output format (fields of the composite record) and how errors are handled (e.g., invalid country name). Given no output schema, more context would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of parameters, and the description adds 'as Numbeo spells it', which is helpful but does not significantly augment the schema's own description. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves a Numbeo country record by name from the datasets, distinguishing it from sibling tools like 'datasets_numbeo_countries_search' and 'datasets_numbeo_cities_item' by specifying the dataset id and the type of record.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for fetching a single country by exact name but lacks explicit guidance on when to use this tool versus search or other tools, and does not mention prerequisites or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavior. It reveals that the tool performs a read operation ('Returns') and that the data is 'crawled' from a specific dataset, but it does not mention error behavior (e.g., what happens if the ID is not found), rate limits, or the completeness of the returned record. The description is not misleading but adds only basic behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence of 19 words. It front-loads the verb and resource and includes the necessary dataset enum value without any filler. Every word contributes to clarifying the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a simple, single-parameter tool with no output schema, so the description should clarify what the return value is. It says 'Returns one crawled PitchBook advisor record' but does not explain the structure or contents of that record. The dataset enum value is useful context, but the absence of output schema means more detail about the return value would improve completeness. Overall, it is minimally sufficient for a fetch-by-ID tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes the `id` parameter fully with an example, giving 100% coverage. The description adds minimal extra meaning beyond 'by id', which is echoed in the schema. Since schema coverage is complete, a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Get' and clearly states it returns one crawled PitchBook advisor record by id from dataset id enum value `pitchbook-advisors`. This distinguishes it from sibling tools like datasets_pitchbook_advisors_search or _facets, which are for searching or aggregating instead of fetching a single record by ID.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you have a specific PitchBook advisor ID by stating 'by id'. However, it does not explicitly mention alternatives or when not to use this tool, such as 'use datasets_pitchbook_advisors_search to find advisors without an ID'. The context is clear but not explicitly contrasted with siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explains result structure (one row per SKU, grouping by concept_id/np_title_id) and documents enums for price_tier and sort. However, without annotations, it does not explicitly confirm read-only behavior or disclose rate limits, though search implies non-destructive use.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the main purpose, but it repeats some enum information from the schema, which could be trimmed. Still, it is efficiently structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 28 parameters and no output schema, the description does not sufficiently describe return fields, pagination limits, or expected output format. It lacks completeness for an agent to fully understand tool behavior without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds value by explaining the meaning of concept_id/np_title_id grouping and detailing price_tier and sort enum values, going beyond the schema's parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a search for PlayStation games dataset, specifying it searches the crawled public PlayStation Store catalog. It distinguishes itself from sibling tools like datasets_playstation_games_item by focusing on searching with multiple filters.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like datasets_playstation_games_item or datasets_playstation_games_facets. The description lacks explicit context for choosing this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full safety/disclosure burden. It does usefully disclose that data is public and sourced from Depop's shop pages, implying a read-only, low-risk call. However, it says nothing about pagination, listing limits, request failure, or whether the returned 'current listings' are the complete shop inventory, which is significant in a tool that returns an entire seller's shop.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, each purposeful. The first names the action and object; the second enumerates the output and optional filters, then closes with the provenance note. There is no filler, no restating of the tool name, and no repeated information from the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 11 parameters, no output schema, and no annotations, the description should the carry more contextual weight. It does outline the return payload (profile fields and listings) and points to the public source, which is useful. Yet it omits a mention of the sizes filter, any pagination or listing cap information, and any caveat about shops with zero listings, leaving moderate ambiguity for an agent that wants to exhaust a seller's entire inventory.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the input schema already documents every parameter completely. The description adds value by summarizing many filter categories in plain language ('discount' for on_sale, 'colour' for the colours list), but it omits 'sizes' and does not clarify composite values. Since the schema is already rich, the description provides useful but not necessary reinforcement.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource ('Get a Depop seller's shop') and immediately clarifies the resource's meaning: seller profile plus current listings. The sentence distinguishes it from item/search-focused Depop siblings even without naming them, since the agent is told exactly what kind of object comes back.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description establishes a clear context for use — you want a shop's profile and listings at once — but it never states when NOT to use this tool or points to alternatives such as depop_item, depop_search, or depop_search_sellers. With a large sibling list containing many Depop endpoints, the routing depends on implied scope rather than explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that no DoorDash account or token is required, which is a notable behavioral trait. However, it does not mention the return format, potential side effects, rate limits, or why latitude/longitude are needed beyond the schema. This is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three short sentences, front-loaded with the primary action, and every sentence adds value: purpose, source scope, and auth requirement. There is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with 4 required parameters and no output schema, the description is mostly adequate. It covers the purpose and auth, but lacks details on what 'details' include and doesn't specify expected response content. The schema covers parameter meanings, so the main gap is return value expectations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond the schema; it doesn't explain the relationship between parameters or provide usage examples. Thus it does not improve on the structured data.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get DoorDash menu item details' with a specific verb and resource, and distinguishes it from sibling tools like doordash_store_menu and doordash_search by focusing on a single item. It also identifies the data source ('Android mobile guest experience'), making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving a specific menu item's details based on the presence of item_id and store_id, and notes that no auth token is required. However, it does not explicitly state when to use this tool instead of alternatives like doordash_store_menu or doordash_search, nor does it provide exclusionary guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears the full burden. It mentions the data is from a 'credential-free public JSON' but does not disclose ordering, pagination, number of articles returned, or error handling for invalid sport/league combinations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single focused paragraph, front-loading the purpose and then detailing parameter values. Every sentence adds value with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (two parameters, no nested objects, no output schema), the description covers the main points: what it returns and the valid input values. It could be more complete by mentioning the typical number of articles returned or any rate limits, but it is sufficient for basic use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with two required parameters. The description adds substantial value by listing all accepted sport and league enum values explicitly, along with the constraint that the league must be valid for the chosen sport. This goes beyond the schema's minimal descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: returns recent news articles (headline, description, link) for a league from ESPN's public JSON. The verb 'returns' and resource 'news articles' are specific, and it distinguishes from sibling tools like espn_game_summary or espn_athlete by focusing on league news.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives. The description does not mention contexts where other tools (e.g., for scores or teams) would be more appropriate. Usage is implied but not clarified.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden for behavioral disclosure. It only restates schema-level details (keyword filter, id formats) and does not mention pagination behavior, default page size, response structure, or error handling. This is a significant gap for a tool without annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with the main action front-loaded. No filler or redundancy; every sentence contributes useful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, and the schema covers parameter details, but there is no output schema and no mention of pagination, default limits, or return fields. The description provides a high-level 'catalog' return but is not complete enough for an agent to know what to expect without further assumptions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all parameters are already documented. The description repeats the id and keyword filter info but adds no new semantic meaning beyond what the schema provides. Baseline 3 is appropriate given the high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the action ('Get an Etsy shop's listings') and resource ('a shop's listing catalog'), distinguishing it from sibling tools like etsy_search and etsy_shop by focusing on a specific shop's catalog. It also mentions the optional keyword filter and accepted id formats, making the purpose precise and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies appropriate usage when you need a specific shop's listings and have a numeric id or shop name. It does not explicitly name alternatives or exclusions, but the context is clear enough for an agent to decide when to use this tool over broader search tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It mentions output format but omits details on rate limits, authentication, error handling, data freshness, or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences front-loading core purpose, output type, and key usage rule. No extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 13 parameters and no output schema, the description is minimal. It lacks details on pagination, error responses, and additional behavioral context needed for complete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although schema coverage is 100%, the description adds value by specifying the mutual exclusivity of 'q' and structured fields, a critical constraint not present in individual parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches Nominatim places and returns forward geocoding results, differentiating it from sibling tools like geocoding_lookup and geocoding_reverse.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear constraint ('Use either q or structured fields, not both') but does not offer guidance on when to choose this tool over its siblings or other alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It mentions pagination ('Returns a page') and scope ('public repositories'), but omits details like authentication, rate limits, or pagination behavior (e.g., defaults, max page size). Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. Front-loaded with the core action and resource. Highly concise and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with 6 parameters and no output schema, the description is adequate but not comprehensive. It covers the basic purpose and pagination hint, but could be more helpful about sorting, filtering (type, direction), or expected response structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents all parameters. The description adds no new semantic information beyond the schema; the parenthetical 'company tech stack' is a use-case hint, not parameter detail. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb (List) and resource (GitHub organization's public repositories), and the parenthetical '(company tech stack)' adds context. It effectively distinguishes from siblings like github_user_repos and github_search_repositories.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit mention of when to use this tool versus alternatives (e.g., github_repo for single repos, github_search_repositories for search). The use case is implied by the name and description, but guidance is lacking.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that the tool returns pinned repositories and is empty if none, but lacks details on side effects, authentication needs, or rate limits. Since no annotations are provided, the description carries the full burden; it is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, consisting of two sentences that convey the essential information without redundancy. It is front-loaded with the purpose and includes a behavioral note about empty results.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and absence of output schema, the description adequately explains the return (repositories) and edge case (empty). However, it could be more complete by hinting at the structure of returned repositories (e.g., array of repo objects).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage and a single parameter ('username') already described in the schema, the description adds minimal extra meaning beyond 'GitHub username'. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists a GitHub user's pinned repositories, with a specific verb ('List'), resource ('pinned repositories'), and context ('showcase signal'). It distinguishes from siblings like github_user_repos (which lists all repos) by focusing on pinned ones.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving highlighted repos ('showcase signal') but does not explicitly state when to use this over alternatives like github_user_repos or github_user. No exclusion criteria or context for when not to use it is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, and it does well: it explains that the tool returns a page of normalized hits and aggregate breakdowns over the full result set, and it makes clear the data is public and sourced from Google Patents' own search API. It does not mention rate limits or edge cases, but core behavioral expectations are stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with 'Search Google Patents' before providing details on scope and return values. Though the first and second sentences somewhat duplicate the list of filters, the text is tight, readable, and avoids unnecessary fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 13 parameters and no output schema, the description still manages to explain the return shape ('a page of normalized hits' plus breakdowns) and the data source, giving an agent a solid mental model. It could clarify what 'normalized hits' means or how breakdowns are computed over the full result, but it is complete enough for a search tool with a thoroughly documented schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the schema already documents every parameter with useful context. The description only lists high-level filter types, which adds no meaning beyond the schema, so it meets the baseline for full schema coverage but does not go further.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource ('Search Google Patents') and specifies the full-index free-text scope with filters. The mention of 'full index', 'free-text query', and result breakdowns distinguishes it from sibling tools such as googlepatents_detail, googlepatents_recent, and googlepatents_classification.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a general search use case but gives no guidance on when to use this tool versus alternatives such as googlepatents_recent, googlepatents_detail, googlepatents_coverage, or googlepatents_suggest. It also does not state when not to use it or how it complements the other Google Patents tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as authentication requirements, rate limits, or side effects. It only states the return content (ids and labels), which is minimal for a read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (two sentences) with no unnecessary words. It front-loads the tool's purpose and immediately clarifies the output, making it efficient for an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and no output schema, the description adequately explains what it returns (ids and labels) and the context (top-level categories for Trending Now filters). No further details are needed for a simple listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so the description adds value by specifying that the tool returns 'top-level Google Trends category ids and labels,' which is not evident from the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns 'top-level Google Trends category ids and labels' for the specific use case of 'Trending Now category filters,' which distinguishes it from other Google Trends tools that handle exploration, trending, or enums.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide explicit guidance on when to use this tool versus alternatives like google_trends_enums or google_trends_explore. It implies usage for Trending Now filters but lacks when-not-to-use or alternative suggestions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description only states it returns enum values, without mentioning read-only behavior, permissions, rate limits, or data freshness. For a metadata tool, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence that is clear and directly states the tool's purpose. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema or annotations, the description explains the tool's function and return categories. However, it lacks detail on the structure of returned data and how the values are used in sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters, so schema coverage is 100%. Description adds nothing beyond schema, but baseline 4 for zero-param tools is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as returning enum metadata for Google Trends filters, listing specific categories (locations, date ranges, etc.). It distinguishes from sibling tools like google_trends_explore which actually use these enums.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. It implies usage for obtaining filter values before using other Google Trends tools, but does not state this directly or mention alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that related data is returned 'when Google returns them,' indicating variability. However, it does not mention other behavioral traits like rate limits, required permissions, or what happens if the term is not trending.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, concise, and front-loaded with the purpose. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (multiple return widgets), no output schema, and no annotations, the description is adequate but incomplete. It lacks details about the request object structure and the format of the returned data, which are necessary for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% but only provides a minimal description 'Trending detail request' for the nested request object. The tool description adds no further detail about the request structure or fields, thus adding no value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns detail widgets for a single trending term, listing specific data types (interest over time, regional interest, etc.). It distinguishes itself from siblings like google_trends_trending and google_trends_explore by focusing on a single trending term's detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for getting details on a trending term but does not explicitly state when to use vs alternatives (e.g., google_trends_trending or google_trends_explore). No when-not or alternative guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool 'Returns normalized public IMDb filmography sections', but lacks details on behavior such as rate limits, pagination, or what 'normalized' means. It does not disclose any potential side effects or prerequisites.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the purpose, and every sentence adds value. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description could elaborate on what 'filmography sections' entail or the structure of the response. However, for a simple lookup tool with clear sibling context, it provides adequate but minimal completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters. The description adds the important constraint that exactly one of `id` or `url` must be passed, which is not enforced by the schema's empty 'required' array. This provides meaningful guidance beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Returns' and the resource 'normalized public IMDb filmography sections for a person'. It distinguishes from sibling tools like imdb_name (which likely returns basic info) and imdb_name_awards.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description specifies 'Pass exactly one of `id` or `url`', which is a clear constraint. However, it does not provide guidance on when to use this tool versus alternatives like imdb_name or imdb_name_awards, nor does it mention when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states the return type (categories and severity signals) but does not disclose behaviors like what happens if no parental guide exists, rate limits, or authentication needs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, no unnecessary words. Efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, so description need not cover return values in detail. It mentions 'parental-guide categories and severity signals', which provides basic context. However, it lacks details on what happens when data is missing or the scope (all titles or only some).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds the constraint 'Pass exactly one of id or url', which is useful beyond schema. However, it does not provide additional semantics beyond what the schema already describes.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it returns parental-guide categories and severity signals for an IMDb title. It distinguishes itself from sibling tools like imdb_title, imdb_title_awards, etc., by specifying the exact resource and action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit instruction to pass exactly one of id or url, which guides parameter usage. Does not discuss when to use this tool versus alternatives, but the purpose is clear enough among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully communicate behavior, and it does state the output is a feed and that pagination is supported. However, it does not disclose auth prerequisites, rate limits, or how 'feed' items are structured, limiting an agent's ability to predict the call's full behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and to the point, with the main verb and purpose front-loaded. The first two sentences are slightly redundant, both saying that a user's Reels are returned, but this does not significantly harm usability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the parameters and the schema's full coverage, the description is mostly sufficient for an agent to call the tool correctly. It could be improved by stating that the ID must be numeric (though schema does say this) or clarifying what data a single Reel feed item contains.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already has 100% coverage for both parameters, so the description does not need to elaborate. It does add a subtle nod to max_id for pagination, but that information is already present in the schema's description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Retrieve', the resource 'Instagram Reels', and specifies it is for a particular user via a user ID. It distinguishes from related Instagram tools by focusing exclusively on Reels, so an agent can easily tell it from instagram_profile or instagram_post.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: call this when you need the set of Reels for a given Instagram user. However, it does not explicitly say when not to use it or when to prefer a sibling tool like instagram_post or instagram_profile. Pagination guidance is helpful but focuses on parameter handling rather than tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the burden. It discloses that it is 'Credential-free' (no auth) and 'public ATS JSON' (output format). It mentions pagination (limit/offset). It does not cover error handling, rate limits, or edge cases like invalid company IDs, but these are minor for a simple read endpoint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, but the first two are almost identical ('List a company's SmartRecruiters postings' and 'Lists a company's public SmartRecruiters postings...'), creating minor redundancy. Apart from that, it is efficient and front-loaded with the key action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema is provided, so the description should explain the response format. It only says 'Credential-free public ATS JSON,' lacking detail on fields returned (e.g., title, location, date). For a listing tool, response structure is crucial, making this incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema coverage is 100% with descriptions for each parameter. The description adds value by explaining the company parameter as 'the SmartRecruiters identifier from its careers URL,' clarifying how to obtain it. For limit/offset, it reiterates pagination but adds no new detail beyond the schema. Overall, it enhances understanding beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The tool name and description clearly state it 'List a company's SmartRecruiters postings,' with a specific verb and resource. It differentiates from siblings like jobs_greenhouse_board by specifying the ATS (SmartRecruiters) and public nature. The repetition in the description is minor.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use: when you need public SmartRecruiters postings from a company. It explains how to find the company identifier (from careers URL). However, it does not explicitly state when not to use it (e.g., for authenticated or internal postings) or mention alternatives among siblings, leaving the agent to infer.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It states the return is 'popular titles for one monetization type' but does not disclose read-only nature, output format, or any limitations beyond parameter validation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two short sentences that cover purpose and key parameter constraints. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is adequate but leaves gaps: it does not describe the structure of the returned titles, potential errors, or prerequisites. It covers the bare minimum.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Even though schema coverage is 100%, the description adds value by explicitly listing the allowed values for monetization_type and type, which are not enforced via enums in the schema. This provides clearer guidance beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb (Get), resource (JustWatch monetization titles), and scope (for one monetization type). It focuses on a specific functionality distinct from sibling tools like justwatch_popular or justwatch_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides parameter constraints but does not explicitly state when to use this tool versus alternatives such as justwatch_popular or justwatch_provider_titles. Usage context is implied but not explicitly outlined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states that it returns data from public orderbook JSON, lacking details on data freshness, rate limits, side effects, or what 'normalized' means. This is insufficient for a mutation-free tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the core purpose. Every word serves a purpose. No extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, but the description omits important details like the exact output structure, handling of more than 25 tickers, and examples. It provides minimal context, leaving the agent to infer behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a description for the single parameter. The tool description does not add additional semantics beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns normalized yes/no bid levels for up to 25 Kalshi market tickers, using a batch mode. It distinguishes itself from the singular sibling tool by explicitly calling it a 'batch' version.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for multiple markets via 'batch' and 'up to 25 market tickers', but does not explicitly contrast with the singular sibling or state when to avoid usage. However, the batch context provides clear guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description carries burden. States paginated nature and public data access, but does not disclose rate limits, error handling, or data freshness. Adequate for a simple listing tool but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first defines purpose and pagination, second lists return fields and credential info. No fluff, front-loaded, every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema; description compensates by listing return fields. But misses details on sort parameter, default pagination, and any limits. Adequate for a simple tool but leaves some ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (all four parameters described). Description adds no extra meaning for parameters beyond schema; it mentions pagination generically but not sort options or constraints. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'List a Metacritic game's user reviews' with specific verb and resource. Lists return fields (author, score, etc.) and notes credential-free access. Clearly differentiates from sibling Metacritic tools like metacritic_game_critic_reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description mentions 'Credential-free public Metacritic data' implying no auth required, but does not explicitly state when to use this tool versus alternatives (e.g., critic reviews, game details). No exclusionary guidance or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It discloses the data source (public Metaculus data, no credentials) and a key limitation (comment bodies not exposed). However, it lacks details on caching, rate limits, or whether the data is precomputed or live. The time window is noted as 'roughly the last week.'
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is just two sentences: the first defines purpose and scope, the second adds data source and a critical limitation. No wasted words, front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks detail on the output structure (fields of the 'normalized question rows'), which is needed since no output schema is provided. The 'topic' parameter is only mentioned in the schema; the description doesn't explain its effect. Overall, it covers core functionality but is incomplete for a tool without an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters (limit, topic) have descriptions in the schema (100% coverage). The description adds no additional meaning beyond what the schema already provides. Baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns 'normalized Metaculus question rows for the questions whose recent public comments collected the highest vote scores over roughly the last week.' It distinguishes itself by specifying it returns question rows (not comments) and that comment bodies are not exposed, setting it apart from sibling tools like metaculus_comments_feed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving questions with highly-voted comments over the past week, but it does not explicitly state when to use this tool versus alternatives like metaculus_comments_feed or metaculus_category_questions. No direct comparisons or exclusions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that invalid slugs return 404 and that output is 'normalized', but it omits details on return format, pagination, or rate limits. It offers some useful behavioral context but is not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose, and contains no redundant information. Every word serves a purpose, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema, the description does not enumerate the fields in the normalized rows, leaving the agent to guess the return structure. It is adequate for a simple fetch tool but lacks details that would make it fully self-contained for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes both parameters with 100% coverage. The description adds minimal value by reiterating that filtering is by slug, but it does not introduce any new semantics or formatting details for the parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool returns normalized Metaculus question rows for a specific public tournament, filtered by slug. This distinguishes it from sibling tools like metaculus_questions or metaculus_project_questions by explicitly scoping to tournaments.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (you need a tournament slug), but it does not explicitly mention when to prefer this tool over other Metaculus tools, nor does it provide exclusions or alternatives. Clear context exists, but no direct guidance for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description notes 'Credential-free public Numbeo data' implying read-only and no auth, but does not disclose error handling, rate limits, or caching behavior. Adequate for a simple data retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two clear sentences with no extraneous content. Front-loaded with primary purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and simple parameters, the description explains inputs and outputs adequately but lacks error/edge case info. Could mention response format or example usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with minimal param descriptions. Tool description adds context by explicitly listing index families and result structure, but does not further detail slug format or valid values beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it retrieves a Numbeo city's data for an index family. Lists valid families and describes result structure, distinguishing it from sibling tools like numbeo_cost_of_living_city or numbeo_indices_country.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool over siblings. The description implies city-level index data, but does not address selection criteria or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description adds some behavioral context: credential-free public data, current vs. historical snapshots. However, it lacks details on output structure, error handling, or rate limits, which are important for a ranking tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences: purpose, feature (current/historical), and data source note. No unnecessary words, front-loaded with key info.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema is provided, and the description does not explain the return format (e.g., list of cities with ranks). The concept of 'index family' remains vague. Some context is provided about data being public, but overall completeness is adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions. The description reinforces the meaning of 'index family' and current/historical scope but does not add new semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets global city rankings for a Numbeo index family, with support for current and historical snapshots. This distinguishes it from sibling tools like numbeo_cost_of_living_rankings or numbeo_indices_city.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for global rankings but does not explicitly guide when to use this tool versus alternatives like numbeo_cost_of_living_rankings or numbeo_indices_rankings_by_country. No 'when not to use' guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It states returns 'normalized public trade rows' and is 'credential-free', but does not disclose side effects, rate limits, or behavior with missing parameters. The read-only nature is implied but not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, then enums. No wasted words. Efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 7 parameters and no output schema, the description covers basic behavior and enum constraints but lacks examples, typical usage, or explanation of parameter interactions. Adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, but the description adds specific enum values for taker_only, filter_type, and filter_amount, which are not in the schema descriptions. This adds concrete semantics beyond the generic descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Starts with 'List Polymarket activity trades', a clear verb and resource. Distinguishes from many sibling tools that deal with other aspects like events, markets, tokens, or search. The specific mention of 'activity trades' sets it apart.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives. While it mentions credential-free and Data API, it doesn't compare to other polymarket tools or specify selection criteria like when to use this vs polymarket_trades or other list tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Mentions it uses public CLOB market-data JSON, credential-free, and handles up to 25 token ids. However, without annotations, more details about rate limits, response format, or error behavior would be beneficial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first states purpose, second clarifies authentication requirement. No fluff, all information is relevant and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description adequately covers what the tool does, what it expects, and returns. Could include how to structure the body (e.g., array of strings), but overall sufficient for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema shows one required 'body' object with description 'Token ids request body'. Description adds that it accepts up to 25 token ids, clarifying the parameter's content and constraint. This adds value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it gets Polymarket token spreads and returns CLOB spreads. However, does not explicitly differentiate from sibling tool 'polymarket_token_spread' (singular), which might cause confusion about batch vs single usage.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides context that it works with public data and does not require authentication, but does not specify when to use this vs the singular version or other alternatives. No exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Lists returned data types but does not disclose rate limits, authentication needs, or data freshness. Adequate but not detailed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first states action, second lists returned data. No redundant words. Efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Simple tool with one param and no output schema. Description lists key data types but not structure. Adequate for retrieval but could be more precise. Sibling tools offer similar context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Single parameter 'id' is described as 'Product Hunt slug' in schema. Description adds no extra meaning beyond schema, which already covers it. Baseline 3 due to 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'Retrieve' and resource 'Product Hunt product about page'. It differentiates from sibling tools like producthunt_product by emphasizing 'richer' payload including launch, forum, review tags, and media data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage: use when needing the about page payload. No explicit when-not or alternatives mentioned, but context of sibling tools suggests differentiation. Lacks exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that posts are 'normalized public posts' and provides specific handling for 503 throttling responses, which is useful. However, it does not mention read-only nature, authentication requirements, pagination behavior, or return format details, leaving gaps in behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the core purpose. Each sentence adds value: first states the action, second clarifies return characteristics (normalized, public), third provides actionable retry guidance. The slight repetition of 'multi-subreddit' does not detract from overall efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a moderately complex tool (5 params, no output schema, no annotations). The description covers purpose and error handling but does not explain return values in detail (e.g., fields, structure) or default behaviors for sort/time/limit, which the schema does not cover. It is adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 5 parameters. The description adds minimal parameter-related meaning beyond the schema, only indirectly hinting at the 'subreddits' parameter via 'multi-subreddit'. This aligns with the baseline of 3 for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('List') and resource ('Reddit multi-subreddit posts') and provides an additional clarifying sentence about returning normalized public posts from a combined multi-subreddit feed. This distinguishes it from single-subreddit tools like reddit_subreddit_posts by explicitly emphasizing the multi-subreddit scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for fetching posts across multiple subreddits ('combined multi-subreddit feed') but does not explicitly state when to use it over alternatives, nor does it mention exclusions or prerequisites. The 503 retry note is operational guidance, not usage selection guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description discloses it's a 'faithful pass-through' of Redfin's public AVM and historical data resources, indicating read-only behavior and source. No annotations provided, so description carries full burden; it adds useful behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first states purpose and outputs, second adds backend context. Efficient, no redundancy, but could be slightly more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema, description adequately lists return data and backend nature. Lacks details on property facts scope but otherwise complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema already describes 'property_id' as 'Redfin property id' (100% coverage). Description does not add further meaning or examples, meeting baseline without enhancement.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool returns the Redfin Estimate for a property, listing specific data points (current estimate, property facts, monthly history with comparatives). It distinguishes itself from sibling tools like redfin_property by focusing on the estimate and historical data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool over alternatives such as redfin_property or redfin_search. Usage context is implied but not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses that the tool is 'credential-free' and returns metadata and a URL, but does not mention rate limits, error behavior, or what happens if the filing is not found. For a simple read-only tool, this is adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four sentences, each adding value. It front-loads the main action and then details what it returns and parameters. Could be streamlined, but it is clear and concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with 3 parameters and no output schema, the description states what is returned (metadata and URL) and that it is credential-free. It does not detail the metadata fields, but that is acceptable given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds that 'cik or ticker' can be provided alongside accession, which slightly clarifies usage, but does not add significant meaning beyond the schema's parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the specific resource 'a single filing by accession number'. It mentions it returns 'metadata and primary document URL', which distinguishes it from sibling tools like sec_company_search or sec_company_submissions that have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some parameter guidance ('Provide accession plus cik or ticker'), but does not explicitly state when to use this tool versus alternatives like sec_filing_sections or sec_full_text_search. It lacks when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses credential-free access and returns every filer's value, but omits details on pagination, rate limits, or handling of missing data. No annotations present to compensate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences, front-loaded with core purpose, no redundant information. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple data retrieval tool with well-documented schema, but lacks return format details and handling of large result sets given the limit parameter.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All parameters have schema descriptions (100% coverage), so the description adds minimal new meaning—only contextualizing concept and period as EDGAR frames.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool retrieves cross-company values for one XBRL concept and period, distinguishing it from other SEC tools like sec_company_submissions or sec_financials.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage for aggregate XBRL data across companies, but lacks explicit when-to-use/when-not-to-use guidance or mentions of alternative tools for single-company data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral disclosure burden. It compensates well by revealing a genuine quirk: Sephora's upstream 'never returns a genuine zero-result state' for nonempty queries and 'a deliberately nonsense query still returns unrelated product suggestions.' This helps an agent interpret unexpected results. It doesn't cover all aspects like rate limits or return size, but this is valuable context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact at three sentences with no filler. It front-loads the core action and return content, then adds a meaningful behavioral caveat. There is minor redundancy in repeating 'Sephora's own', but overall every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no output schema, the description explains what the response will contain: keyword completions, matching products, and categories. It also covers an important edge case (nonsense queries still return results). Details about response structure or limits are absent, but the lack of complexity and the sufficient level still allow an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for the single 'query' parameter, so the schema already documents it as 'Partial search keywords.' The description adds slight extra context by framing the parameter as partial keyword input for type-ahead suggestions, plus the no-zero-result caveat. Still, the semantic burden is largely met by the schema, yielding the baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb, 'Returns', and names a precise resource: Sephora's search-box type-ahead suggestions, followed by the concrete content: keyword-completion terms, matching products, and related categories. It does not explicitly compare to sibling tools like sephora_search, but the 'type-ahead' positioning self-distinguishes it from full-search tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for a partial keyword' clearly implies this tool is meant for autocomplete/type-ahead scenarios. However, the description gives no explicit when-to-use, when-not-to-use, or alternative guidance compared with sephora_search, sephora_category, or other suggestion tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description should disclose behavioral traits. It notes parameter formats but omits details on what 'adjacent' means, pagination, side effects, or auth requirements. Unclear behavior for list retrieval beyond basic listing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: the first establishes purpose, the second covers parameter details. No fluff, front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Lacks output schema, so description should explain return value shape. 'Adjacent variants' is vague, and no details on pagination or response structure. Adequate for basic use but incomplete for advanced scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds extra value: clarifies selected_options as JSON object and documents alternative query formats (option.Name=value). This goes beyond the schema's brief descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List Shop.app product variants' and specifies 'Returns adjacent variants for a Shop.app product'. This distinguishes it from siblings like shop_app_product (product details) and shop_app_product_variant (singular variant).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides parameter usage details (e.g., selected_options must be JSON, option.Name=value formats) but does not explicitly state when to use this tool vs. alternatives like shop_app_product_variant for a single variant. Usage context is implied but not directive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses the endpoint is credential-free and uses Ajax, indicating no authentication needed. However, it lacks details on rate limits, error handling, or data freshness, which are typical for such tools.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at one sentence, covering the primary purpose, return types, and source. It is front-loaded with the action verb 'Get' and avoids unnecessary details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description should explain what the return object looks like. It mentions the return types but not the structure. The parameter documentation in the schema covers the inputs, but overall completeness for a tool with 4 parameters and no annotations is adequate but not fully comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description does not add new semantics beyond the schema; it mentions return types but does not elaborate on parameter syntax or constraints beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Shopify search suggestions, listing the specific return types (products, collections, query suggestions) and noting the endpoint is credential-free and uses predictive search Ajax. This distinguishes it from other Shopify search tools like shopify_search and similar suggest tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for autocomplete-like suggestions but does not explicitly state when to use this tool versus alternatives like shopify_search or other suggest tools. No exclusions or best practices are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses credential-free access and 404 on missing lineups, which is helpful, but omits potential rate limits, response structure, or other behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: the first clearly states purpose and output, the second notes the 404 error case. No wasted words, information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description covers the main outputs and error case, but could elaborate on output structure (e.g., player details, formation format) to improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents the id parameter. The description adds that id is 'Numeric SofaScore event (match) id', but this adds minimal value beyond the schema description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool returns 'starting XI and substitutes per side, with formation' for one match, clearly differentiating from sibling tools like sofascore_event or sofascore_event_statistics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for retrieving lineups via name, but lacks explicit guidance on when to use this tool versus alternatives like sofascore_event for general match info. No when-not or alternative mentions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It does disclose a meaningful trait — 'Public data sourced from SoundCloud's own JSON API' — which signals a safe read operation requiring no authentication. However, it does not mention rate limits, behavior on invalid or removed tracks, or any caching characteristics, leaving it at baseline rather than rich disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact — three short sentences, each earning its place: purpose, returned fields, and data source. The scoping statement is front-loaded, and there is no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-required-parameter tool with no output schema and no nested objects, the description is largely complete: the input is fully covered by the schema, and the description enumerates the key fields of the return payload. The only gaps are minor edge details like failure behavior for invalid URLs, which are not critical for a low-complexity read tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the schema already fully documents that `url` is the track's permalink_url. The description adds no additional parameter-level detail beyond what the schema provides, which is exactly the baseline for full schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb-resource pair — 'Get a SoundCloud track's detail' — and immediately distinguishes itself from siblings like soundcloud_search, soundcloud_playlist, and soundcloud_profile by scoping to a single track. The enumeration of returned fields (title, artwork, description, genre, tags, counts, uploader) leaves no ambiguity about what the tool produces.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit when-to-use or when-not-to-use guidance, nor named alternatives. An agent can infer this is the right tool when it already holds a track URL and wants full metadata, but the description never says to use soundcloud_search for discovery or soundcloud_playlist for playlist content. The usage context is implied rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It states it's 'credential-free' and 'public,' implying a safe read operation, but does not explicitly disclose idempotence, rate limits, or that it is read-only.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loading the main action. It is concise with no wasted words, though it could include more context without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with 3 parameters and no output schema, the description is fairly complete: it states purpose, return fields, and that it's public. However, it could mention that only one app can be queried at a time.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds no additional parameter meaning beyond the schema's descriptions (appid, count, maxlength), which are already clear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get recent news posts for a Steam app,' specifying the resource (Steam app) and action (get recent news). It distinguishes from sibling tools like 'datasets_steam_news_search' by focusing on a single app's news.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions 'Credential-free public Steam WebAPI JSON,' indicating no authentication needed, but does not explicitly state when to use this tool versus alternatives like 'datasets_steam_news_search' for cross-app news searching.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It states that the tool 'returns normalized details and visitor information,' giving some output expectations. However, it does not disclose any potential side effects, error behaviors, or requirements beyond the ID. For a simple read operation, this is acceptable but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences with no fluff. The first sentence 'Get a Ticketmaster venue' slightly repeats the tool name, but the second sentence adds essential context about return content. It is front-loaded and efficient, though not entirely without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with only one parameter and no output schema, the description gives a reasonable summary of what it returns ('normalized details and visitor information'). It does not detail the structure of the return value, but the simplicity of the tool and the presence of sibling tools like ticketmaster_venue_events provide enough context for an agent to select it appropriately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% as the parameter 'id' is documented as 'Numeric Ticketmaster venue id'. The description adds no additional meaning beyond the schema. Per baseline for high schema coverage, a score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets a Ticketmaster venue with a specific verb ('Get') and resource ('venue'). It distinguishes itself from sibling tools like ticketmaster_event or ticketmaster_venue_events by mentioning 'normalized details and visitor information' for a single venue, which uniquely identifies its purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: use this tool to retrieve details for one venue by ID. However, it does not explicitly state when to use this over alternatives, such as ticketmaster_event for event details or ticketmaster_venue_events for events at a venue. There is no mention of exclusions or alternative conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only restates the core function ('Returns upcoming Ticketmaster events at one venue') and adds the sort enum values. It does not disclose pagination behavior, whether events are sorted by date by default, timezone implications, or any other behavioral nuance.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short but somewhat redundant—'List a venue's Ticketmaster events' and 'Returns upcoming Ticketmaster events at one venue' say nearly the same thing. It is not as polished as it could be, though it does front-load the key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple and has no output schema, but the description does not mention what fields the returned events contain or how many results are returned. It gives the essential 'what' but lacks enough detail for full context, though it is adequate for a straightforward listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds valuable detail by explicitly listing the accepted sort values (`relevance` and `date`), which the schema does not provide. This goes beyond the baseline and assists with correct parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List'), the specific resource ('a venue's Ticketmaster events'), and the scope ('upcoming', 'at one venue'). This differentiates it from sibling tools like ticketmaster_search_events or ticketmaster_attraction_events, which cover different scopes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Clear context is provided: this is for a single venue's upcoming events, requiring a venue ID. However, it does not explicitly mention exclusions or alternatives (e.g., when to use ticketmaster_search_events instead), so it falls short of a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden and discloses a crucial behavioral trait: anonymous requests receive at most 3 hashtags and full results require a logged-in TikTok One account. It also clarifies that the result is ranked, giving agents realistic expectations about return scope.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, with the first two sentences largely redundant ('Retrieve...' and 'Returns...'). The third sentence is useful and concise, but the redundancy could be trimmed to make it tighter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description does not specify the fields returned (e.g., hashtag name, rank, count). It covers the auth limitation well, but leaves the response structure and optionality of 'period' unexplained, which is a notable gap for a retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with 'period' and 'country_code' clearly described. The description adds no extra parameter-level detail (e.g., allowed period ranges, defaults), but the schema already provides sufficient meaning for straightforward parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Retrieve') and resource ('TikTok Creative Center trending hashtags'), clearly stating it returns ranked trending hashtags for a country and period. This distinguishes it from sibling tools like tiktok_search_hashtag, which focuses on searching specific hashtags.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for country- and period-specific trending hashtags, but does not explicitly state when to use this tool over alternatives or include exclusions. The authentication limitation provides some context, but no direct comparison to related hashtag tools is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It mentions 'cursor-based pagination', which is a useful behavioral trait. However, it does not disclose other important behaviors like rate limits, authentication requirements, or whether results are limited to public hashtags.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no redundant words. The purpose is stated upfront, and the pagination detail is included concisely.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema and moderate complexity (3 parameters, pagination), the description covers the basic purpose and pagination method. However, it lacks details on what the response contains, any result limits (beyond count clamp), or error conditions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by stating that the 'count' parameter is 'clamped to 50', which is not evident from the schema. However, it does not add additional meaning beyond the schema for 'keyword' and 'cursor'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Search' and clearly identifies the resource 'TikTok hashtags' and 'challenges'. It distinguishes from sibling tools like tiktok_search (general) and tiktok_search_user by focusing on hashtags/challenges.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (searching hashtags by keyword) but provides no explicit guidance on when not to use it or alternatives among the many sibling tools. No mention of prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry full transparency burden. It discloses that the data is credential-free and public, indicating a safe read operation. However, it does not explain pagination behavior, result size limits, or the shape of returned data, which are important for an agent to form expectations beyond the minimal 'returns a chart' statement.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the main action. The second sentence redundantly restates 'Returns a TMDB movie chart,' which is a minor flaw. However, the overall structure is efficient, and the 'Credential-free public TMDB data' sentence adds useful context without unnecessary verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 14 optional parameters and no output schema, the description is too sparse. It does not mention the extensive filtering capabilities (date ranges, ratings, runtime, genres) or the structure of the returned movie list. This is a significant gap for a tool with this complexity; the agent would need to rely entirely on the schema to understand the tool's full capabilities.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides 100% coverage for all 14 parameters, so the baseline is 3. The description adds value by explicitly listing the valid category values (popular, top rated, now playing, upcoming) that map to the 'category' parameter, which the schema does not enumerate. This extra detail helps the agent determine valid inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb ('Get'), a clear resource ('TMDB movie chart'), and enumerates the chart categories (popular, top rated, now playing, or upcoming). This distinguishes it from sibling tools like tmdb_search (movie search) and tmdb_tv_list (TV charts), making its purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for fetching predefined movie charts but does not explicitly state when to use this tool versus alternatives such as tmdb_search or tmdb_movie. It mentions 'Credential-free public TMDB data,' which gives some context about no-auth access, but it lacks explicit when-to-use or when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It adds meaningful context: the data source (public place HTML), the differentiated fast path for certain page types, and the use of browser fallbacks when direct HTML is blocked. This goes beyond a simple 'get' tool and helps an agent anticipate potential delays or source variations, though it doesn't cover error cases or normalization specifics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, with a clear front-loaded purpose ('Get TripAdvisor place') followed by a single sentence of behavioral context. Every word earns its place; there is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains what the tool returns and some behavioral nuances, but it omits how the two optional parameters ('id' and 'url') are meant to be used—for example, whether one is required or takes precedence. With no output schema, an agent would benefit from more explicit input guidance to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% description coverage for both parameters ('id' and 'url'), so the schema does the heavy lifting. The description adds no parameter-level details, but the baseline of 3 is appropriate when schema coverage is high.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Get') and a specific resource ('TripAdvisor place'), and specifies the return as a 'rich normalized TripAdvisor place profile.' It distinguishes itself from sibling tools by focusing on place profiles, though it doesn't explicitly contrast with other TripAdvisor tools like tripadvisor_hotels or tripadvisor_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some context about behavior—such as a faster dedicated lookup for destination and bookable tour/experience pages, and configured browser fallbacks when HTML is blocked—but it never explicitly states when to use this tool over alternative TripAdvisor tools or provides when-not-to-use guidance. The usage context is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears the burden of explaining behavior. It states this is a 'Get' operation (implying read-only) and lists the return content, but it does not disclose potential errors, authorization needs, or behavior for invalid slugs. It is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long with no redundant information. It is front-loaded with the verb and resource, making it easy to parse. However, it could be slightly more structured by explicitly stating the input parameter's role.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 parameter, no output schema), the description adequately covers what the tool does and returns. It mentions both the category page and the startups with verified revenue/MRR, which is sufficient for an agent to understand the output. No missing critical details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (slug parameter is described as 'TrustMRR category slug'). The description adds no additional meaning beyond the schema, matching the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'TrustMRR category detail', specifying it returns a single category page and startups. It distinguishes itself from sibling tools like trustmrr_categories (which likely lists categories) and trustmrr_startup (which likely gets a single startup).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving a specific category detail, but it does not explicitly state when to use this tool versus alternatives (e.g., trustmrr_categories for listing all categories) or provide any exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It does not state that data is public (no auth), limited to the last 7 days, and sorted most-viewed first. However, it does not disclose rate limits, error behavior, or what happens when no clips exist, leaving some gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences total, well front-loaded with the core action and resource. The second sentence redundantly says 'Twitch channel's clips' again, but overall the wording is compact and covers essential constraints and returns.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 2-parameter tool with no output schema and full schema coverage, the description adds important context: time window, sorting order, return field list, and data source. This is enough that an agent can confidently invoke the tool without further documentation, though pagination behavior is not elaborated since limit is already described.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already fully documents both 'login' (with a concrete example) and 'limit' (default 20, max 100). The description adds no new parameter meaning beyond the schema, so the baseline of 3 for full schema coverage is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Get a Twitch channel's clips' and adds constraining details (last 7 days, most-viewed first) with a clear list of returned fields (title, view count, duration, curator, game). This clearly distinguishes it from sibling Twitch tools like twitch_videos or twitch_streams.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus the many Twitch-related alternatives (twitch_videos, twitch_streams, twitch_search, etc.). There is no mention of alternatives, exclusions, or selection criteria, so an agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden. It discloses that the data is public, originates from Twitch's GraphQL API, is scoped to past broadcasts, and is ranked by view count. This is more behaviorally transparent than a minimal statement, though it omits factors like pagination, rate limits, or explicit output ordering (e.g., descending).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three short sentences that front-load the primary purpose. It briefly repeats 'videos (VODs)' and has a little redundancy, but overall the content is tight and no words are wasted on irrelevant details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 2-parameter tool with no output schema, the description compensates by listing the return field values (title, view count, length, publish date, game) and the ranking behavior. It does not describe response envelope, error conditions, or pagination, but those are not critical for this lightweight read-only use case.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% parameter description coverage for both 'login' and 'limit', so the schema already documents the parameters. The description adds no additional parameter-level semantics, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool's purpose with a specific verb and resource: 'Get a Twitch channel's videos (VODs).' It also narrows the scope to 'past-broadcast videos' to distinguish the tool from adjacent concepts like streams or clips. However, it does not name any sibling tool explicitly, so it misses the strongest form of differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool's context of use — when a user needs a channel's past-broadcast VODs — but it does not give explicit when-to-use or when-not-to-use guidance. It also doesn't mention alternatives such as twitch_streams, twitch_clips, or twitch_search. The usage signal is present but implicit rather than direct.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses 'Public data, sourced from Vinted's own server-rendered brand page', implying a read-only, no-auth operation. However, it does not mention pagination behavior, rate limits, or what fields a listing contains, which would be valuable context for a scraper tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description includes a redundant first sentence ('Vinted listings for a brand.') that repeats the second sentence. The order values are also listed in both the description and the schema, creating duplication. It is short but contains unnecessary waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, so the description should explain what a 'listing' looks like, but it only says 'returns Vinted listings' without describing the structure. It also lacks pagination details despite having a page parameter. Acceptable for a simple read tool, but significant gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description mentions optional price filtering and sort order, but this information is already present in the schema's property descriptions. It adds no new meaning beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Returns Vinted listings for a specific brand', giving a specific verb (returns), resource (Vinted listings), and scope (specific brand). This distinguishes it from siblings like vinted_brands (list of brands) and vinted_item (single item).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: the tool is for a specific brand and supports optional price filtering and sort order. However, it does not explicitly mention alternatives or when not to use this tool compared to other Vinted tools like vinted_catalog or vinted_category. No exclusions are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds the useful context that this is 'Public data, sourced from Vinted's own server-rendered catalog page', implying safe read-only access and data provenance. However, it doesn't disclose pagination behavior, response structure, or rate limits, which the absence of annotations makes more important.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded, starting with the core purpose in a single sentence. The list of order values is a concise, useful addition, and the sourcing note is brief. No wasteful words or redundant details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the basic search function and filters, but with no output schema, it does not explain what fields are in each returned listing or how pagination works. Given the tool's moderate complexity (5 params), the description is adequate but leaves gaps in expected result details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with each parameter documented. The description's mention of 'optional price filtering' and the list of order values matches the schema descriptions but does not add new meaning beyond the structured input schema, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool is a 'Vinted listing search' that 'returns Vinted resale listings matching a text search', explicitly naming the action (search) and resource (Vinted resale listings). It clearly distinguishes from sibling tools like vinted_item or vinted_category by focusing on text-based search with filters.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for text-search queries on Vinted and mentions optional price filtering and sorting, but it does not explicitly explain when to choose this over sibling tools like vinted_category or vinted_item, nor does it state any exclusions or alternative recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description simply says it lists keys. With no annotations, the description carries full burden for behavioral disclosure. It does not mention that the data is read-only, how fresh the data is, or any other behavioral traits (e.g., no side effects). This is minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two short sentences that convey the purpose and an important usage hint. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with no parameters and no output schema, the description is adequate but could be more complete. It does not mention the format of the keys, whether the list is static or dynamic, or any ordering. However, it provides enough for basic usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, and schema description coverage is 100% (empty). The description adds no parameter information because there are none. Baseline of 3 is appropriate as no additional meaning is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: listing Yahoo Finance industry keys. It uses a specific verb ('lists') and resource ('Yahoo Finance industry keys'), and distinguishes itself from sibling tools like yahoo_finance_industry (which likely requires a key) and yahoo_finance_sectors.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates that the output can be used with 'the industry endpoint', implying yahoo_finance_industry. This provides context for when to use this tool (before querying a specific industry). However, it does not explicitly mention alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. The description does not disclose any behavioral traits such as read-only nature, error handling, rate limits, or whether the operation is destructive. Minimal disclosure beyond basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at two sentences. It front-loads the key information and contains no filler. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no output schema, the description should ideally provide more details about the returned ESG modules structure. It gives a high-level understanding but lacks specificity. Adequate for a simple tool but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for the single parameter 'symbol'. The description adds no additional meaning beyond the schema's description 'Yahoo Finance symbol such as AAPL'. It meets the baseline but does not enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns ESG and sustainability modules for a given symbol. The verb 'returns' and resource 'ESG and sustainability modules' are specific. Among many yahoo_finance_ticker_* siblings, this tool's focus on sustainability differentiates it effectively.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining ESG data. While it doesn't explicitly list alternatives, the purpose is clear enough that an agent should infer to use this tool when sustainability data is needed and other ticker tools for other data. A minor lack of explicit when-not-to-use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that it returns 'normalized playlist items' and an optional continuation token, but fails to mention authentication needs, rate limits, or potential side effects. Adequate for a simple read operation but not detailed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the main action. Every word is purposeful, with no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description gives a basic idea of return data ('normalized playlist items') and pagination. However, it doesn't clarify what 'normalized' means or provide details on field structure, which could aid agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters. The description adds minimal value beyond schema, only mentioning the continuation token's purpose. Baseline of 3 is appropriate as no extra semantics are provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Retrieve' and the resource 'playlists tab for a YouTube channel', precisely defining the tool's purpose. It distinguishes from sibling tools like youtube_channel_videos and youtube_playlist by targeting the specific playlists tab.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (to get a channel's playlists) but provides no explicit guidance on alternatives or when not to use. It lacks contrast with sibling tools like youtube_playlist for specific playlist details.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the burden. It mentions 'normalized video search items' and 'resolved top-level query', hinting at output structure, but does not disclose rate limits, authentication needs, or any potential side effects. For a search tool, it's adequate but not detailed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that front-load the core purpose. No redundant or extraneous information. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description is minimal. It explains the action and output style but omits details on pagination behavior, error scenarios, and the nature of 'normalized' items. Adequate but could be more thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the parameters are well-described in the schema. The description adds no extra meaning to the parameters; the mention of 'normalized video search items' relates to output rather than input semantics. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Search within a YouTube channel' and 'returns normalized video search items scoped to a specific channel', clearly distinguishing it from siblings like 'youtube_search' (searches across YouTube) and 'youtube_channel_videos' (lists all videos without a query).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for channel-specific search but does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives. Context from sibling tools helps but the description itself lacks this clarity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral traits. It states the return is a 'normalized public host profile' and lists fields, but does not explicitly mention that the operation is read-only, idempotent, or any potential errors. Adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that front-loads the purpose and key returned fields. Every word adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description adequately lists the returned fields. However, it could mention error handling (e.g., invalid ID) or clarify that only public data is returned, but overall it is fairly complete for a simple profile retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'id' is described in the schema as 'Host id (numeric)'. The description adds no additional meaning beyond what the schema already provides, meeting the baseline for 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'Airbnb host profile'. It lists specific returned fields, distinguishing it from sibling tools like airbnb_host_listings and airbnb_host_reviews which retrieve different data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool is for retrieving a host's public profile, but it does not explicitly state when to use it over alternatives or provide prerequisites. No when-not-to-use guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses pagination behavior (first page from profile, deeper pages from portfolio) but lacks details on read-only nature, authorization, rate limits, or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (2 parameters, no output schema), the description covers core functionality well. Minor omissions: no mention of return format, error handling, or data limits.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters. The description adds no additional meaning beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('Airbnb host listings'), clearly distinguishing it from sibling tools like airbnb_room or airbnb_host. It also mentions pagination, providing strong clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining a host's listings, but does not explicitly state when to use this tool over alternatives (e.g., airbnb_room for individual listings) or any prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It states the tool returns upcoming broadcasts, is paginated, and credential-free, but lacks details on rate limits, data freshness, error handling, or what happens when no upcoming episodes exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loads the core purpose, and includes only essential information without redundancy. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description lists the return fields and mentions pagination and ordering. It also identifies the data source (AniList). However, it does not specify the format of time fields (e.g., UTC offset) or countdown units, leaving minor gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description does not need to add more, but it does not provide additional context beyond what the schema already offers (page defaults, per_page max). The description's mention of pagination and ordering is tool-level, not parameter-level.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as providing an upcoming anime airing schedule with specific return fields (episode number, air time, countdown, normalized title) and ordering (soonest first). It distinguishes itself from sibling anime tools like anime_search or anime_rankings by focusing on the schedule aspect.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions it is credential-free, implying easy access, but does not provide explicit guidance on when to use this tool versus alternatives like anime_search for finding specific anime or anime_rankings for popularity. There is no mention of when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It states the tool is read-only ('List'), returns paginated results with ratings and media entries, and is 'credential-free public AniList data', which communicates that no authentication is needed. However, it does not mention error handling, rate limits, or default sorting, but these are minor omissions for a simple read tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences. The first sentence states the core purpose, and the second adds key details (returns, rating, media entry, pagination, credential-free). Every sentence adds value; no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 3 parameters, no output schema, and no nested objects, the description sufficiently covers the tool's behavior: it lists recommendations with ratings and media entries, is paginated, and uses public data. It omits some details like error responses or output format, but for a straightforward list tool, it is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers all 3 parameters with descriptions (100% coverage). The tool description does not add meaning beyond the schema; it simply restates that the 'id' is the anime ID. For high schema coverage, baseline is 3, and no extra value is provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists anime recommendations, specifying the verb 'list' and the resource 'anime's recommendations'. It differentiates from sibling tools like anime_title, anime_title_characters, and anime_title_staff by focusing solely on recommendations, and includes details about returned data (rating, normalized media entry, pagination).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention when not to use it, nor does it compare it to other anime tools like anime_search or anime_title. The phrase 'Credential-free public AniList data' implies it's a public API, but this is not a clear usage guideline.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosing behavior. It adds value by specifying the source ('public catalog page') and the normalized fields returned (ISBN, page count, publisher, audience, rating histogram, series linkage). However, it does not explicitly state that this is a read-only operation, nor does it mention rate limits, authentication, or error behavior, leaving some gaps for a no-annotation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise: two sentences that front-load the action and resource, followed by a list of key metadata fields. Every word contributes to understanding, with no redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool, the description is complete: it states the purpose, the source, and the kind of data returned. The schema documents the parameters, and the description enumerates key output fields even in the absence of an output schema. It does not detail response structure or how to obtain the ID, but that is not essential for basic use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers all three parameters (id, lang, country) with descriptions, achieving 100% coverage. The tool description does not add any additional meaning to these parameters beyond what the schema already provides, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Apple Books book details, using the specific verb 'Retrieve' and resource 'Apple Books book details'. It distinguishes from sibling tools like apple_books_audiobook, apple_books_book_reviews, and apple_books_book_similar by focusing on the book's metadata, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for retrieving book metadata from a public catalog page, which provides context for when to use it. However, it does not explicitly mention when not to use it or name alternatives (e.g., 'for reviews, use apple_books_book_reviews'), so guidance is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It discloses that the tool returns related books from the Apple Books catalog page, which is useful, but it omits behavioral details such as pagination, result limits, ordering, or how lang and country affect results. This is acceptable for a simple read-only lookup but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences with the key verb and resource front-loaded. There is no filler or redundancy, and each sentence contributes either the primary purpose or the source context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity retrieval tool with full schema coverage, the description adequately conveys what is returned and from where. It lacks explicit mention of the output shape or list behavior, and since no output schema exists to offload that, this is a minor but not critical gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides descriptions for all three parameters (100% coverage), including the numeric book ID, language tag, and two-letter storefront country code. The description adds no parameter-specific meaning beyond the schema, so it meets but does not exceed the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb, 'Retrieve,' and identifies the resource as 'Customers Also Bought' books from the Apple Books catalog page. This clearly distinguishes it from sibling tools like apple_books_book (detail lookup), apple_books_book_reviews, and apple_books_audiobook_similar.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the usage context through the 'Customers Also Bought' phrasing, but it does not explicitly state when to choose this tool over alternatives or when not to use it. There are no exclusion or alternative mentions, though a user can reasonably infer this is for finding related books from a specific book ID.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry behavioral disclosure. It states the data source is Apple Books' public catalog page, implying read-only public access, and specifies that it returns metadata and the full ordered list. However, it does not explicitly state that the operation is read-only, has no side effects, or requires no authentication, nor does it mention potential pagination or rate limits. The 'full ordered list' detail adds useful behavior, but gaps remain.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only two sentences, front-loaded with the action and resource, and includes essential return information. Every word earns its place; there is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a straightforward retrieval tool with a fully documented schema, the description adequately covers purpose, return type, and data source. It does not explain how optional parameters like lang and country affect results, but the schema already does so. The lack of an output schema is mitigated by the clear statement that series metadata and the full ordered book list are returned.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% parameter coverage: id is described as an Apple Books numeric series ID, lang as a result language tag, and country as a two-letter storefront country code. The description adds no additional meaning beyond restating the purpose, so the baseline of 3 for full schema coverage is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('Retrieve') and resource ('an Apple Books series and its full book list'), making it distinct from siblings like apple_books_audiobook_series by specifying 'book list' rather than audiobooks. It also notes the return of series metadata and the ordered list, which removes ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (when series data and book lists are needed) and provides context via 'from Apple Books' public catalog page', but it offers no explicit guidance on alternatives or exclusions. It does not mention sibling tools like apple_books_book or apple_books_audiobook_series, leaving the agent to infer usage from purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the data source ('modern podcasts.apple.com show page's listener-cohort recommendation data') and the return type ('You Might Also Like' rail), which is useful. However, it does not mention potential limitations like scraping fragility, rate limits, or error behavior, leaving gaps in behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary action, and contains no fluff. Every word contributes value by specifying the tool's purpose and data source. It is appropriately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description explains what is returned (the 'You Might Also Like' rail) and adds context about the data source. It is reasonably complete for a simple tool, though it could slightly clarify the shape of the return (e.g., array of show objects), but this is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description does not add meaning beyond the schema; all parameter details (id, limit, country) are already fully described in the input schema. The description does not provide any extra context about parameter usage or relationships.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Apple Podcasts 'You Might Also Like' related shows for a single show. It uses a specific verb ('Retrieve'), names the exact resource (related shows), and distinguishes itself from sibling tools like apple_podcasts_show and apple_podcasts_show_episodes by referencing the 'You Might Also Like' rail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (needs a single show's ID) and specifies the scope ('for a single show'), but does not explicitly mention when to use this tool over alternatives or exclude other tools. It lacks a direct 'when-not' or alternative tool reference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations. Description mentions return content but lacks details on behavior like pagination, limits, or error cases. Adequate for a read tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with purpose, no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Describes what is returned (version history entries). No output schema, but tool is simple. Could mention pagination or limits, but overall adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameters with descriptions. Description adds no additional parameter info, baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states action 'Retrieve App Store version history' and specifies it returns the entries shown in the 'What's New' section. Distinct from sibling tools like appstore_app.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives. Implied usage for version history, but no when-not-to-use or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden. It reveals key behavior: returns up to 24 results, uses normalized listing fields, and returns an empty list for out-of-range pages rather than an error. It does not cover auth or rate limits, but the read-only search context makes this omission acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at two sentences, front-loads the search-and-return behavior, and provides all parameter semantics without filler. It is slightly dense but well-structured for the complexity of a two-parameter search tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Since there is no output schema, the description covers the needed ground: it enumerates output fields, page size, and the page-past-end behavior. It does not describe ordering, sort options, or error conditions for malformed input, but for a straightforward search endpoint the call semantics are largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for both parameters, but the description adds meaning beyond the schema: q is described as 'free-text search keywords' with a concrete example, and page not only has its 1-indexed default clarified but also the edge-case behavior of out-of-range pages returning an empty list. This added context is genuinely useful.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches Best Buy's product catalog and explicitly lists what it returns (sku, title, url, image, price, rating, review count), so an agent can grasp the scope. It stops short of explicitly differentiating itself from sibling tools like bestbuy_product, but the 'search' verb and catalog scope make the function's role clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool: when you need a keyword search over Best Buy's catalog, with q as free-text search and pagination via page. It provides an example query and explains pagination behavior, but it does not mention alternatives or explicitly say when to use another tool like bestbuy_product.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that results are scraped from HTML pages and may return 503 errors on challenges. This adds behavioral context beyond the schema. However, since no annotations are present, the description carries full burden and could disclose more about expected response structure, latency, or usage restrictions. The scraping approach is a key behavioral trait adequately covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at three sentences, with the primary purpose in the first sentence. Each sentence adds distinct value: purpose, locale defaults, and error behavior. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description adequately covers the tool's purpose, source of data, and key error behavior. However, without an output schema, it does not describe the return format or fields, which could help an agent interpret results. Pagination is implied by page and count but not elaborated. Overall, it covers most essential aspects for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers all parameters with descriptions. The description adds the default values for country and lang (us, en-us) and implies they are linked via 'locale defaults'. This provides additional semantic context about how the parameters work together. For page and count, the schema already specifies defaults and ranges, so the description adds minimal extra. Overall, it enhances understanding of parameter initialization.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool's action ('Search Bing video results') and resource (video results from Bing). It also clarifies that results are normalized and sourced from Bing's video HTML pages. Among siblings like bing_images and bing_news, it clearly differentiates by focusing on videos.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lacks explicit usage guidelines such as when to use this tool versus alternatives like bing_search or bing_images. It does not provide context on when not to use it or what other tools might be better suited for broader searches. The only guidance is technical (locale defaults and error handling).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It lists what is returned and frames it as a 'core detail page', which clarifies scope but does not disclose limitations (e.g., 'does not include reviews' or 'requires prior search') or operational details like data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that front-load the purpose and enumerate contents without unnecessary words. Every part adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lists the main return components, which is helpful since there is no output schema. It is fairly complete for a simple single-parameter retrieval tool, though 'core detail page' is slightly vague and could explicitly mention what is NOT included.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description does not add parameter semantics beyond the schema, but the schema already fully documents hotel_id.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a Booking.com hotel's core detail page, enumerating specific content (rating, facilities, highlights, house rules, cover photos, rooms with photos). This specific verb+resource distinguishes it from sibling tools like booking_search and booking_reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly say when to use this tool vs alternatives. The schema hint ('from a prior search's property id') implies usage after booking_search, but the description itself lacks explicit guidance or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It usefully discloses that empty pages return a typed not-found error instead of empty success, but does not mention other behaviors like rate limits, authentication, or what 'normalized rows' entail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences efficiently convey the purpose and an important behavioral note, with no extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core functionality and error behavior, but given the lack of annotations and output schema, additional details about the return format or row structure would enhance completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, the description adds no extra meaning beyond the schema's description of the 'date' parameter. A baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns domestic daily box office data ('domestic daily box office') and differentiates from sibling tools like weekend or yearly variants by specifying 'daily' and referencing 'Box Office Mojo's public domestic daily chart'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for retrieving daily box office data for a specific date, but does not provide explicit guidance on when to use this tool versus alternatives (e.g., boxofficemojo_weekend_domestic) or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description mentions output as 'normalized release-group rows' but lacks details on data freshness, rate limits, or other behavioral traits beyond the implied read-only nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, zero waste. Every sentence is informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With only one parameter and no output schema, the description adequately explains the tool's purpose and return type. Missing some behavioral details, but sufficient for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a descriptive parameter comment ('Box office year, from 1977 through 2100'). The description adds no new meaning beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns 'normalized release-group rows from Box Office Mojo's public worldwide yearly chart', and the tool name includes 'worldwide', distinguishing it from siblings like boxofficemojo_year_domestic.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description implies use for worldwide yearly box office data but provides no explicit when-to-use or when-not-to-use guidance compared to alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Given no annotations, the description carries full burden. It describes returned results comprehensively (web results, pagination, related queries, etc.) and mentions pagination offset. Missing info on auth, rate limits, or read-only nature, but the detail provided is substantial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences: purpose, time filtering guidance, locale defaults. No unnecessary words, but could be slightly more structured (e.g., separate sections for return types and parameters).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, so description compensates by listing return types (web results, pagination, etc.). Parameter coverage is good with usage tips. However, it lacks any mention of error handling, rate limits, or authentication, which would be beneficial given no annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage, but description adds value beyond schema by explaining how time_range and date_from/date_to work together, and explicitly mentioning locale defaults. This helps users understand parameter relationships and defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search Brave' and lists returned items (web results, pagination, related queries, discussions, videos, knowledge card). However, it does not explicitly differentiate from other search siblings like google_search or bing_search, which have similar features.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides guidance on time filters (time_range vs date_from/date_to) and defaults for locale, but no advice on when to choose Brave Search over alternatives such as google_search or bing_search.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions return fields and parameter defaults but does not disclose behavior like pagination, rate limits, authentication requirements, or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. The first sentence concisely states purpose and output; the second provides defaults. Front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description lists return fields and defaults, which is good. However, it lacks information on pagination, error handling, or whether the tool supports additional search parameters. Adequate for a simple search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are documented. The description adds value by stating default values for num, country, and lang, which are not in the schema. This helps agents understand expected behavior without guessing defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches Chrome Web Store items and returns search result cards with specific fields (id, name, rating, etc.). It distinguishes from sibling tools like chromewebstore_categories or chromewebstore_item by focusing on keyword search with defaults.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for keyword-based search but does not explicitly state when to use this vs other chromewebstore tools like chromewebstore_suggest or chromewebstore_collection. Defaults are provided but no exclusions or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does disclose that the data is public from Costco's own search backend and that the output includes category slugs and product counts, which adds useful context. However, it does not mention rate limits, authentication, or potential caveats about the returned data (e.g., whether categories are hierarchical or limited). For a simple read-only retrieval tool, this is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, each adding value: the first states the primary purpose, the second explains the output and its relation to the search endpoint, and the third notes the public data source. It is front-loaded, concise, and free of unnecessary fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description must explain both the output and any important context. It describes the return values (category slugs and product counts), the optional query parameter, and the data source. It does not explicitly state what happens when no query is provided (though it implies all categories are returned), nor does it mention pagination or limits. For a tool of this complexity, it is reasonably complete but could be more explicit about the default behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter, 'query', whose description is truncated ('Search text to scope the returned categories to, e.g. \"'), so the schema itself provides limited semantic value. The tool description clarifies that the search term is optional and scopes the returned categories, adding some meaning. However, it does not provide example values or specify the expected format beyond the truncated schema text. Since schema coverage is 100%, the baseline is 3, and the description adds only marginal value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Get Costco category facets' and further clarifies that it returns category slugs and product counts scoped by an optional search term. It also notes that the slugs are directly usable with the search endpoint, which differentiates it from other Costco tools like costco_search and costco_product. The verb+resource is specific and distinguishable from siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a usage pattern by stating that slugs are usable directly with GET /costco/search's category filter, suggesting a workflow for filtering searches. However, it does not explicitly state when to use this tool versus alternatives like costco_search or costco_product, nor does it provide exclusions or explicit when-not-to-use guidance. The context is somewhat clear but not fully explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavioral traits. It notes the tool returns 'a page' of reviews and that data is public, offering some context, but it does not explain pagination behavior, error conditions, or confirm that this is a read-only operation beyond the word 'Get'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two tightly written sentences front-load the purpose and enumerate the output fields without extraneous detail. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter read operation, the description covers purpose, return content, and data provenance. It falls short only in not addressing pagination mechanics or next-page behavior, which would be helpful for an agent processing multiple pages.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents the single 'id' parameter with 100% coverage, including guidance on sourcing it from a search result. The description adds only general references to 'a Costco product', offering no additional detail about format or constraints beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb ('Get') and a clear resource ('a Costco product's reviews'), immediately distinguishing this tool from siblings like costco_search or costco_product. It also enumerates the returned fields, leaving no ambiguity about what the tool produces.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for retrieving reviews for a specific product, but provides no explicit guidance on when to prefer it over related Costco tools or how to obtain the required id beyond the schema note. No alternatives or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that suspected-automation records are excluded by default unless the parameter is set, but lacks details on rate limits, authentication, output format, or other behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise sentences, front-loaded with purpose. Every sentence adds value, with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 29 parameters and complex filtering, the description is minimal. It covers the main facet enums but lacks explanation of output structure, pagination, or other defaults, leaving gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. The description adds value by listing the facet and influence_tier enum values and explaining the default exclusion behavior, providing context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that it facets the GitHub users dataset and returns terms aggregation counts. It lists the specific facet enums, distinguishing it from search or item retrieval tools in the sibling list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for aggregation counts but does not explicitly contrast with alternatives like datasets_github_users_search or datasets_github_users_item. No when-to-use or when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It openly discloses the dataset's incomplete coverage and crawl-derived nature, which is useful behavioral context. But it does not describe return format, pagination behavior, or side effects, and the sort enum is redundant with the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences and front-loaded with the primary action. The coverage caveat is valuable, but the sort enum sentence is redundant with the schema and could be trimmed without losing meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 9 optional parameters and no output schema, the description adequately introduces the resource and its caveats, but it falls short of explaining what results are returned or how the search relates to sibling tools like datasets_goodreads_authors_item. The schema covers parameter details, so the main gap is missing output/response context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds no parameter meaning beyond the schema; it only repeats the sort enum values already defined in the 'sort' parameter description. No extra guidance on how to combine parameters is provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Search Goodreads authors dataset' and 'Searches the crawled public Goodreads author profile index.' It clearly distinguishes this search tool from sibling item/facets tools by emphasizing it searches an index and noting the dataset's provenance.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context about the dataset's scope: 'Authors are discovered as a byproduct of the books crawl... not a full catalog.' This tells the user when to expect limitations, effectively guiding against using this tool for authoritative/full-catalog author searches. However, it does not explicitly name alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It states the primary behavior (returns terms aggregation counts), which implies a read-only operation. However, it does not disclose any other behavioral traits such as default limits, pagination, or interaction between multiple filter parameters. The description is not misleading but could be richer.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loads the key purpose, and contains zero wasted words. Every sentence adds meaningful information about the tool's function and required facet values.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the 8-parameter schema with 100% coverage and no output schema, the description explains the core function (returns terms aggregation counts) and the required facet parameter. It does not explain response shape in detail, but the phrase 'terms aggregation counts' gives sufficient context for a facet endpoint. The tool appears complete for its purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description repeats the facet enum values which are already in the schema's facet parameter description. It does not add any new parameter semantics beyond what the schema provides, so a 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Returns terms aggregation counts for the PitchBook advisors dataset.' It clearly distinguishes itself from sibling tools like search (datasets_pitchbook_advisors_search) and item (datasets_pitchbook_advisors_item) by focusing on faceted aggregation. Listing the facet enum (service_type, hq_country, hq_state, run_id) further specifies the exact scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: you call this tool when you need facet counts, and you must supply a facet from the listed enum. However, it does not explicitly state when to prefer this over search/item tools, nor does it mention any exclusions. It provides the required enum but lacks explicit alternatives or when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It adds some useful context by noting the data is 'crawled' and from a specific dataset (`pitchbook-companies`). However, it does not disclose error behavior, rate limits, or output format, which could be relevant for an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with two sentences that front-load the main action ('Get a PitchBook company from dataset') and then provide necessary specifics. There is no fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple item-fetch tool with one parameter and no output schema, the description is reasonably complete. It states the return type ('one record'), the dataset id, and the lookup key ('by id'). It could be slightly more complete by mentioning how to obtain the id (e.g., via search) or what the record contains, but this is not a major gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter (`id`) with full description coverage (100%), including an example. The tool description adds minimal semantic value by referencing 'by id' and the dataset id, but does not meaningfully elaborate on the parameter beyond what the schema already provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get a PitchBook company from dataset' and specifies it returns one record by id from a specific dataset (`pitchbook-companies`). This distinguishes it from sibling tools like `datasets_pitchbook_companies_search` and `datasets_pitchbook_companies_facets`.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the usage context by requiring an id ('Returns one... record by id'), which signals that the user must have a specific PitchBook id. However, it does not explicitly state when to use this tool instead of alternatives like search or facets, nor does it mention prerequisites beyond the id.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses that records are 'crawled' and that the tool returns a single record, which gives some context. However, it does not mention error behavior (e.g., not-found cases), rate limits, or completeness of data, though for a simple getter this is acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the action, and contains no filler. Every phrase earns its place, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with one parameter and no output schema, the description provides adequate context: it states what is returned, how it is identified, and the dataset source. It could mention behavior when the id is not found, but that is a minor gap for such a focused getter.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%: the 'id' parameter already has a clear description with an example. The description adds 'from dataset id enum value' which contextualizes the dataset but does not add new meaning to the parameter itself. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the operation: 'Get a PitchBook investor from dataset' and specifies it returns one record by id. It names the specific dataset ('pitchbook-investors'), which distinguishes it from sibling search/facets tools and other PitchBook item tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used when you have a specific investor id (since it says 'by id'), but it does not explicitly state when to use it vs alternatives like datasets_pitchbook_investors_search or datasets_pitchbook_investors_facets. No exclusion criteria or alternative tool names are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that data comes from a crawl of PitchBook's public sitemap and preemptively explains that missing FAQ sections are normal. This adds useful behavioral context beyond the raw schema, though it does not cover all possible traits (e.g., pagination limits, data completeness).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is about 60 words and front-loads the primary purpose with the first sentence. Some redundancy exists (e.g., 'Discovered from PitchBook's public sitemap' restates 'crawled public', and the sort enum duplicates schema info), but it remains concise and logically structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with 10 optional parameters and no output schema, the description provides dataset context and a data-quality caveat. However, it lacks an explicit note about typical return format or result pagination (beyond what the schema states) and gives no examples. It is adequate but leaves the agent to infer several operational details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of parameters with descriptions, so the baseline is 3. The description only repeats the sort enum values already present in the schema and does not add new meaning to fields like `q`, `hq_country`, or `institution_type`. It adds no value beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Search PitchBook limited partners dataset' and then specifies it 'Searches the crawled public PitchBook limited partner (institutional investor — e.g. pension fund, endowment, insurance company) profile catalog stored in a search index.' This gives a specific verb (search) and resource (PitchBook LP catalog), clearly distinguishing it from sibling item/facets tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for searching the public LP catalog and provides context about the data source, but it never explicitly states when to use this tool versus alternatives like datasets_pitchbook_limited_partners_item or facets. There are no clear 'when not to use' statements or references to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states that the tool returns distribution counts, which implies a read-only operation. It mentions honoring search filters, implying consistency. However, it does not disclose potential limitations like maximum facet buckets, zero-count handling, or pagination behavior. This leaves some behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loaded with the core action, and contains no unnecessary words. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema is provided. The description states 'returns distribution counts' but gives no hint of the response format (e.g., array of objects with value and count). Given the tool's complexity and lack of output schema, the description should elaborate on what the distribution counts look like.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description does not add meaning to individual parameters beyond the schema. It only reinforces that the same filters as search apply, which is useful context but does not provide additional semantics for the parameter values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool facets the Product Hunt products dataset, returns distribution counts, and lists the exact facet enums (topic, launch_year, pricing_type, product_state). It specifies the dataset ID and distinguishes from search by noting it honors the same filters. This leaves no ambiguity about the tool's function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states it 'honors the same filters as search', providing clear context that this tool is for aggregation after defining search filters. However, it does not explicitly state when to use this tool instead of search or item retrieval, nor does it mention alternatives. The guidance is good but could be more comprehensive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does well: it discloses the return fields (launch history, description, website, twitter_url, pricing, makers) and the 404 error condition. It lacks details on authentication or rate limits, but for a simple get operation this is quite transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exactly two sentences, front-loaded with the main purpose and followed by the error condition. Every word earns its place, with no fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter item fetch with no output schema, the description covers the essential context: what is returned, the dataset identifier, and the 404 case. The term 'once hydrated' is slightly ambiguous but does not detract from overall completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides 100% coverage for the only parameter `slug` with a clear example. The description reiterates the slug concept but does not add significant meaning beyond the schema, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets a Product Hunt product from the dataset by slug, which is specific and actionable. It distinguishes itself from live Product Hunt tools by mentioning 'dataset' and 'archive', but does not explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for archived dataset products, but does not explicitly state when to use this tool over the sibling producthunt_product or when not to use it. No alternatives or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that fields like description/website/pricing/makers are filled in via hydration runs, and states each result contains topics, upvotes, ranks, and launch history. This adds meaningful behavioral context beyond the bare operation, though it lacks details on pagination limits or authentication.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively compact at four sentences, starting with the core purpose. However, it repeats the word 'Searches' in the second sentence and duplicates the sort enum already documented in the schema, which slightly reduces efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description gives a solid overview of result contents and hydration behavior, but with 13 optional parameters and no output schema, it lacks guidance on default behavior when no query is supplied, and does not explain the relationship to related facet/item tools. Some expectations like pagination limits are left to the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description restates the sort enum already present in the schema and adds a note about hydration for maker/topic fields, but does not introduce new parameter format or syntax details beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a search over the Product Hunt products dataset, specifying it searches individual launches from the `producthunt-products` dataset. It distinguishes from sibling tools like datasets_producthunt_makers_search by focusing on products and launches.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a search use case but does not explicitly state when to prefer this over siblings like datasets_producthunt_products_item or datasets_producthunt_products_facets. No alternatives or exclusions are mentioned, leaving the agent to infer from the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that counts are 'suppressed' and that filtering mirrors search, but does not explain suppression details, rate limits, or other behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences concisely convey purpose and context. Could be slightly tighter by removing the explicit facet enum listing, but overall efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, so description should detail return values. 'Returns suppressed distribution counts' is vague; lacks specifics on response structure, pagination, or limits. Adequate for basic understanding but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description repeats the facet enum values and mentions 'same filters as search', but adds no new meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Facet' and the resource 'Product Hunt trends dataset', and specifies it returns 'suppressed distribution counts'. It distinguishes from sibling 'datasets_producthunt_trends_search' by indicating aggregation vs. search results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states it 'honors the same filters as search', implying when to use this tool (for aggregated counts) vs. the search sibling. It lists the facet enums (topic, launch_year), but does not explicitly exclude scenarios or mention alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the sorting order (most recent first), the return of empty series for missing data, and implies a read-only operation. However, it does not mention authentication or rate limits, which may be less critical for a publicly available company dataset.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two sentences that cover the main purpose, data source, sorting, and error behavior. No wasted words, and key information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 5 parameters and no output schema, the description covers the main functionality, required parameter (CIK), and edge cases (empty results). It lacks details on output structure, but given the standard nature of insider transaction data, this is acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema provides full descriptions for all 5 parameters (100% coverage). The tool description does not add any meaningful detail beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it retrieves insider-transaction history for an SEC company. The purpose is specific and unambiguous, but does not explicitly differentiate from the sibling tool 'sec_insider', which may have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides guidance on expected behavior for unknown CIK or no transactions (empty series, not 404), but does not specify when to use this tool versus alternatives like 'sec_insider' or other dataset tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool returns one enriched record by appid, which is a clear behavioral trait. However, it does not cover edge cases like missing/invalid appid, potential errors, or what 'enriched' includes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the main purpose, and contains no fluff. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (one parameter, no output schema, no annotations), and the description is adequate for a single-record lookup. It covers the core behavior but could be more complete by describing the return structure or error handling, though the low complexity lessens the gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the schema already states that appid is the Steam app id. The description merely repeats 'by appid' without adding new details like format, constraints, or examples, so it stays at the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('Steam game'), and clearly states it returns one record by appid. It also distinguishes itself from sibling tools like datasets_steam_games_search by specifying the lookup key and dataset id enum value.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you have an appid ('by appid'), providing clear context but no explicit alternatives or when-not guidance. It does not mention that search tools should be used when the appid is unknown.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes the dataset structure and filter semantics but lacks details on pagination behavior, rate limiting, output format, or error handling. The description is informative but not fully comprehensive on behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph that is front-loaded with the dataset purpose. It covers all necessary points without unnecessary verbosity. Slightly more structured formatting (e.g., bullet points for filter types) could improve readability, but it remains efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of 20 parameters and no output schema, the description covers the main usage patterns and filter logic well. It is mostly complete but could mention default values (e.g., run_id defaults to latest), pagination constraints, or return format to be fully comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds significant value by explaining the reverse-index filter logic (AND, OR, NOT with technology, any_of, not) and providing an example. This goes beyond individual parameter descriptions to explain how they interact.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches the website tech-stack dataset, explains the dataset content (one record per site listing web technologies), and compares to BuiltWith/Wappalyzer. It does not explicitly distinguish from sibling tools like datasets_techstack_facets or datasets_techstack_item, but the search purpose is evident.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides detailed usage guidance: how to use technology (AND), any_of (OR), and not (exclusion) filters, with an example. It explains the sort enum values and render_tier enum. However, it does not explicitly state when to use this vs siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must bear full behavioral disclosure. It describes the return data but fails to mention that the tool is read-only, idempotent, or any prerequisites (e.g., authentication, rate limits). This is a significant gap for a data retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently conveys the tool's action, input, and output. No extraneous information, and each phrase earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description usefully lists the returned fields (verified revenue/MRR, traffic, etc.) and the dataset ID. It lacks error conditions or response structure, but for a simple single-record lookup, it is mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides 100% coverage for the only parameter (slug) with a clear description. The tool description adds context about the dataset and returned fields but does not enhance the semantic meaning of the slug parameter beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a single TrustMRR startup record by slug, listing the specific fields returned. It distinguishes from sibling tools like datasets_trustmrr_search (search) and datasets_trustmrr_facets (facets) by focusing on a single record lookup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when a specific slug is available, and the returned fields indicate it's for detailed startup data. However, it does not explicitly state when not to use it or mention alternatives like search for unknown slugs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It does disclose that this is public read-only data, uses Depop's dedicated similar-items API, and is paginated up to 150 per page. However, it does not mention rate limits, required auth, return shape, or response size beyond a simple per-page cap, so behavioral transparency is adequate but not strong.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only a few clauses, but it is somewhat repetitive: 'Get Depop items similar to a listing' and 'Returns items similar to a given Depop listing' say the same thing, and 'Depop's dedicated similar-items API' is restated in the final sentence as 'Depop's own similar items API'. The useful comparative and pagination details are between the repeated lines.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema or annotations, the description is complete enough for a developer: it states the resource, the behavior, and the advantage of the richer paginated API, while the schema handles all parameter meanings including the opaque cursor semantics. No critical invocation detail is missing for a straightforward read-only lookup.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents all parameters at 100% coverage, so the baseline is 3. The description's only parameter-related addition is the 'up to 150 per page' limit, which restates the schema's limit max and does not add material semantic meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb+resource: 'Get Depop items similar to a listing.' It also distinguishes the tool from the 'small, non-paginated similar items carousel already included in item detail,' making it clear this is the richer, paginated similar-items endpoint rather than a generic item or search tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly compares this tool to the similar-items carousel that ships with item detail, saying this one is 'richer and paginated upward to 150 per page.' That gives an agent enough context to choose it over the smaller built-in carousel, although it does not name the literal tool or spell out explicitly when to use an alternative instead.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It states the tool returns a 'normalized' profile and lists fields, and is 'credential-free', but lacks details on rate limits, data format, or error handling. Adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with clear front-loading: first sentence states purpose, second details output and adds context. No irrelevance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with one param and no output schema, it is fairly complete: it lists the output fields and notes no credential needed. Could mention error handling or data format, but minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single 'id' parameter with a basic description. The tool description does not add new semantics about the parameter (e.g., how to obtain the id or format). Meets baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('Discogs artist profile') and lists the fields returned (real name, bio, links, etc.). It clearly distinguishes from sibling tools like discogs_artist_releases or discogs_search by focusing on the profile itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions 'Credential-free official Discogs database data' implying no auth needed, but it does not explicitly state when to use this vs alternatives (e.g., discogs_search for finding artists by name, or discogs_artist_releases for releases). No when-not-to-use or alternative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description mentions pagination and credential-free access, which are helpful. However, it does not disclose potential behaviors like rate limits, error handling, ordering, or data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences with no fluff. It front-loads the main action and efficiently communicates the tool's purpose and return fields.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool, the description covers purpose, return fields, pagination, and credential-free access. It lacks details on sorting or default behavior, but is mostly complete given no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents all parameters. The description adds the return fields but does not enhance parameter meaning beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists a Discogs label's releases and specifies the return fields (title, artist, format, catalog number, year). It distinguishes itself from sibling tools like discogs_label (label info) and discogs_artist_releases (artist releases).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives, but the purpose is clear enough that an agent would infer it for label releases. There is no exclusion or when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'Credential-free official Discogs database data', indicating no authentication needed, but does not disclose other behavioral traits such as rate limits, idempotency, or potential data truncation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the action, and contains no redundant information. Every sentence adds value: stating the action, explaining the concept, and noting credential-free access.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is no output schema, the description lists what the response includes (artists, tracklist, genres, etc.) and confirms it is credential-free. It covers key aspects for a simple retrieval tool, though it omits potential error conditions or data availability nuances.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter 'id' described as 'Discogs master release id'. The description adds context about what a master release is but does not provide additional semantic meaning for the parameter beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get a Discogs master release' (specific verb+resource) and explains that a master release is a 'version-agnostic grouping of a release across pressings/reissues', which effectively distinguishes it from the sibling tool 'discogs_release' that would fetch a specific version.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving aggregated release data, but does not explicitly state when to use it versus alternatives like 'discogs_release' or 'discogs_search'. No when-not-to-use or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It mentions the data source (api.discogs.com) and that it is credential-free, which adds some behavioral context. However, it does not disclose rate limits, error handling, or response format details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences, no wasted words, and front-loads the core purpose. Every sentence adds value: first states the action and returned fields, second identifies the authoritative source.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with one required parameter and no output schema, the description adequately lists the returned fields and data source. However, it lacks information about potential errors or response format, leaving minor gaps for an agent to infer.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers the single parameter 'id' with a brief description 'Discogs release id'. The tool description does not add further semantics (e.g., format, example, or where to obtain the ID) beyond what the schema already provides. With 100% schema coverage, a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get a Discogs release' and enumerates the returned data fields (artists, labels, formats, etc.), making the purpose explicit. It distinguishes itself from sibling tools like discogs_search or discogs_artist by focusing on a single release by ID.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a specific Discogs release ID is known, but does not explicitly state when to use this tool versus alternatives such as discogs_search or discogs_master. No when-not-to-use or alternative tool guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that no account/token is required and that it uses the mobile guest flow, which is valuable behavioral context. Yet it does not mention whether it is read-only, what happens on invalid input, or the exact structure of the returned metadata.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two clear sentences, front-loaded with 'Get a DoorDash store' and no wasted words. Every sentence adds meaningful information: purpose, return type, location awareness, and authentication requirements.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-store lookup with 3 fully-described parameters and no output schema, the description is largely complete. It explains the tool's purpose, key behavioral context, and auth requirements. It could elaborate on what 'metadata' includes, but overall it suffices.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds only the 'location-aware' qualifier, which reinforces the role of latitude/longitude but doesn't provide format details beyond the schema. No additional parameter meaning is contributed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with the specific verb 'Get' and resource 'a DoorDash store', then clarifies it returns 'location-aware DoorDash store metadata'. This directly states the tool's function and distinguishes it from sibling tools like doordash_store_menu or doordash_store_reviews by emphasizing the metadata and guest flow.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides useful context ('through the Android mobile guest flow', 'No DoorDash account or caller-supplied token is required') implying this is the public, unauthenticated store lookup. However, it does not explicitly name alternatives or state when not to use it, leaving some room for ambiguity among the many DoorDash sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral disclosure burden. It usefully reveals the data comes from 'DraftKings' credential-free public JSON' and that an empty `events` list is a legitimate response when no markets exist. This adds meaningful behavioral context beyond a basic 'returns markets' statement, even though it omits rate limits, error handling, and full output shape.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences with no filler: the first gives the core purpose, the second defines both parameters, and the third clarifies a likely confusing edge case. The most important context is front-loaded, and every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter read-only tool with no output schema, the description covers the source, scope, identifier semantics, and expected empty-response behavior. It does not explain the output structure beyond 'markets and selections' and `events`, nor where to find subcategory IDs, but it is sufficient for an agent to call the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%; both parameters already include descriptions ('Numeric DraftKings league id' and 'Numeric DraftKings futures market subcategory id'). The description restates that both are numeric identifiers, reinforcing but not materially expanding the schema. Baseline 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb-resource pair: it 'returns league-level futures markets and selections' for a given DraftKings market category. It names 'futures' prominently and clarifies the league-level scope, which helps separate it from event-level or odds-focused DraftKings tools. However, it does not explicitly name or contrast a sibling, leaving some differentiation to inference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for fetching DraftKings futures by league_id and subcategory_id, and it explains both identifiers in context. It does not state when to prefer this over alternatives like draftkings_event_markets or draftkings_odds, nor does it give any when-not-to-use guidance. The empty-events note is a useful edge-case hint, but not a usage directive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses that the data is stable and embedded in a public DraftKings page, which implies a read-only, low-auth operation. However, it does not describe return structure, pagination, or potential failure modes, so behavioral transparency is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded: it states the resource and return value first, then gives parameter provenance and constraints. Every sentence contributes useful information, and there is no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple metadata lookup, the description is mostly sufficient, but there is no output schema and no detail on what fields 'stable team metadata' contains. An agent could call the tool, but may not know what to do with the returned page metadata or how it is structured.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema coverage is 100%, so the schema already documents each parameter. The description adds meaningful cross-parameter semantics by saying all three values should come from a single item returned by /draftkings/sportsbook/teams, and it repeats the allowed sport values, which reinforces correct usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool returns stable team metadata for a DraftKings Sportsbook team, naming the resource and the action. It does not explicitly differentiate from the sibling `draftkings_teams` tool, but the singular/plural distinction and the mention of 'an item returned by /draftkings/sportsbook/teams' make the purpose reasonably distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a concrete usage precondition: supply `team_id`, `sport`, and `slug` from an item returned by /draftkings/sportsbook/teams. It also enumerates the allowed sport values. It does not explicitly say when not to use this tool versus alternatives, but the provenance guidance is strong.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It states that the tool returns only currently live and upcoming streams (not past streams), which is useful behavioral context. It does not disclose pagination behavior or potential limitations, but the schema parameters for pagination provide some clues.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short, focused sentences. The first gives the original action; the second adds necessary scope and constraint. No filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with no output schema, this description is quite complete. It explains what is returned and the category constraint; the schema covers the optional parameters including pagination mechanics. It could mention the output format, but that is minor given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes all three parameters clearly, including defaults and pagination semantics. The description only reinforces 'category channel' without adding meaning beyond the schema, so the baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List') and resource ('eBay Live streams') and adds a specific scope: only currently live and upcoming streams for a category channel. This differentiates it from the singular 'ebay_live_stream' and other related sibling tools, though it does not explicitly name them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies clear usage for retrieving live/upcoming streams filtered by category channel. However, it does not explicitly mention alternatives like 'ebay_live_streams_batch' or 'ebay_live_stream_items' or provide when-not-to-use guidance, so it falls short of a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It discloses that the return value is a 'normalized summaries' batch, and imposes a 9-id capacity. However, it does not mention behavior for invalid IDs, partial errors, or the exact shape/structure of the summaries.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no filler. The main purpose and the batch cap are front-loaded, and every sentence contributes.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter batch-read tool, the description is largely sufficient: it states the ids parameter, the limits, and the type of return ('normalized summaries'). Without an output schema or annotations, it could say more about the summary shape, but it is close to complete for calling correctness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the schema already explains the comma-separated or repeated-query format and the 9-id limit. The description repeats the cap but adds no substantial meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Get') and resource ('multiple eBay Live streams'), and spells out the batch nature with 'in one call, up to 9 ids per request'. This strongly distinguishes it from singular tools like ebay_live_stream or listing tools like ebay_live_streams.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use case is implied: when you need multiple eBay Live stream/event ids fetched in one batch. However, the description never names alternatives or states when not to use it, such as single ID retrieval via ebay_live_stream or listing via ebay_live_streams.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full burden. It states the tool 'gets' data, implying a read operation, and mentions 'normalized' and 'cleaned' output. However, it does not explicitly confirm non-destructive behavior, authentication needs, or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with a clear purpose and a list of return fields. It is front-loaded and concise, with zero wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description covers return values well (stats, top-rated, location, categories). It is sufficient for a simple retrieval tool, though it could mention that the endpoint is public and requires no authentication.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter 'seller' described as 'eBay seller username'. The tool description does not add additional semantic meaning beyond what the schema provides, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get eBay seller about details' and specifies the source and content, including seller stats, top-rated status, location/member-since fields, and cleaned categories. This distinguishes it from sibling tools like ebay_seller, ebay_seller_feedback, and ebay_seller_shop.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when seller about details are needed, but lacks explicit when-not-to-use or alternative suggestions among siblings. No guidance is provided for choosing between this and similar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It mentions the tool is credential-free and returns specific data types (scores, schedule, status, odds). However, it does not disclose pagination, rate limits, or authentication requirements beyond being public.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise paragraph covering all key points without excessive verbosity. It could be slightly more structured (e.g., bullet points for enums), but it efficiently conveys purpose and parameter details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately states the return data (scores, schedule, status, odds). However, it omits details like response structure, field names, or possible empty results, which would improve completeness for a 5-parameter tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds value by explaining the season type enum values and providing examples for dates. It also lists the sport and league enums explicitly, which is helpful beyond the schema's brief property descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns games with scores, schedule, status, and odds for a specified sport and league. It specifies the source (ESPN credential-free public JSON) and enumerates the sports and league enums, making it distinct from sibling tools like espn_team or espn_game_summary.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides details on parameter constraints (e.g., league must be valid for sport, seasontype enums) and notes that week is for football leagues. However, it lacks explicit guidance on when to use this tool versus alternatives like espn_game_summary or espn_standings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the burden. It discloses the output nature (typeahead suggestions) but does not mention whether the operation is read-only, any normalization details, rate limits, or error behavior. It implies a safe search operation, but additional behavioral context would be expected given zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, about 20 words, with the primary purpose front-loaded in the first sentence. It conveys the search target, the types of results, and the input requirement without any fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has one opaque nested parameter with no defined properties, no output schema, and no annotations. The description explains what the tool does but does not provide the essential information about how to construct the 'option' payload, leaving the agent without enough details to invoke the tool correctly. This is a significant gap for a tool with such an unspecified schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% description coverage, but the parameter description ('Location search payload') is tautological. The tool description adds the phrase 'for a free-text term', which gives a hint about the payload's content, but does not specify the internal structure of the 'option' object (e.g., expected fields like 'text'). With high schema coverage the baseline is 3, and the description provides only marginal added meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Search') and resource ('Expedia destinations'), and further specifies the return type: 'normalized destination/property typeahead suggestions (cities, airports, neighborhoods, hotels)'. This clearly distinguishes it from sibling tools like expedia_properties_search, expedia_flights_search, and expedia_activities_search, which cover different Expedia search domains.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context: it is for typeahead destination suggestions for a free-text term, listing the categories of results. However, it does not explicitly state when to use this tool over alternatives or exclude specific use cases (e.g., 'use expedia_properties_search for property availability'). This is clear context but lacks explicit differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the transparency burden. It lists the output fields, but it doesn't disclose potential errors, rate limits, or how invalid IDs are handled. It also doesn't specify the structure of the required 'option' payload, which is a significant behavioral gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the tool name and primary purpose, and includes specific output fields. Every word adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has one nested parameter, no annotations, and no output schema. The description conveys the main output fields and the need for a property ID, but lacks details on how to populate the option payload and any additional prerequisites or error conditions. This leaves the tool mostly usable but incomplete for a fully autonomous agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one parameter 'option' described as 'Property detail payload', which is vague and provides no field names or structure. The tool description mentions 'known property id' but doesn't explain how to include it in the payload. The description fails to compensate for the schema's lack of detail, making it hard for an agent to construct the argument correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a hotel's detail summary (name, star rating, address/coordinates, top amenities) for a known property ID. It distinguishes from sibling tools like expedia_properties_search (finding properties) and expedia_properties_reviews (reviews) by focusing on the detail summary.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for a known property id' implies a prerequisite of already having the ID (e.g., from a search tool), which gives clear usage context. However, it doesn't explicitly mention alternatives or when not to use it, such as when seeking reviews or availability.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose the limited scope ('highlighted/recent') but omits any statement about read-only nature, auth requirements, rate limits, pagination, or error behavior. For a read operation this is acceptable but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loads the purpose, and includes only essential details about inputs and outputs. Every word earns its place, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema, the description explains return values (overall rating, review fields) and the input prerequisite. It misses details on pagination or number of reviews, but for a straightforward retrieval tool it is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single 'option' object described as 'Property reviews payload'. The description adds that this payload requires a known property ID, which gives some semantic meaning beyond the schema's generic label. However, the structure of the payload is not detailed, so the added value is modest.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Returns') and clearly identifies the resource ('Expedia Stays property guest reviews') with concrete output details (overall rating, highlighted/recent reviews with reviewer, date, rating, message). It also distinguishes itself from sibling review tools by naming the platform and property-id prerequisite.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for a known property id' implies a prerequisite (obtain the ID first), but the description does not explicitly state when to use this tool versus alternatives like expedia_properties_detail or search, nor does it mention exclusions or failover options. Usage context is implied but not fully articulated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals that data comes from Fiverr's server-rendered pages via a real browser-rendering backend, which hints at potential latency and dependence on page structure. However, it stops short of declaring read-only status, rate limits, or error behavior, leaving some unknowns for the agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three crisp sentences: action, return payload list, and data-source note. All content is substantive with no repetition or filler, and the verb is front-loaded. This is a model of concise, well-structured tool documentation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Even without an output schema, the description lists the core returned attributes (title, description, packages, rating, orders, tags, gallery, seller summary), giving the agent a solid mental model of the response. It does not cover edge cases like missing optional fields or page-load failures, but the schema fully documents the two required parameters, making this adequate for a read-only detail fetch.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both 'slug' and 'username' accurately described (e.g., slug is 'the trailing path segment after the username'). The tool description adds no further parameter-level explanation beyond the schema, so it meets the baseline for high coverage without enhancing semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description begins with 'Get Fiverr gig detail,' a specific verb-resource pair, and enumerates the exact return fields (title, description, pricing packages, rating, etc.). This clearly delineates it from sibling tools like fiverr_search (which searches) and fiverr_seller (which covers seller profiles), leaving no ambiguity about its purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use whenever a gig detail is needed and provides context about the data source ('normalized,' 'server-rendered'), but it does not explicitly contrast with alternatives such as fiverr_search or fiverr_seller, nor state when not to use this tool. The guidance is implicit rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions the tool returns 'typed Nominatim JSONv2 places' but does not disclose any behavioral traits like rate limits, authentication requirements, or side effects. The description is adequate but lacks depth about the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at 24 words across two sentences. It front-loads the key action and resource, provides a specific example, and contains no filler. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description adequately explains the return format ('typed Nominatim JSONv2 places'). All 5 parameters are described in the schema. However, the tool could benefit from a brief note clarifying its distinct use case among sibling geocoding tools, though it is still sufficiently complete for a straightforward lookup.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond the schema; it only provides an example of OSM ID format. The schema already defines each parameter clearly, so the description does not enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Lookup Nominatim OSM ids' and specifies the return type 'typed Nominatim JSONv2 places'. It provides concrete examples of OSM ID formats, making it distinct from sibling tools like geocoding_search and geocoding_reverse.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you have OSM IDs ('comma-separated OSM ids') but does not explicitly state when to use this tool over alternatives or include any exclusion criteria. No guidance on best practices or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the returned data (language byte breakdown sorted by bytes descending) but does not address side effects, rate limits, or error conditions. For a read-only tool, this is adequate but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loading the purpose and adding detail on the output format. No extraneous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (2 params, no output schema), the description is complete enough: it states input requirements and output format. It would benefit from noting if the response is a map or list, but it's still functional.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers both parameters with clear descriptions (owner, repo). The description does not add additional semantics beyond what the schema provides. With 100% schema coverage, baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a repository's language breakdown, sorted by bytes descending. It specifies the resource (repository) and action, distinguishing it from sibling tools like github_repo or github_repo_contributors.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives like github_repo (which returns general repo info). It only implies usage for language analysis, but lacks explicit guidance on when-not or alternative mentions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'returns a page' which aligns with pagination parameters, but does not disclose rate limits, authentication needs, or output format details like response structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no redundancy. Front-loaded with action and resource, followed by a clarifying parenthetical. Every sentence is purposeful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given moderate complexity and good schema coverage, the description is fairly complete: it states the action, the result, and the pagination aspect. The 'momentum/health signal' adds helpful context. Could mention what happens when no releases exist, but not critical for this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all parameters. The description adds no additional detail beyond the schema, so it meets the baseline but fails to add extra context for parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'List' and resource 'releases', clearly indicating its function. It also adds context about releases as a momentum/health signal, distinguishing it from sibling tools like github_repo or github_org_repos.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing to list releases but lacks explicit guidance on when to use this tool versus alternatives. No when-not-to-use or alternative recommendations are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavioral traits. It reveals pagination behavior (auto-fetch multiple pages unless paginate=true) and the existence of a next_pagination_token, but does not explain how to use the token, rate limits, or that reviews are read-only. This is adequate but incomplete for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, front-loaded with the core purpose. Every sentence is useful and contains no filler. The structure is efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 7 parameters, no output schema, and no annotations, the description is too brief. It lacks details on the return format (e.g., review content, star ratings, dates) and full pagination flow (how to use next_pagination_token). This leaves significant gaps for an agent to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds meaning to the paginate parameter by clarifying its effect ('only the requested page') beyond the schema. Other parameters are well-described in the schema already, so the description adds minimal additional value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Google Play reviews, with a specific verb ('Retrieve') and resource ('Google Play reviews'). It distinguishes from sibling tools like googleplay_app (app details) and googleplay_search (app search) by focusing on reviews. The mention of pages adds specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides guidance on pagination behavior ('Set `paginate=true` to fetch only the requested page'), which helps the agent decide when to use this parameter. However, it does not explicitly state when to use this tool over alternatives like appstore_reviews or other Google Play tools, missing cross-tool guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states 'Returns up to 10 suggestions', which adds some behavioral info, but lacks details on idempotency, rate limits, or results structure. It is minimally adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the action and result. No extraneous words. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (3 params, no output schema), the description is adequate. It covers the core behavior and constraint (up to 10). Slight lack of output format info, but acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds context that the tool returns suggestions for a 'search term', but does not add meaning beyond the schema for 'country' and 'lang'. No value added beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves Google Play query suggestions, distinguishing it from siblings like google_suggest (Google web) and googleplay_search (search results). The verb 'Retrieve' and resource 'Google Play query suggestions' is specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives such as googleplay_search or google_suggest. It only implies use when query suggestions are needed, but no when-not or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but the description fully discloses behavior: proxied browser rendering, concurrent renders, stale-cache fallback, and error codes for 503 and 429 with rate limit details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph containing essential details like error handling and rate limiting, but it could be more structured (e.g., bullet points). It is concise and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a complex nested parameter and no output schema or annotations, the description should explain parameter usage and output format. It only covers error codes and rate limit, leaving parameter semantics and return values unexplained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% but the schema description for 'searchOption' is just 'Search options', which is vague. The tool description adds no additional meaning about the parameter's fields or structure, so it fails to compensate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Google search API' and 'Returns normalized Google web search results', specifying the verb and resource. It distinguishes from siblings like google_news and other search engines.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives like bing_search or google_news. It implies general web search but lacks direct comparison or when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It transparently specifies the tool returns only the interest-by-region widget, supports multiple comparison terms, and returns an empty array when no rows exist. This covers key behavioral traits effectively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at three sentences, front-loaded with the core purpose, and each sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so description should compensate. It specifies the return is an 'interest_by_region array' and handles the empty case, but does not describe the structure of array items (e.g., region names, values). This leaves some ambiguity for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% but the sole parameter 'request' is described only as 'Explore request,' adding no meaning beyond the property name. The description mentions 'multiple comparison terms' but does not explain how to structure the request object, leaving the agent with inadequate guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns the interest-by-region widget from Google Trends Explore, distinguishing it from siblings like google_trends_explore_interest_over_time. It specifies the tool's scope and behavior with multiple comparison terms and empty array handling.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when only regional interest is needed by saying 'only the interest-by-region widget,' but it does not explicitly list alternative tools or conditions for when not to use this tool. Sibling list provides context but description lacks direct guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must cover behavior. It states the function but lacks details on output format, rate limits, or constraints. Adequate for a simple lookup.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with purpose. Slightly redundant with tool name but no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema; description only says 'location codes' without examples or structure. Sufficient for simple tool but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist; description correctly notes no input is needed. Baseline 4 for zero parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it 'Returns supported Google Trends location codes' and mentions relation to Explore endpoints, distinguishing it from sibling tools like google_trends_explore or google_trends_categories.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining location codes used in Explore endpoints but does not explicitly state when to use vs alternatives or provide exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so description carries full burden. It discloses the 503 error for challenge pages and mentions parsing from a public page. However, it lacks details on rate limits, empty results, or other edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise with three sentences. Each sentence adds value: purpose, output details, and error condition. No unnecessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description lists returned fields adequately. However, it omits pagination behavior (e.g., how 'page' and 'count' affect results). Otherwise complete for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds no additional parameter meaning beyond what is already in the schema (e.g., default values are already documented).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches Google video results and specifies the returned fields (title, platform, link, duration, age). This distinguishes it from sibling tools like google_search, bing_videos, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for Google video searches but does not explicitly state when to use this vs alternatives or when not to use it. No exclusions or comparative guidance are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds 'Public data sourced from Instacart's own storefront pages,' which informs the agent about the data source and public nature. It also enumerates the returned attributes. However, with no annotations and no output schema, it does not disclose limitations or behaviors like geolocation dependence beyond what the schema describes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with the main purpose, and the second sentence efficiently lists the return fields and data source. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the return fields and data source, which is adequate for a detail-lookup tool. The schema descriptions handle the provenance of identifier parameters. It doesn't explicitly tie into a workflow with sibling tools, but that is not necessary given the schema covers it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and each parameter already includes a description (e.g., shop_id from GET /instacart/stores). The tool description adds little beyond the schema, only emphasizing 'at a specific store.' This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get Instacart product detail at a store' with a specific verb and resource. It lists the returned fields (name, size, brand, image, pricing, availability, etc.), distinguishing it from sibling tools like instacart_search or instacart_stores.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool is used for looking up a single product's detail at a specific store, and mentions it's public data. However, it does not explicitly state when to use it versus alternatives (e.g., instacart_search for finding products) or provide exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full transparency burden. It discloses that the tool is 'credential-free' and returns 'full HTML/text description, department, and benefits'. However, it omits error behavior, rate limits, or response validation details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three short, focused sentences with no redundancy or fluff. Every sentence adds value: purpose, return types, parameter hints, and access method.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately explains what is returned (description, department, benefits) and notes credential-free access. It covers the main use cases for a simple single-job retrieval, but could mention response format details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds minor context (e.g., 'id is the req_id/slug from a board listing' and 'lang defaults to en-us') but largely repeats what the schema already describes, providing no substantial new meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Get a single iCIMS job' and lists returned fields (description, department, benefits), plus notes it's credential-free and public ATS JSON. This differentiates from sibling tools like jobs_icims_board (which likely lists jobs) and other ATS-specific tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description advises that 'id is the req_id/slug from a board listing' and mentions language default, giving implicit usage context. However, it does not explicitly state when not to use this tool or provide alternatives among the many job siblings, leaving the agent to infer from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility. It explicitly states that the tool returns genre short names and translations, which is sufficient. However, it does not mention any side effects, auth requirements, or rate limits, but for a read-only list tool this is acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that immediately convey purpose and output. No wasted words; information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one optional parameter and no output schema, the description adequately covers the basics. It could be enhanced by clarifying the effect of the language parameter, but it remains clear enough for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers the only parameter 'language' with a description. The tool description adds no additional meaning beyond what the schema provides, so it meets the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool retrieves JustWatch genres and specifies the return type (short names and localized translations). It distinguishes itself from siblings like 'justwatch_genre_titles' which likely list titles per genre.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'justwatch_genre_titles' or 'justwatch_age_certifications'. The description does not mention any prerequisites or contextual cues.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description discloses it fetches a title page and returns metadata/offers, implying read-only. Lacks details on error handling, rate limits, or authentication needs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no filler. First sentence defines purpose and output, second clarifies parameter usage. Appropriate length for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 100% schema coverage, no output schema, and low complexity, the description is adequate. Could mention it is a read operation, but the tool name implies that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers both parameters with descriptions; description adds mutual exclusivity guidance ('exactly one'), which is not in the schema structure. Addresses 100% coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the verb (Get, Fetches) and resource (JustWatch title details, title page), and specifies outputs (normalized metadata, current offers). Distinct from sibling tools like justwatch_search or justwatch_title_by_id due to using path or URL.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Only provides parameter usage guidance ('Pass exactly one of path or url') but does not explain when to use this tool over alternatives like justwatch_title_by_id, justwatch_title_offers, etc.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It implies a read operation by saying 'Get' and mentions the returned data (credits, clips, backdrops), but does not clarify auth requirements, rate limits, or any side effects. It adds moderate transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence followed by an example. It is front-loaded with the core purpose. Slightly lacking structure, but no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, so the description should describe the return format more thoroughly. It only says 'returns normalized credits, clips, and backdrops', which is vague. The role of 'country' and 'language' parameters in filtering media is not explained. For a media retrieval tool with 3 parameters, more detail is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% coverage for parameters. The description adds value by providing an example ID format ('tm92641') and clarifying that the ID is a 'raw JustWatch movie/show id'. However, it does not explain the effect of 'country' and 'language' parameters on the returned media.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves 'JustWatch title media' and specifies it returns 'normalized credits, clips, and backdrops' for a given movie/show ID, with an example ID 'tm92641'. This distinguishes it from sibling tools like 'justwatch_title' or 'justwatch_title_offers'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context by mentioning the input ID format and example, but does not explicitly state when to use this tool versus alternatives like 'justwatch_title' or 'justwatch_title_by_id'. No guidance on when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full burden. It mentions the tool returns 'normalized offers' and accepts country codes, but does not disclose rate limits, authentication, or further behavioral traits like pagination or error handling. It is adequate for a straightforward read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is efficient and front-loaded with the main action. However, it could be slightly more concise by reducing redundancy (e.g., 'across one to five comma-separated country codes' could be shortened).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description should clarify what constitutes 'normalized offers' and possibly list response fields. It also omits any mention of error cases or limitations. Overall, it is adequate but not exhaustive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description reinforces the ID format and country count limit, but adds minimal new meaning beyond the schema descriptions. It does not elaborate on the language parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves offers for a JustWatch title by its raw ID, with country filtering. It includes the key verb 'Get' and specifies the resource 'title offers'. It effectively distinguishes from siblings like justwatch_search and justwatch_title by focusing on offers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly guides usage: use when you have a raw JustWatch ID and need offers across specific countries. It does not explicitly exclude other scenarios or name alternatives, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden. It states the tool is 'credential-free' and uses 'public market-data JSON', indicating read-only access and no authentication needed. However, it does not detail other behavioral traits like pagination behavior, rate limits, or whether results are real-time or cached.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, directly stating the tool's purpose and a key parameter. It is front-loaded with 'Kalshi markets' and contains no superfluous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, no output schema, numerous siblings), the description provides concise yet sufficient context for a listing tool. It could benefit from clarifying what 'normalized' means or detailing output fields, but overall it is complete enough for an agent to use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage, so baseline is 3. The description adds value by explicitly listing accepted values for the 'status' parameter ('unopened', 'open', 'closed', 'settled'), which is not fully conveyed by the schema's enum description alone. Other parameters are not elaborated.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool returns 'normalized Kalshi market rows from credential-free public market-data JSON', which is a specific and distinctive purpose. It differentiates from sibling tools like 'kalshi_market' (singular) and 'kalshi_markets_history' by emphasizing public data and normalization.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide explicit guidance on when to use this tool versus alternatives like 'kalshi_market' or 'kalshi_markets_history'. It mentions the status enum values, which implies filtering capability, but lacks direct comparison or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries full burden. It adds useful context about data source (AniList) and public access, but lacks details on rate limits, response behavior, or handling of invalid filters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-load the purpose and key features. No wasted words; each sentence adds value (purpose, data source, filtering).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a ranking tool with 6 optional params and no output schema, description covers data source, public access, and filtering. Slightly lacking in describing what the returned ranking contains (e.g., scores, popularity), but sufficient for basic use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% so baseline is 3. Description mentions 'Filter by format, genre, and status' which matches schema but adds no new meaning beyond what the parameter descriptions already provide.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs 'Rank' and 'Returns' with clear resource 'manga ranking'. It mentions filtering capabilities and data source, distinguishing it from search tools like manga_search and anime_rankings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description implies usage for public ranking data but does not explicitly state when to use this tool over siblings like manga_search or manga_title. No alternatives or exclusions mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description adds that data is 'Credential-free public Metacritic data', implying read-only and no auth needed, but does not disclose other behavioral traits like rate limits or response size.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with front-loaded purpose, no redundant information, and minimal word count.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple lookup tool with one param and no output schema, the description adequately specifies inputs, outputs, and access requirements. Lacks details on return structure but remains sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with description 'Metacritic movie slug'. Description adds no extra meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Get a Metacritic movie' and lists specific return fields (Metascore, user score, genres, etc.), distinguishing it from sibling tools like metacritic_game.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or alternatives guidance. The name and description imply usage for movie lookup by slug, but could mention when to use metacritic_movie_critic_reviews or metacritic_movie_user_reviews instead.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description mentions 'Credential-free public Metacritic data' implying no auth required, but does not disclose rate limits, pagination behavior beyond 'paginated', or any potential side effects. As a read-only operation, it's acceptable but could be more specific.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. Covers purpose, output fields, and data type. Front-loaded with verb and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description details the fields returned. Mentions pagination. Could be more complete by describing default sort order, or error handling for invalid slugs, but sufficient for a simple list tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All 4 parameters (page, slug, sort, per_page) have schema descriptions, so baseline is 3. The tool description does not add additional context beyond the schema, e.g., acceptable sort values or slug format. No extra value provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it lists critic reviews for a Metacritic TV show. Specifies the returned fields: publication, score, quote, author, source URL. Distinguishes from sibling tools like metacritic_game_critic_reviews and metacritic_tv_user_reviews by explicitly mentioning 'TV show' and 'critic reviews'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states when to use (for TV show critic reviews) but lacks explicit exclusions or alternative tool mentions. It does not discuss prerequisites like needing a valid slug or handling of missing data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It discloses that only public projects are returned and that an invalid slug yields a 404. However, it does not explain the response format, pagination, or other behavioral details, leaving some gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, all meaningful: the first frames the tool, the second states its primary function, and the third notes the 404 error. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter read tool, the description covers purpose, scoping, and an error case. It lacks explicit mention of the return shape beyond 'normalized rows,' but given the simplicity and schema coverage, it is mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes both parameters (slug and limit) with 100% coverage. The description reinforces 'slug' but adds no new semantic detail about either parameter, so it meets the baseline but does not elevate it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly names the resource ('Metaculus question rows') and the action ('Returns') with a specific filter ('for one public project, filtered by its slug'), distinguishing it from other Metaculus tools like metaculus_questions or metaculus_tournament_questions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It implies usage when you have a project slug, but does not explicitly contrast with sibling tools or state when not to use it. The phrase 'filtered by its slug' gives context, but there is no explicit mention of alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the full burden of disclosing behavior. It does state that the tool returns a comprehensive set of 'at-bat and pitch/event records', which is useful, but it lacks detail on response format, data availability limits, or potential error conditions. The added behavioral insight beyond the tool's name is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exceptionally concise, with two sentences that front-load the core purpose and then elaborate with a clear statement of included data. Every word contributes to understanding, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a straightforward tool with one parameter, and the description effectively communicates its purpose and the scope of returned data. However, given the absence of annotations and an output schema, a brief pointer to related tools or data granularity nuances would enhance completeness. Still, it is adequate for the simple nature of the operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides a full description of the single 'id' parameter as a 'Numeric MLB game id', achieving 100% coverage. The tool description adds no additional parameter context, but with such complete schema coverage, this meets the baseline expectation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb ('Get') and resource ('MLB game play-by-play'). It further defines the return content as 'every at-bat and pitch/event record', which distinguishes it from sibling tools like mlb_game_boxscore or mlb_game that serve different data needs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used when play-by-play data is needed, but it offers no explicit guidance on when to choose this over alternatives (e.g., mlb_game_boxscore for a box score) or any exclusion criteria. The usage context is only implicit and not fully fleshed out.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the fixed result size (30 clubs) and the metadata fields included, which is useful. However, it does not mention error handling, whether historical seasons are supported, or explicitly confirm read-only behavior, leaving some uncertainty.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence: 'List MLB teams' immediately conveys the action, followed by concise details on return content. Every word earns its place, with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with one optional parameter and no output schema, the description covers the essentials: what it returns and the season context. Minor gaps like exact output structure or historical data availability are not critical given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% coverage for the only parameter, 'season', including its format and default. The description's phrase 'for a season' aligns with the schema but adds no additional semantic detail. Baseline 3 is appropriate given the schema already defines the parameter well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List') and resource ('MLB teams'), and clearly states the output: the 30 MLB clubs with league, division, venue, and abbreviation metadata. This distinguishes it from sibling tools like mlb_team_roster or mlb_standings, which serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the use case: when you need a catalog of MLB teams for a season. However, it does not explicitly state when to use this over related sibling tools (e.g., mlb_team_roster) or provide exclusions. The season context is clear, but alternatives are not discussed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It notes 'Credential-free public Numbeo data' but lacks details on data freshness, rate limits, or the format of the slug. Minimal behavioral context beyond obvious read-only nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with action. Every sentence is essential and concise. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description provides a good overview of return content (itemized prices grouped by category). It lists example categories. Almost complete for a simple tool, though exact structure is not detailed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with 'slug' described. The description adds no extra meaning about slug format or how to construct it (e.g., city name conventions). Baseline 3 is appropriate as schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get a Numbeo city's cost-of-living prices' with a specific verb and resource. It distinguishes from siblings like numbeo_cost_of_living_country by explicitly focusing on a single city and mentioning itemized categories.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for a single city's detailed prices but does not explicitly state when to use versus siblings (e.g., country-level or rankings). No 'when-not' or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses that data is public and sourced from profile pages, and mentions pagination ('a page'), but lacks details on page size, cursors, error cases, or rate limits. It adds useful context but remains incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the key action, and each clause adds value without redundancy. It is appropriately sized for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The return values are enumerated and the data source is noted, which is helpful given no output schema. However, 'a page' leaves pagination semantics unclear (e.g., how to get next pages, default size), and there is no mention of sorting or limits. For a one-parameter tool, it is mostly complete but has a notable gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents 'username' with 100% coverage. The description adds minimal semantic value for the parameter, only contextualizing it as belonging to a Pinterest user. No format, uniqueness, or case-sensitivity guidance is given, so the schema baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Get a Pinterest user's boards') and resource, and details the returned fields (name, description, cover image, pin/follower counts). It distinguishes itself from sibling Pinterest tools by scoping to a user's own boards.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the clear purpose, but there is no explicit statement of when to choose this tool over siblings like pinterest_board or pinterest_user_pins. No exclusions or alternative tool mentions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description covers key behavior: credential-free access (public data) and output structure. Lacks details on rate limits, safety (though read-only implied), or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: first defines purpose and output, second explains parameters and credential-free nature. Front-loaded with key information, no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Description adequately explains output for a simple, single-page tool with optional parameters. No mention of pagination or max results, but given likely all-at-once response, this is acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters. Description adds minor clarification (cc selects region and currency, l selects language) but does not substantially exceed schema info.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'Get', resource 'PlayStation Store latest-release shelves', and describes output structure (shelves with titles and prices, flattened list). Distinct from siblings like playstation_browse or playstation_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description implies usage for latest releases but does not explicitly state when to use this tool over siblings like playstation_browse or playstation_deals. No mention of alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description bears full responsibility. It states the endpoint requires no user token or auth, which is helpful, but does not disclose rate limits, error handling, or what 'normalized' means. Adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences that immediately convey the core function and key attributes. No redundant information; front-loaded with the verb and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has one parameter and no output schema, the description adequately explains the input and basic behavior. It lacks details about the return structure but is sufficient for a simple retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%—the single parameter 'slug' is described as 'Polymarket event slug' in the schema. The description adds context about the data source but does not provide additional semantics beyond the schema definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get Polymarket event detail.' It specifies the data source (public Gamma event JSON) and that it returns one normalized event, distinguishing it from list tools like polymarket_events.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description notes no authentication is required, implying public access, but fails to provide guidance on when to use this tool versus siblings like polymarket_market_detail or polymarket_events. No explicit when-to-use or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description mentions pagination and return contents (alternatives, tags, discussions) but does not disclose potential side effects or auth requirements. For a read-only retrieval tool, this is acceptable but could be more explicit about idempotency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. Front-loaded with purpose. Efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
5 parameters including filtering (tags) and pagination (first, cursor, order). Description does not explain how tags parameter affects results, nor the role of order or cursor. Missing clarification on the output structure. Incomplete for a tool with multiple optional parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema already describes all parameters (100% coverage). Description does not add any additional parameter-level information. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool retrieves alternatives for a Product Hunt product. The verb 'retrieve' and resource 'alternatives' are specific. Distinguished from siblings like producthunt_product which gets product details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implicitly clear that it's for getting alternatives given a product ID. No explicit when-not or alternatives listed, but the use case is straightforward.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It adds useful details such as 'flat public comment entries' and specific handling instructions for a 503 throttling response (Retry-After), which goes beyond the schema's parameter descriptions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: two sentences that efficiently state the purpose, return shape, and an important error-handling note. Every sentence provides value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list endpoint with schemas that fully document its parameters, the description provides sufficient context: it states what is returned, the resource being accessed, and a likely error condition. It lacks usage guidance, but this is a secondary concern given the low complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% parameter description coverage, so the description does not need to add parameter details. The description does not contribute any extra parameter semantics beyond what the schema already provides, resulting in the baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists Reddit user comments, using a specific verb ('List') and resource ('Reddit user comments'). It further distinguishes from sibling tools by specifying 'from a public Reddit user's comments feed', making its scope clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like reddit_subreddit_comments or reddit_comments. It only describes the tool's functionality without contextual placement or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description should disclose behavioral traits. It only mentions it is a 'faithful pass-through', but lacks details on rate limits, data freshness, permissions, or idempotency. This is insufficient for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff. First sentence states purpose, second lists data points and notes pass-through nature. Efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with 2 parameters and no output schema, the description covers functionality and return data. It lacks details on time range or historical scope, but the listed metrics sufficiently inform the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds operational context: both parameters come from 'autocomplete', and region_type defaults to 6 (city). This helps the agent understand how to obtain valid parameter values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('Redfin region market trends'). It lists the returned data points, distinguishing it from property-level sibling tools like redfin_property or redfin_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage ('aggregate market trends for a region') but does not explicitly advise when to use this tool over siblings or provide exclusion criteria. No guidance on prerequisites like needing a region_id from autocomplete.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that results are normalized and come from credential-free server-rendered HTML, which provides insight into data source and auth requirements. However, no mention of rate limits, pagination behavior, or potential performance implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, directly addresses purpose and key characteristics. No extraneous information. Front-loaded with primary function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple search tool with no output schema. Describes return type (normalized rows) and key aspect (credential-free). Could optionally mention the return format or fields, but not essential given low complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema already provides descriptions for both parameters (query and limit) with 100% coverage. The description adds no additional semantics beyond what the schema offers.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it is a Rotten Tomatoes movie search tool, specifying it returns normalized search rows from credential-free server-rendered search HTML. Distinguishes from sibling tools like rottentomatoes_browse_movies and rottentomatoes_movie.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage for searching movies on Rotten Tomatoes, but no explicit guidance on when to use this over other search tools or alternatives. No exclusions or conditions mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It mentions normalization and credential-free access but does not disclose limitations, output format, or data freshness beyond the schema parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences that front-load the purpose and add value about normalization, XBRL resolution, and credential-free access. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description lacks details on return format, structure of normalized statements, or behavior for multiple periods. Missing information that would help an agent understand the output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with good parameter descriptions. The description adds minor emphasis on cik/ticker requirement but no significant new meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized financial statements (income, balance sheet, cash flow) and resolves XBRL tags to a stable schema, distinguishing it from siblings like yahoo_finance_ticker_financials and other SEC tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description specifies providing cik or ticker and notes credential-free access, but lacks explicit guidance on when to use this tool over alternatives like yahoo_finance_financials or other SEC tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It indicates a read operation ('resolves the public merchant profile') but does not disclose potential issues like missing product-shop association, rate limits, or id format requirements. Behavior is minimally inferred.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two short sentences, no unnecessary words. Every sentence adds value, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter retrieval tool with no output schema, the description is largely complete. It could mention expected return format or error cases, but given no output schema, the basic operation is clear enough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a simple 'Product id' description. The tool description clarifies the parameter's role (resolving the shop), but adds no further detail on id format, validity, or behavior. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get', the resource 'Shop.app shop for a product', and specifies that it resolves the public merchant profile for a product id. This effectively distinguishes it from sibling tools like shop_app_product (product details) and shop_app_shop (shop by ID).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage via product id but does not explicitly state when to use this tool versus alternatives (e.g., shop_app_shop). No when-not or exclusions are provided, leaving the agent to infer context from the name and sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It mentions 'public' variant, hinting at access level, but does not disclose idempotency, rate limits, auth needs, or side effects. The description is minimal for a tool with no annotations, lacking key transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (3 sentences), front-loaded with the main purpose, and every sentence adds unique information. No filler or redundancy. It efficiently communicates key details about the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (2 params, no output schema), the description covers the essential usage of selected_options with multiple formats. However, it could mention what the response contains or error behavior, but it is mostly complete for a simple variant retrieval tool. The absence of output schema is compensated by the concise parameter guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds value by explaining that 'selected_options' must be a JSON object and offering alternative syntax (option.Name=value, option[Name]=value), which is not present in the schema. This aids correct usage beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and the resource ('a Shop.app product variant'), and distinguishes from siblings like 'shop_app_product' (gets a product) and 'shop_app_product_variants' (lists all variants). It specifies that it returns the exact public variant matching selected options, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you need a specific variant based on options, but it does not explicitly state when to use this tool vs alternatives like 'shop_app_product_variants' for listing all variants. No when-not-to-use or exclusion criteria are provided, so guidance is implicit but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses limit behavior (default 20, max 50) and credential-free nature, but omits details on rate limits, pagination, result format, or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the purpose. Every word earns its place; no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and 5 parameters, the description covers the search scope and limit behavior. Parameter details are handled by the schema. Slightly lacking in explaining result structure or advanced features like deep_search, but adequate overall.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents all 5 parameters. The description adds no extra meaning beyond repeating the limit behavior, which is also in the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches Shop.app products using a credential-free public web search flow, distinguishing it from other search tools that may require authentication or target different domains.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context via 'credential-free public web search flow,' but does not explicitly specify when to use this tool versus sibling search tools like shop_app_suggestions or amazon_search. No exclusion criteria are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It adds context about 'child sitemaps' and 'capped entries', but this is largely redundant with the schema (limit parameter). It does not disclose other behavioral traits such as authentication needs, rate limits, or output format, which would be useful.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two sentences with no wasted words. The first sentence states the core purpose, and the second adds relevant detail about the nature of the results. It is appropriately sized and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with three parameters and no output schema. The description covers the key aspects: listing URLs, from child sitemaps, by type, with a cap. However, it does not describe the output format (e.g., array of strings), which would be helpful given the absence of an output schema. Still, it is mostly complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no new information beyond what the schema already provides for each parameter (url, type, limit). It does not enhance understanding of parameter values or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists Shopify sitemap URLs and explains it fetches capped URL entries from child sitemaps by type. The verb 'list' and resource 'Shopify sitemap URLs' are specific, and it distinguishes from the sibling tool 'shopify_sitemaps' which likely lists available sitemaps rather than their URLs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining URLs from specific Shopify child sitemaps, but it does not provide explicit guidance on when to use this tool versus alternatives like 'shopify_sitemaps' or 'shopify_products'. No exclusions or when-not-to-use scenarios are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions that a 404 is returned when odds are not available, which is a useful behavioral note. However, with no annotations provided, the description should also disclose rate limits, data freshness, or whether the response format is documented. The 'credential-free' mention helps but is limited.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise: three sentences with no waste. It front-loads the purpose and includes key details (data source, error behavior) efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one parameter and no output schema, the description covers the main aspects: what it returns (markets and choices), the source, and a common error. It lacks detail on the structure of the returned data, but given the simplicity, it is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of the single parameter id, and the description adds no extra meaning beyond 'Numeric SofaScore event (match) id'. The schema already describes it adequately, so the description does not add value here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'one match's betting markets and choices' from SofaScore. It specifies the data source ('credential-free public JSON') and an important behavior (404 when no odds). This distinguishes it from siblings like sofascore_event, which likely returns general match info.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving odds for a specific match, but does not explicitly state when to use this tool versus other SofaScore tools (e.g., sofascore_event, sofascore_event_h2h). No guidance on prerequisites or scenarios where alternatives are better.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description provides useful behavioral details: it returns statistics from credential-free public JSON, indicates grouping/splitting by period, and mentions a 404 for matches without tracked statistics. This is good disclosure for a simple read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two efficient sentences with no wasted words. The first sentence states the core functionality, the second adds a key error case. Front-loaded and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description covers the purpose, parameter usage, and error condition. It gives a good overview of the returned data structure without being overly verbose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter 'id' described as 'Numeric SofaScore event (match) id'. The description reinforces this without adding new meaning beyond what the schema already provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns one match's statistics including specific categories like possession, shots, passes, and more, grouped by period. This is specific and distinguishes it from other sofascore event tools like sofascore_event (basic info) or sofascore_event_lineups.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is given on when to use this tool versus alternatives among the many sofascore siblings. The description lacks when-to-use or when-not-to-use context, leaving the agent to infer based solely on the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'credential-free public JSON', indicating no authentication needed. However, it does not disclose rate limits, data freshness, or how the tool handles missing fields.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence. It front-loads the tool's purpose ('SofaScore player detail') and specifies the return data concisely. No extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter tool with no output schema or annotations, the description adequately covers purpose, source, and key output fields. It could mention that the output includes additional fields not listed, but overall it is complete enough for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes the 'id' parameter as 'Numeric SofaScore player id' with 100% coverage. The description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns a player's bio with specific fields (position, height, market value, current team) from SofaScore's credential-free public JSON. The verb 'Returns' is explicit, and the resource is distinct from sibling tools like sofascore_team or sofascore_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives (e.g., sofascore_search to find a player ID first). It implies usage when a player ID is available, but no guidance on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries the burden. It mentions 'credential-free public JSON' and that an empty events list is valid, but does not disclose rate limits, pagination behavior beyond zero-based page, error handling, or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each essential. No redundancy, no fluff. Front-loaded with purpose, then constraints.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so description should elaborate on return structure. It mentions 'page of fixtures' and empty events, but does not describe fixture fields, error cases, or how page size is determined. Incomplete for a tool with 3 parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds value by clarifying direction enum values ('next' and 'last') and stating page is zero-based, which enhances schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a page of a team's upcoming or recent fixtures, identifying the specific verb ('Returns') and resource ('team fixtures'). It distinguishes from sibling tools like sofascore_team and sofascore_team_players by focusing on fixtures.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for upcoming or recent fixtures via direction enum, but does not explicitly guide when to use this over alternatives like sofascore_event, sofascore_live_events, or sofascore_round_events. No 'when not to use' guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes the return as normalized metadata but does not disclose potential authentication needs, rate limits, or behavior when both parameters are provided. With no annotations, more detail would be beneficial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise: two sentences that front-load the purpose and essential usage. No unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with high schema coverage, the description covers purpose, input options, and default behavior. Missing output details but acceptable given no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions. The description adds value by explaining optionality and fallback, but the schema already conveys most information, so baseline score is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Retrieve Spotify track details' with a specific verb and resource. It distinguishes from sibling tools like spotify_album or spotify_search by focusing on retrieving track metadata from Spotify Web Player.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides guidance on providing either uri or id, and mentions default behavior when omitted. However, it lacks explicit when-to-use or when-not-to-use guidance compared to alternative Spotify tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist. The description adds the behavioral trait 'credential-free public Steam storefront JSON', informing the agent it requires no authentication. However, it does not disclose rate limits, data freshness, or other side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise sentences, front-loading the purpose, enumerating the categories, and noting the credential-free nature. No extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description adequately explains the return structure (merchandising buckets with item lists). It could mention pagination or item count limits, but it is largely complete for a simple list tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (both parameters have descriptions). The description adds no additional meaning beyond the schema; it mentions 'region' but does not elaborate on the parameters. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Steam storefront merchandising buckets (specials, top_sellers, new_releases, coming_soon), distinguishing it from siblings like steam_top_sellers or steam_featured by specifying the exact categories and their lists.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly guide when to use this tool versus alternatives. It implicitly implies usage for fetching curated Steam categories, but no when-not-to-use or alternative references are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the disclosure that the tool is 'credential-free', uses Steam's keyless API, and resolves up to 100 app IDs provides useful behavioral context. However, it omits potential rate limits, error handling, or return structure details, which would enhance transparency for a batch tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (3 sentences) and front-loaded with the core action and key outputs. Every sentence adds value, and the technical terms are explained clearly. There is no verbosity or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description compensates by listing returned fields (weighted tags, review score, credits, release date, platforms, price) and noting the API source and batch limit. It lacks only explicit output format details but is otherwise complete for the tool's purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description reinforces the max 100 app IDs and mentions 'normalized store items' but does not add significant meaning beyond the schema parameter descriptions. No new constraints or formatting details are introduced.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool resolves a batch of app IDs to store items with weighted tags, listing specific returned fields and emphasizing its role as a 'batch enrichment primitive for the community-tag taxonomy'. This effectively communicates the tool's unique value and distinguishes it from sibling Steam tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for batch enrichment with community tags but does not explicitly state when to use this tool versus alternatives (e.g., steam_app for single app details). No exclusion criteria or alternative recommendations are provided, leaving some ambiguity for the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries the burden. Mentions it is 'credential-free public Steam WebAPI JSON', which adds useful context about authentication and data format, but does not disclose rate limits, error handling, or response structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences that front-load the purpose and include essential context (credential-free, public). No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description provides sufficient context (current count, official source) but could mention the expected response format (e.g., JSON object with count).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter 'appid', which is described as 'Numeric Steam app id'. The description adds no additional meaning beyond 'for a Steam app', so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it gets the current concurrent-player count for a Steam app. The verb 'Get' and specific resource 'current concurrent-player count' differentiate it from sibling tools like steam_charts_concurrent that focus on overall charts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage for fetching concurrent players of a single app, but does not explicitly state when to use this tool versus alternatives like steam_charts_concurrent or datasets_steam_playercounts_search.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that only public posts are returned and that an opaque continuation cursor is used for pagination, which is useful. However, it omits details like pagination behavior (e.g., page size, ordering), whether reposts are included, or any access limitations beyond 'public'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no redundant words. It efficiently conveys the core action and the key pagination detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter retrieval tool with no output schema, the description adequately explains the purpose and the cursor mechanism. It does not describe the shape of returned posts, but given the simplicity and the presence of sibling tools like threads_post that may cover post structure, this is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with both parameters documented. The description adds no extra meaning beyond the schema: it does not elaborate on the username format or cursor usage beyond what the schema already states. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Retrieve') and resource ('public posts from a Threads profile'), clearly distinguishing it from siblings like threads_post (single post) or threads_search (search). It states exactly what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving public posts from a profile, but does not explicitly state when to use this vs alternatives such as threads_profile, threads_post_replies, or x_profile_posts. No exclusion or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the behavioral burden. It states it 'Returns normalized details,' which implies a read operation and hints at output structure, but it does not disclose failure conditions, permissions, rate limits, or what 'normalized' entails. 'Get' is a weak but acceptable signal for a read-only operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences and front-loaded with the core action. Every phrase adds value, including the explicit types of attractions and the 'normalized details' outcome, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter lookup, the description is nearly complete: it identifies the resource, action, and high-level return type. The absence of annotations and output schema would benefit from slightly more detail about output contents or error handling, but the tool is simple enough that the description adequately covers it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% coverage with 'id' described as 'Numeric Ticketmaster attraction id.' The description adds no new parameter semantics beyond clarifying that an attraction can be an artist, team, or other entity, which is already implicit in the resource name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action ('Get') on a specific resource ('Ticketmaster attraction') and defines attraction as an artist, team, or other attraction. This distinguishes it from sibling tools like ticketmaster_event and ticketmaster_venue, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when the agent needs details for a single attraction by ID, but it does not explicitly state when to use this tool versus alternatives. It offers no contrast with sibling tools such as ticketmaster_attraction_events or ticketmaster_search_events, and no exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses default values for four parameters (period, page, limit, order_by) indicating read behavior, but lacks details on side effects or rate limits given no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two focused sentences with no superfluous content, efficiently conveying the tool's purpose and key additions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a list retrieval tool with 13 parameters and no output schema, the description adequately covers defaults and filter sourcing, though it omits output structure details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All parameters have schema descriptions (100% coverage), and the description adds default values for four parameters and references an external filters endpoint, offering some extra guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves top ads from TikTok Creative Center, distinguishing it from sibling tools like detail or analysis tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides guidance on using the /tiktok/top-ads/filters endpoint for dynamic values, but does not explicitly state when to use this tool versus alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden. It states it is a retrieval operation returning 'public Creative Center safety configuration flags related to search surfaces,' implying a safe, read-only action. However, it does not discuss rate limits, side effects, or authorization needs beyond the implicit read-only nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, no repetition, no unnecessary words. The description is front-loaded with the primary action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters, no output schema, and simple functionality, the description adequately explains what the tool does and what type of data it returns. It provides enough context for an AI agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so the baseline is 4. The description adds meaning by explaining the output context ('safety configuration flags related to search surfaces'), which compensates for the lack of parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Retrieve') and the resource ('TikTok Top Ads safety configuration'), and further specifies 'Returns public Creative Center safety configuration flags related to search surfaces.' This distinguishes it from sibling tools like 'tiktok_top_ads_analysis' or 'tiktok_top_ads_detail'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as 'tiktok_top_ads_filters' or 'tiktok_top_ads_suggestions'. It does not mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly indicates a read operation via 'Returns' and adds valuable context about data normalization, sourcing from Upwork's server-rendered pages, and the use of a real browser-rendering backend. However, it does not mention potential failure modes, latency, or what happens for invalid IDs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two focused sentences: the first states the action and resource, the second enumerates return fields and data source. Every sentence earns its place, with no filler or redundancy, and the key information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter read-only tool with no output schema and no annotations, the description is quite complete. It explains the return content in detail and the data provenance. The only notable gap is usage guidance, but it still provides sufficient context for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides a description for the single 'id' parameter ('Upwork freelancer id, the value after...'), achieving 100% schema coverage. The tool description does not add further detail about the parameter, but with only one parameter and high schema coverage, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb+resource ('Get Upwork freelancer profile') and enumerates the exact fields returned (name, title, rating, Job Success Score, etc.). This clearly distinguishes it from sibling tools like upwork_job and upwork_search, which focus on jobs and search respectively.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool versus alternatives like upwork_search. The description does not state prerequisites, when not to use it, or how it relates to other Upwork tools, leaving the AI to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It states the tool is read-only (get) and returns ordered results. However, it lacks details on pagination, authentication requirements, or potential side effects. Adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that front-load the main purpose and key details (output fields, ordering, time range). No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of sibling tools, the description sufficiently covers what the tool returns and its time-based filtering. However, it could explicitly mention parameter dependencies (e.g., from/to only with range=custom) to improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with clear parameter descriptions for from, limit, range, and to. The description adds minimal new meaning beyond summarizing the time range selection. Baseline 3 is appropriate as schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool retrieves the current user's endpoint usage breakdown with per-endpoint request and credit totals, ordered by request volume. This differentiates it from siblings like usage_overview (likely aggregate) and usage_timeseries (time-based).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for endpoint-level breakdowns but does not explicitly mention when to use this tool versus alternatives like usage_overview or usage_timeseries. No exclusions or 'when not to use' guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the full behavioral disclosure burden. It only states 'public data' and the source, but does not describe authentication expectations, failure modes, rate limits, or what the actual output structure looks like beyond enumerating content types.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is reasonably compact, but the first and second sentences are largely redundant, both highlighting bibliographic data, abstract, description, and claims. The useful workflow note about using prior search values appears only in the second half, but overall it is still easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema and only two simple parameters with 100% schema coverage, the description provides enough context: what is fetched, how to obtain the parameters, and the public nature of the data. It lacks info on errors or authentication, but these are less critical for a straightforward read-only detail lookup.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents both parameters, including allowed source values. The description adds value by explaining that guid and source are intended to be passed through from a usptoppubs_search result, which is important workflow context not fully captured in the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb and resource: 'Fetch a single USPTO Patent Public Search record's full text...' and enumerates exact content: bibliographic data, abstract, description, and claims. It also distinguishes itself from the search sibling by emphasizing a single record and GUID-based lookup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says guid and source 'normally come straight from a prior /usptoppubs/search result's guid and database fields,' giving concrete workflow guidance. It does not explicitly state when not to use it or name alternatives, but the context is clear enough for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses the use of proxied browser renderers and credential-free access, which is useful. However, it does not mention rate limits, error handling, or potential issues like CAPTCHA blocking.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no filler. First sentence states purpose and output, second gives behavioral context. Efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so description compensates by listing returned fields. Could mention pagination behavior or error scenarios, but adequate for a simple search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% so baseline is 3. The description adds value by listing returned fields but does not elaborate on parameter behavior beyond schema descriptions (e.g., sort values, page range).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches Walmart products and returns specific fields (item id, title, brand, etc.). It distinguishes itself from sibling search tools by specifying the source (Walmart) and noting it uses credential-free public data from proxied browser renderers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance is provided. The description implies it's for public Walmart searches without credentials, but doesn't compare to alternatives like amazon_search or ebay_search among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden. It discloses the offset-based pagination, the normalized product fields, and the empty-result behavior for no match. It does not cover rate limits or state, but for a search tool this is a strong behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only about 70 words, but the first two sentences are redundant ('Search Wish products' and 'Searches Wish's product catalog by keyword'). The informative details about features and empty results come after a slightly repetitive opener; still compact overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema and no annotations, but the description compensates by listing the returned product fields and describing the empty-result edge case. Combined with the detailed input schema, the agent has enough context to invoke the tool and interpret the result. Missing Sorting semantics is a minor omission at best.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents every parameter at 100% coverage, including nonobvious constraints like the offset multiple behavior. The description adds only 'real offset-based pagination' and does not materially enrich parameter-level semantics; baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource ('Search... Wish's product catalog by keyword') and clearly states the return shape ('normalized products with price, currency, rating, review count, and merchant id'). This distinguishes it from catalog/structure tools like wish_categories, single item lookups like wish_product, or suggestion tools like wish_suggest.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use case is inferable: use this when you need to search Wish products by keyword. However, there are no explicit alternative/non-excluded mentions such as 'use wish_suggest for typeahead' or 'use wish_categories for browsing'. The usage is implicit rather than clearly routed to the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but the description adequately conveys the behavior (listing). However, it doesn't disclose any potential limitations or side effects, which is acceptable for a simple list tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with the tool's name. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with no parameters and no output schema, the description is complete enough. It explains the single purpose adequately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Zero parameters, schema coverage 100%. Description adds no param details but it's unnecessary since there are no inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists Yahoo Finance predefined screeners, distinguishing it from siblings like yahoo_finance_screener which likely executes a screener.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus yahoo_finance_screener or yahoo_finance_screener_custom. Missing context about prerequisites or use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses it returns four holder module types, but no annotations exist to offload safety/read-only status. Does not mention data freshness, rate limits, or result structure beyond module names.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence that front-loads the main purpose. No redundant or extraneous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with one parameter and no output schema, the description covers the basics. It lacks detail on the structure of the returned modules, but that is acceptable given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage for the single symbol parameter, and the description adds that it returns holders for that symbol. Baseline of 3 is appropriate as no additional parameter nuance is provided beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns holder modules for a symbol. The verb 'returns' plus the specific data types distinguish it from sibling tools like yahoo_finance_ticker_info.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when holder information is needed, but does not explicitly say when to use vs. alternatives like yahoo_finance_ticker_analysts or yahoo_finance_ticker_earnings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool returns calls and puts and requires a Unix expiration timestamp, but does not mention error handling, data freshness, or required permissions. This is adequate for a simple read-only tool but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded and contains no unnecessary words. It efficiently conveys the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two parameters and no output schema, the description adequately explains what it does and what it returns. It could mention that it returns a list of option contracts, but the phrase 'options chain' implies this. It is sufficiently complete for an agent to understand its purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of parameters with descriptions. The description adds that it returns calls and puts, which is contextual but does not add new parameter-specific meaning beyond what the schema already provides ('symbol' and 'Unix expiration timestamp').
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('returns'), the resource ('options chain by expiration'), and the output ('calls and puts'). It distinguishes from sibling tools like yahoo_finance_ticker_options by specifying 'by expiration' with a specific Unix timestamp.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving options for a specific expiration date but does not explicitly state when to use this tool versus alternatives like yahoo_finance_ticker_options (which may return all options). No when-not-to-use or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It adds useful context: the feed is from Yahoo Health's own server-rendered section pages, suggesting the content is as published on the site and may include pagination. However, it does not disclose failure modes (e.g., invalid category), how the page parameter behaves at bounds, or whether the feed is dynamic or cached.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, the first being immediately useful, the second defining the output fields, the third contextualizing the source. It's efficient with no major redundancy, though 'some content' could be made more specific about what the section field accepts.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is no output schema, the description compensates reasonably by naming the returned fields. However, it lacks details on how category parameters map to actual Yahoo Health section names, whether the page parameter is unlimited or capped, and how errors look (empty feed for bad category). This is enough to call the tool correctly in a normal case but not minimal for edge-case handling.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters. The description adds the concept of 'page-based pagination' but does not add syntax or valid values for the category parameter beyond what the schema provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Returns a Yahoo Health section's editorial story feed' with detailed fields (title, destination URL, category, thumbnail image) and page-based pagination. It clearly distinguishes from siblings like yahoo_health_article and yahoo_health_home by scoping to section feed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description identifies it as a section story stream and explicitly notes its data source (server-rendered section pages), which implies when to use it: when the agent needs category-specific story listings. It does not explicitly name alternatives such as yahoo_health_home or yahoo_health_article, so it is a single exclusion short of ideal.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It does disclose the source ('Yahoo Life's own server-rendered homepage') and the returned fields, suggesting a read-only, fixed feed. However, it does not mention item count, ordering, freshness, or any fetch-time considerations such as page-load/sanitization behaviors, which are useful for a no-annotation scraping-backed endpoint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short, focused sentences contain every necessary fact: scope, output fields, and data source. The description is front-loaded with the core purpose and wastes no words, making it very fast for an agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter read-only feed tool with no output schema, the description is complete: an agent knows exactly the result shape ('feed: title, destination URL, and thumbnail image') and the source. The absence of output schema is fully compensated by this explicit description of return fields.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters and schema coverage is 100%, so there are no param details to document. The description correctly adds no parameter noise and simply clarifies what the no-argument call returns, which is all that is needed here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Yahoo Life homepage story stream,' giving a specific resource scope, and then states the action ('Returns') and the exact output fields (title, destination URL, thumbnail image). This is clear enough to distinguish from other feed tools by content topic, though it does not explicitly name a sibling for contrast.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage context is implied through the name and resource description: this tool is for the Yahoo Life homepage feed. However, there is no explicit when-to-use or when-not-to-use guidance relative to the many sibling feed tools (e.g., yahoo_entertainment_home, yahoo_news_home), so an agent must infer the boundary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations available, the description carries the full behavioral disclosure burden. It clearly states that only top-level comments are returned, includes sort order and cursor-based pagination, and correctly reflects the read-only nature of the operation. It adds sourcing provenance ('Yahoo's own comment platform gateway'), which adds context, but it does not mention auth, rate limits, or error behavior, so I do not award a 5.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact — a two-sentence resource line plus a short provenance line. There is no filler, and key information about pagination, ordering, and top-level scope is front-loaded. The provenance sentence is a nice-to-have but not essential, so it's not as tight as a pure 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description gives a reasonable mental model of the return type and pagination, despite the lack of an output schema. It misses, however, a note about the companion tool yahoo_news_comment_replies and does not explain where to obtain the content_id (the schema says 'returned by home/category/article' but the description doesn't). For a complete call, an agent still has to gather its content_id source from the schema; that's an uncovered gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is already a 3. The description mentions 'sort order' and 'cursor-based pagination', which loosely echo the sort and cursor parameters, but it does not explain their values or relationships beyond what the input schema already states. Thus the description adds minimal semantic value over the structured schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb, 'Returns', and pinpoints the exact resource: a page of an article's top-level comments. It also names the returned fields (author, body, reaction counts, reply count, pin status), and the 'top-level' qualifier distinguishes it from the sibling tool yahoo_news_comment_replies without opening any schemas.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description tells the agent what the tool does but never explicitly says when to choose it over alternatives. An agent can infer from 'top-level comments' that yahoo_news_comment_replies covers the nested replies, but the routing is not made explicit as it is in a more assertive description. No exclusions or prerequisite steps are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full burden of behavioral disclosure. It usefully states that results are fetched from Yahoo's server-rendered image-search page and that dimensions are included only when available. Even so, it does not mention pagination, result-count limits, failure behavior, or how many results are returned, leaving some behavioral uncertainty.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded: it states the action in the first sentence and then provides the return-field list and source context in two efficient sentences. There is no unnecessary repetition or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter, read-only search tool, the description is nearly complete: it explains the source, the return fields, and the availability caveat for dimensions. The main omission is a statement about result count or pagination, but at this complexity level the description gives an agent enough context to call the tool and interpret its output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema fully documents the only parameter, 'q', as 'Search query', giving 100% schema coverage. The description references 'a query' but adds no new meaning or syntax requirements beyond what the input schema already provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Search') and resource ('Yahoo image results'), and details exactly what the output contains: title, direct image URL, hosting page, source domain, thumbnail, and dimensions. This clearly differentiates the tool from broad Yahoo search and alternative image-search engines like bing_images or duckduckgo_image.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description conveys the basic context: use this tool when you want Yahoo's image-search results for a query. However, it does not explicitly mention alternatives or exclusion conditions, such as 'use yahoo_search for general web results' or 'use bing_images for Bing image results.' The usage guidance is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description clarifies that this is a read-only feed operation and states what each returned story contains. With no annotations present, it does not disclose freshness, ordering, pagination, rate limits, or failure behavior, but for a zero-parameter homepage feed it adds meaningful context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded, stating the key value proposition first and then delivering the needed field details. Both sentences are informative, with no wasted wording.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no parameters and no output schema, the description gives enough to call and understand the response shape by listing the four return fields. It does not fully cover details like feed ordering, update cadence, or response container format, but those are less essential for a simple zero-input feed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters and the description does not introduce any. Since there are no parameters to disambiguate, the description adequately confirms that the tool simply returns the current homepage feed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the resource (Yahoo Tech's homepage) and the operation (returns the editorial story stream). It lists the exact fields returned (title, destination URL, category, thumbnail), and the phrase 'homepage story stream' establishes what makes it distinct from sibling article/category tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit mention of when to use this tool versus alternatives like yahoo_tech_article or yahoo_tech_category. The usage context is implied but the description provides no yes/no criteria, exclusions, or alternative tool guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It discloses that the data is 'Credential-free public data from Agoda's own hotel content source,' which is valuable context about authentication and source. It also enumerates the exact content returned, giving the agent a clear picture of the operation's behavior and scope, though it doesn't describe error cases or edge behaviors.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that lists the main return fields in a structured, parenthetical format. It is somewhat long due to the detailed field list, but every element provides useful information and the structure is clean, meriting a 4 rather than 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema, the description compensates by explicitly listing the fields to be returned, including policy statements. It also clarifies the data source and credential-free nature. It doesn't cover failure modes or when property_id might be invalid, but for a simple detail endpoint with one parameter, this is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers the single parameter fully with a description explaining property_id is a numeric ID from a prior search or URL. The tool description itself does not add further parameter semantics, so the baseline of 3 applies given 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb and resource: 'Get Agoda hotel detail.' It enumerates the exact types of data returned (identity, address, rating, photo, room count, chain, descriptions, policies), which distinguishes it from sibling tools like agoda_activity_detail or agoda_homes_search. The title matches the scope precisely.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by stating it returns hotel detail and the schema notes the property_id comes from a prior search call, but it does not explicitly mention alternatives or when to prefer this tool over agoda_hotels_search or other detail tools. There is no direct exclusion of activities or homes, leaving guidance implicit rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description notes the tool uses public AniList data and optionally scrapes MAL without credentials, but lacks details on rate limits, error handling, or data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences cover the main purpose and extra parameter behavior, though the list of fields could be more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-item retrieval, the description lists all returned fields, but could mention error scenarios or data format details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds value beyond the schema for the 'mal' parameter (adds one fetch, omitted if no MAL id).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get an anime' and lists all returned fields, distinguishing it from sibling tools like anime_title_characters or anime_title_recommendations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you have an AniList id and want detailed info, but does not explicitly mention when to use this tool vs alternatives like anime_search or anime_rankings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the output fields and pagination behavior, which is basic. It does not mention rate limits, authentication needs, or any side effects. However, for a simple read-only API, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loaded with purpose and core output. Every sentence adds value: the first specifies action and result, the second clarifies it's public and free. No redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (3 parameters, no output schema, no nested objects), the description is complete. It states the return type (cast with specific fields) and pagination. There is no missing information for an agent to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for its three parameters. The description adds no additional meaning beyond what the schema already provides (id, page, per_page defaults and limits). Baseline score of 3 applies as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists an anime's characters with specific output fields (character name, native name, billed role, image, favourites) and pagination. It distinguishes from sibling tools like anime_character (single character) or anime_character_search (search across characters) by making 'anime's characters' the focus.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly tells when to use it (when you need characters for a specific anime) but does not explicitly mention when not to use it or recommend alternatives like anime_character or anime_character_search. The 'Credential-free public AniList data' line hints that no auth is required but stops short of full guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral transparency burden. It adds that results are 'normalized' and sourced from a public API, implying read-only behavior, but it does not disclose response structure, pagination defaults, or potential errors, leaving significant ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the core action, and every word contributes (search action, scope, and data source).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and no annotations, yet the description only promises 'normalized Apple Books audiobooks' without specifying the return format, pagination behavior, or result fields. For a search tool with five parameters, this is a moderate gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% parameter description coverage, so the baseline is 3. The description adds no parameter-specific details beyond repeating the search concept, so it does not elevate beyond baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource ("Search Apple Books audiobooks") and adds context about returning normalized data from Apple's public iTunes Search API, which distinguishes it from generic apple_books_search and other apple_books tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It clearly states the tool is for searching audiobooks, which tells when to use it, but it doesn't explicitly mention alternatives or exclusions (e.g., use apple_books_search for books in general).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full transparency burden. It indicates a read-only retrieval operation via the verb 'Retrieve' and provides context about the data source ('App Store lookup API') and normalization. However, it does not explain what happens if neither identifier is provided (schema says required: []), nor does it mention any side effects, rate limits, or error behavior. The verb 'Retrieve' implies safety, but the ambiguity around required parameters is a gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short, front-loaded with the purpose, and every sentence adds value. It covers what the tool does, the source API, the identifier options, and platform coverage without any redundant or filler content. Excellent structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 6 parameters, no annotations, and no output schema. The description provides key information (identifiers, platform coverage) but leaves gaps: it does not clarify how the tool behaves when no id/app_id is provided (schema lists no required params), does not describe the return format beyond 'normalized metadata', and does not mention default behaviors for flags like ratings or platforms. For a simple retrieval tool it is adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds meaningful relational information by stating that `id` and `app_id` are alternatives ('Provide either'), which is not apparent from the schema alone. It also clarifies that both can identify any platform. This goes beyond the individual parameter descriptions, justifying a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Retrieve full App Store app details', which is a specific verb+resource combination. It clearly distinguishes this tool from siblings like appstore_reviews, appstore_ratings, and appstore_search by emphasizing 'full details' and mentioning the lookup API. The purpose is unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by instructing users to provide either `id` or `app_id` and notes that these can identify iPhone/iPad/Mac listings. However, it does not explicitly state when to use this tool versus alternatives (e.g., appstore_reviews for reviews), nor does it mention exclusions. Usage context is implied rather than spelled out.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that results are fetched from public Bing news HTML/async pages and may return 503 on challenge pages. This warns agents about reliability. No annotations provided, so description carries the burden well. Could mention rate limits or data freshness, but still strong.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no waste. First sentence states purpose immediately. Second sentence adds critical defaults and error behavior. Front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, failure mode, and locale defaults. No output schema exists, so description should hint at return structure (e.g., fields included in normalized results). Missing that context. Adequate but with gaps for a no-output-schema tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions. The description reiterates locale defaults already in schema, adding no new semantic meaning. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search Bing news results' with a specific verb and resource. It distinguishes from sibling Bing tools (images, search, videos, suggest) by focusing on news.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides context about locale defaults and potential 503 errors, but does not explicitly guide when to use this tool versus alternatives like google_news or general bing_search. No exclusions or when-not-to-use advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that data is public and credential-free, returns pages (implying pagination), orders newest first, and lists included content types. It does not cover error behavior or rate limits, but for a simple read operation it is reasonably transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the core action. However, the first sentence 'A Bluesky account's posts' is redundant with the second sentence's phrasing, creating minor repetition. Overall it is efficient and each sentence adds useful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with no output schema, the description provides enough context: what it returns, ordering, and public/credential-free API source. It could mention pagination cursor handling more explicitly, but the schema already documents the cursor parameter, so the description is fairly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema descriptions cover all three parameters (actor, limit, cursor) at 100%, so the baseline is 3. The description adds context about post content and ordering but does not add syntax or format details beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a page of a Bluesky account's posts, newest first, with specific content details (text, engagement counts, images/link cards/quoted posts). This distinguishes it from sibling Bluesky tools like profile, followers, or post thread by the resource it acts on.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for retrieving an account's post feed but does not provide explicit when-to-use guidance or mention alternatives. No exclusions or comparisons to sibling tools are given, leaving usage primarily inferred from the name and resource description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses key behavioral traits: public data, no credentials required, and paginated results ('Returns a page'). This is meaningful transparency beyond what the schema provides, though it omits details like default page size or ordering behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences and efficiently conveys the purpose and data source. However, the first sentence 'Accounts a Bluesky account follows.' is redundant with the second, which says the same thing. This slight redundancy prevents a perfect score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with fully described parameters and no output schema, the description adequately covers the resource, pagination, and the public, credential-free nature of the data. It does not explain the response shape or default behavior, but these are not critical given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers 100% of parameters with clear descriptions for actor, limit, and cursor. The description adds no additional semantics beyond what the schema provides, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a page of accounts a Bluesky account follows, with a specific verb ('Returns') and resource ('accounts a Bluesky account follows'). This uniquely distinguishes it from the sibling tool bluesky_followers, which lists the accounts that follow a given account.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides useful context by noting the data is public and credential-free, implying it can be used without authentication. However, it does not explicitly state when to use this tool versus alternatives like bluesky_followers, nor does it provide exclusions or when-not-to-use scenarios. Usage is implied by the resource description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool 'Returns' suggestions, implying a read-only, non-destructive operation. However, it does not disclose rate limits, error behavior, or any specific output structure. For a simple autocomplete tool, this is adequate but lacks richer detail such as potential limits or response format expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and effective: two short sentences. The first establishes the tool's domain ('Booking.com flight autocomplete'), and the second provides the functional purpose. No redundant or filler content exists, and the key information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has four parameters and no output schema, so the description must provide context beyond the input schema. It explains that results are airport/city suggestions for flight search, but does not describe the shape of the returned suggestions (e.g., fields like ID, name, code, type), any default limits, or error conditions. Given the absence of an output schema, this is a notable gap, but for a simple autocomplete endpoint it is not severe.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides descriptions for all four parameters (query, type, origin, origin_type), achieving 100% coverage. The description only mentions 'query string,' adding no new information beyond the schema's 'City or airport name/code to search.' The origin parameter's proximity biasing is explained in the schema, so the description adds no extra semantic value. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Booking.com flight autocomplete. Returns Booking.com flight-search location suggestions (airports/cities) for a query string.' It uses a specific verb ('Returns') and resource ('Booking.com flight-search location suggestions'), distinguishing it from sibling tools like booking_flights_search (actual flight search) and booking_attractions_search. The scope is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for use: it is for retrieving flight-search location suggestions based on a query string. This implies it should be used for autocomplete-style input. However, it does not explicitly mention alternatives (e.g., booking_flights_search for actual flight search) or exclusions, so it falls short of a perfect score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the data comes from a 'public' page, implying no authentication needed, and describes the return type as 'normalized release comparison metrics.' However, it does not disclose whether the operation is read-only, potential side effects, rate limits, or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, with three short sentences that front-load the purpose and include the key usage rule. Every sentence is necessary and no words are wasted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description adequately covers the tool's purpose and parameter selection, but with no output schema, it lacks details about the return format or structure of 'normalized release comparison metrics.' This could leave the agent underinformed about what to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with each parameter described. The description adds critical value by specifying that exactly one of the three parameters must be passed, which is not evident from the schema (none are required). This guides the agent on proper invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns 'normalized release comparison metrics from a public Box Office Mojo showdown page,' specifying the verb and resource. Among many boxofficemojo sibling tools (e.g., boxofficemojo_brand, boxofficemojo_calendar), 'showdown' uniquely identifies this tool's focus.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description instructs to 'pass exactly one of `id`, `path`, or `url`,' which is a clear usage rule for parameters. However, it does not provide context on when to use this tool versus alternatives or when not to use it, leaving the agent to infer from the name and sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It states the tool returns normalized tables from a public page, implying a read operation, but does not disclose any behavioral traits such as rate limits, authentication requirements, or error handling. More detail is needed for a safe agent interaction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no redundancy, front-loading the purpose. Every word adds value, including the specification of returned tables and the parameter constraint.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description mentions 'release-group and market-gross tables' which gives some idea of the return structure. However, it lacks details on the format or any edge cases. For a tool with many siblings, this is moderately complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with simple descriptions. The description adds crucial semantics by requiring exactly one parameter, which is not captured by the schema's optional settings. This constraint prevents misuse.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'normalized Box Office Mojo title release-group and market-gross tables' from a public title page, using a specific verb ('Returns') and resource ('title detail'). It distinguishes itself from sibling tools like boxofficemojo_release or boxofficemojo_release_group by specifying the exact data returned.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly instructs to 'Pass exactly one of id, path, or url', providing clear usage guidance. While it does not explicitly state when to use this tool over siblings, the instruction is sufficient for correct invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the return type (estimate-vs-actual rows) and error behavior for empty pages. However, it does not mention rate limits, authentication, pagination, or data freshness limits, which are important for an agent to know.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no extraneous words. The main purpose is front-loaded, and additional information about error behavior is efficiently provided.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains what the tool returns and one edge case, but without an output schema, it lacks details on the structure of the rows (e.g., fields, data types). For a tool that returns rows, more context would be beneficial. Adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameter descriptions already explain 'weekend number' and 'year range'. The tool description adds no further detail beyond the schema, so it meets the baseline but does not enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized estimate-vs-actual rows from Box Office Mojo's domestic weekend estimates chart. It distinguishes from siblings like boxofficemojo_weekend_domestic by specifying 'estimates' and the nature of the data. The mention of error behavior adds clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for estimate-vs-actual comparisons, which differentiates it from the sibling boxofficemojo_weekend_domestic. However, it does not explicitly state when not to use it or provide direct alternatives. The error behavior note is helpful but not a full guideline.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description takes on the full burden of disclosure. It transparently explains default exclusion of inactive accounts, the partial population of engagement metrics, and that creators without those metrics sort last and omit fields. This is thorough behavioral documentation beyond what the schema alone provides.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and concise. It starts with a clear purpose, then efficiently covers filtering, sorting, and data coverage. Every sentence adds essential information without redundancy. The length is appropriate for the complexity of the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with 11 parameters and no output schema, the description covers filtering behavior, sort options, and data coverage well. It explains that engagement metrics are missing for some creators. However, it does not describe the response format or pagination metadata, which would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds significant context beyond the schema, such as the case-insensitive handle lookup, the coverage nuances for engagement_desc sort, and the default behavior for include_inactive. This extra information helps the agent understand parameter interactions and data quality.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches a TikTok creators dataset, specifying the indexed fields (follower counts, verified status, niche, engagement). However, it does not explicitly distinguish this tool from sibling tools like tiktok_search_user or tiktok_profile, which could cause confusion about when to use the dataset search vs live lookup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some usage guidance: it explains that inactive accounts are excluded by default and how to include them, and it details the sort enum behavior and coverage nuances. However, it does not compare this tool to alternatives or state when to use it over other TikTok creator search tools, leaving the agent to infer from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It states the tool returns one enriched record, which is transparent about the output. It also specifies the dataset id enum value. However, it could disclose more about behavior such as potential errors for missing login or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no unnecessary words. It is front-loaded with the core action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (1 param, no output schema), the description is fairly complete but lacks information about error handling (e.g., if login not found) and the structure of the returned record. Since no output schema exists, the description could compensate by summarizing typical fields.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema for the single parameter 'login' already has a description (GitHub login, max 128 characters), and schema coverage is 100%. The tool description mentions 'by login' but adds no significant extra meaning beyond what the schema provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get', resource 'GitHub user from the dataset', and specifies it returns one enriched record by login from a specific dataset id. It distinguishes from sibling tools like datasets_github_users_search which likely return multiple results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving a single GitHub user by login, but does not provide explicit guidance on when to use this tool versus alternatives like datasets_github_users_search or when not to use it. No exclusions or prerequisites are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry burden. It mentions data source, time range, and a usage tip for latest=true, but lacks details on pagination behavior, rate limits, return format, or destructive potential. The tool is read-only, but this is not explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (5-6 sentences) and front-loaded with purpose, data source, and key enums. No superfluous content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, so description should explain response contents. It mentions data sources but not specific fields, pagination, or result structure. The schema's many filter parameters partially compensate by implying output includes those fields.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. The description adds value by explaining the joined datasets (affordability metrics) and providing a concrete usage tip for latest=true. However, enum lists largely duplicate schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches the US housing markets dataset, specifies data sources (Redfin + Census ACS), lists key enums, and distinguishes from sibling tools like datasets_housing_markets_facets and datasets_housing_markets_item by focusing on search functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains what the tool does but does not explicitly state when to use it versus alternatives like facets or item tools. It implies search use case but lacks explicit guidance or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses key behavioral traits: data is from news outlets' staff pages, no cross-outlet search, and records include outlet, title, beat topics, and contact info. It does not mention pagination constraints or rate limits, but provides substantial transparency about the data source and coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and reasonably concise. It starts with core purpose, explains dataset origin, then lists enums. Every sentence adds value, but could be slightly more compact by avoiding repetition of enum values that are already in the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description compensates by explaining the return fields (outlet, title, beat topics, contact info). It also describes the enum options and data source. Missing explicit mention of pagination limits (page * page_size <= 10000) which is only in schema, but overall complete for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (all 8 parameters described). The description lists enum values for vertical, contact_type, and sort, which are also in the schema descriptions, so it adds little beyond what the schema already provides. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool searches the journalists dataset, explains the dataset's origin (crawled from news outlets' staff pages), and distinguishes it from other dataset search tools by specifying the data source and content. It uses a specific verb+resource and provides enough context to differentiate from siblings like datasets_airbnb_search or datasets_jobs_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description explains that there is no cross-outlet upstream search and that the dataset is built from a curated roster, which implies limitations but does not explicitly state when to use this tool versus alternatives such as datasets_journalists_facets or datasets_journalists_item. No when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description adequately discloses the return data (filing-history, financials, insider activity) and the 404 behavior for missing CIK. It does not mention destructive actions, but the tool is clearly read-only. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loaded with purpose, and every sentence provides value. No redundancy or unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter tool with no output schema, the description fully covers what the tool returns, including the dataset id and error case. It is complete enough for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the schema already describes the CIK parameter with format examples. The description adds no additional semantic nuance beyond what the schema provides. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'a company from the SEC companies dataset by CIK'. It specifies the return content (filing-history, financials, insider activity). While it does not explicitly differentiate from sibling tools like datasets_sec_companies_search or datasets_sec_companies_financials, the purpose is well-defined.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a specific CIK is known and a comprehensive summary is needed. However, it does not provide explicit guidance on when to prefer this tool over siblings (e.g., for just insider activity, use datasets_sec_companies_insider). No 'when not to use' or alternative suggestions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries the full behavioral disclosure burden. It does add some transparency by noting the data is from Depop's public user-search API and that the result contains a username for further lookups. However, it does not mention pagination, result volume, response format/fields beyond the username, or return edge cases, leaving gaps for a search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is mostly efficient and front-loaded—the core action is in the first sentence. The main flaw is slight redundancy: 'Search Depop sellers by name' and 'Finds Depop users/sellers by name or username' repeat the same core idea, so the text could be condensed into three sentences without losing value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter search tool with no annotations and no output schema, the description supplies an adequate amount of operating context: what it searches, how the result can be chained into depop_shop, and the public-source provenance. It does omit the response structure details and whether multiple matches are returned, but for a simple lookup that flows into a known endpoint, it is sufficiently complete for an agent to select and call it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'query' is fully described in the schema (100% coverage: 'Seller name or username to search for'). The description merely echoes that the tool finds by name or username, and the added mention of passing the matched username to depop_shop is about post-processing, not about the parameter itself. It adds no critical meaning beyond the schema, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a precise verb and resource ('Search Depop sellers by name') and clarifies it finds users/sellers by name or username. It marks out a dedicated seller-lookup scope and even distinguishes itself from the shop-detail step by pointing to the next endpoint, depop_shop. This sets it apart from sibling Depop endpoints like depop_search (items) and depop_suggest.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear contextual guidance: use it to find a seller, then pass the matched username to GET /depop/shop/{username} for the full shop. It does not explicitly name alternatives or say when not to use it, but it implies the normal flow and provides a 'next step' for the result, which is practical guidance for an agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It usefully discloses that no auth token is required and that the feed comes from the Android mobile guest experience. However, it omits potential behavioral details like rate limits, pagination behavior, or error handling, leaving some uncertainty.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise sentences, all of which add value. It front-loads the main purpose, then adds differentiating and auth-related information, with no fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With only two parameters and no output schema, the description explains the tool's purpose and prerequisites well. However, it does not describe the output format or any pagination/limitations, which would be helpful for a tool without an output schema. Still, it covers the essential context for a simple read-only feed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with clear descriptions for latitude and longitude. The description adds only that it is 'location-based' but does not specify format, bounds, or other nuances. Per the baseline for high schema coverage, this is adequate but not enriched beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves DoorDash's location-based 'nearby stores' explore feed. It explicitly distinguishes itself from search and autocomplete by noting no search query is required, which helps the agent differentiate it from sibling tools like doordash_search and doordash_search_autocomplete.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: use this when you want the browse feed without a search query, and it also notes no account or token is needed. It does not explicitly mention when to avoid using it or name alternative tools, but the contrast with search/autocomplete provides sufficient usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It discloses a significant behavioral trait: 'No DoorDash account or caller-supplied token is required' and specifies the data source ('Android mobile guest experience'). It does not mention error handling, rate limits, or response format, but the auth context and source are valuable additions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: the first is a concise action statement, and the second packs useful details about content, source, and auth requirements. While the phrase 'for a location' is slightly redundant given the required coordinates, every sentence contributes meaningful information without excessive verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema, the description gives a clear idea of what the feed returns (restaurants, grocery stores, offers) and notes the no-auth requirement. It covers the essential context for a simple feed tool with pagination parameters, though it omits details about result structure or pagination behavior. Given the absence of annotations and output schema, this is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides descriptions for all four parameters (latitude, longitude, limit, offset) with 100% coverage. The description adds context about the feed contents ('trending restaurants, grocery stores, and promotional offers') but does not enhance parameter-specific semantics beyond what the schema already states. Thus, it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as 'Get DoorDash store discovery feed' and specifies that it returns nearby trending restaurants, grocery stores, and promotional offers. This distinguishes it from sibling tools like doordash_search (which likely performs query-based search) and doordash_explore, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use cases (discovery feed for a location) via the required latitude/longitude, but it does not explicitly state when to use this tool versus alternatives like doordash_search or doordash_explore. There is no exclusionary guidance or mention of alternative tools, so usage context is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the full burden. It discloses that results are normalized, lists output fields, mentions page-based pagination, and identifies the underlying source API. This is a transparent description of behavior, though it does not mention rate limits or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the core purpose, and efficiently enumerates output fields. The final sentence about the source API is useful but could be considered slightly redundant; no wasted content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is a straightforward news search endpoint. The description explains the returned fields and pagination, which adequately covers the output in the absence of an output schema. It does not cover all edge scenarios like sorting or rate limits, but for its complexity, it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% coverage with descriptions for all three parameters. The description adds context for 'q' (query string) and 'page' (page-based pagination) but does not elaborate on 'region'. Thus the description complements the schema but does not add significant new meaning beyond it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search DuckDuckGo news results' with a specific verb and resource, and then enumerates the returned fields (title, destination URL, source, excerpt, thumbnail, timestamps). This distinguishes it from sibling search tools like duckduckgo_search and duckduckgo_image.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for news search but does not provide explicit guidance on when to use it vs. alternatives such as duckduckgo_search or bing_news. No exclusions or alternative recommendations are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It mentions the source (ESPN's public JSON) implying no auth, and lists return fields. However, it does not disclose rate limits, update frequency, or other behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loading the core purpose. It could be more structured (e.g., bullet points for enums), but it is efficient and informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, but the description describes return content (player fields, head coach). For a simple roster lookup, it is fairly complete, though missing pagination or error handling details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. The description adds value by listing specific enum values for sport and league, and clarifying that team can be numeric ID or abbreviation, exceeding schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a team's roster with player details and head coach from ESPN's public JSON. It specifies the accepted sports and leagues, making the purpose very specific and actionable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly say when to use this tool over siblings like espn_athlete or espn_team. It provides context on what is returned but lacks guidance on when it is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry behavioral info. It states it returns trending repos, which is straightforward, but lacks details on rate limits, authentication, pagination, or other behaviors beyond the basic purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, no filler. Front-loaded with purpose, every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Simple tool with two optional parameters and no output schema. Description fully covers the tool's behavior and context, leaving no gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters. Description adds no new meaning beyond the schema, meeting the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'List trending GitHub repositories' with a specific verb and resource. It distinguishes from siblings like github_trending_developers and github_search_repositories by specifying it returns repos from the trending page.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage for discovering popular repos, but no explicit guidance on when to use versus alternatives like github_search_repositories or when not to use. No exclusions or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that data is credential-free, public, and parsed from Goodreads' GraphQL cache. This provides useful context beyond the missing annotations, though it omits details like error handling or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description uses two concise sentences: the first states the purpose, the second details return fields and data source, with no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple one-parameter schema and no output schema, the description fully explains returned fields and data source, making it complete for an agent to use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes the single parameter 'id' as 'Goodreads book id' (100% coverage). The description adds no additional semantic information, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a single Goodreads book and lists specific returned fields (description, authors, series, etc.), distinguishing it from sibling tools like goodreads_search or goodreads_author.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus siblings (e.g., goodreads_search for finding books, goodreads_author for author details). It only implies usage when a book ID is known.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It states the tool is read-only ('Returns...'), which implies no side effects. However, it does not mention rate limits, authentication requirements, or the fact that only public awards are returned. The term 'normalized' is vague. Overall, minimal but not misleading.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences conveying purpose, output, and parameter usage. No redundant or extraneous information. The structure places the core purpose first, followed by the key parameter rule.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is no output schema, the description should briefly describe the structure of the returned data (e.g., 'includes award name, year, category') to help the agent understand what to expect. It only says 'award rows', which is vague. The tool has only two parameters, so the input side is well-covered, but the output side is under-specified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage with basic descriptions for 'id' and 'url'. The description adds value by enforcing 'exactly one of id or url', which is a critical usage constraint not present in the schema (where both are optional). This prevents common errors. However, no further details on parameter semantics are added.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'normalized public IMDb award rows for a person', specifying both the resource (awards for a person) and the action (returns). It distinguishes itself from sibling tools like 'imdb_name' and 'imdb_name_credits' by focusing on awards, not basic info or credits.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a useful constraint: 'Pass exactly one of id or url', guiding parameter usage. However, it does not provide guidance on when to use this tool versus alternatives (e.g., when to use imdb_name vs imdb_name_awards). No explicit when-to-use or when-not-to-use context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It mentions 'public' data but does not disclose whether the operation is read-only, authentication needs, rate limits, or pagination behavior. Adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two succinct sentences conveying purpose and key constraint. No superfluous content; each sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, yet the description only mentions 'normalized public IMDb award rows' without specifying fields or structure. For a simple retrieval tool, it suffices but lacks completeness about return format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with clear definitions for 'id' and 'url'. The description only adds a usage constraint ('exactly one'), not enhancing parameter meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized public IMDb award rows for a title, with specific verb 'returns' and resource 'normalized public IMDb award rows'. It distinguishes from sibling tools focusing on other aspects of IMDb titles.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs to pass exactly one of 'id' or 'url', which helps the agent avoid invalid calls. While it doesn't compare with alternative tools, the unique purpose makes the context clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries full burden. It discloses default limit and clamping, and seasonal filtering, but does not mention behavior on invalid input, rate limits, or empty results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences with no unnecessary words. Purpose is front-loaded, and each sentence adds essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and no output schema, description covers key aspects but lacks details on return format or error scenarios, which could help an agent handle edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage, but description adds value by clarifying mutual exclusivity of id and url, and explaining the season parameter's effect. This goes beyond the schema's descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool returns normalized public IMDb episode rows for a series title, using specific verbs and resource. It distinguishes itself from sibling IMDb tools by focusing on episodes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description provides usage guidance on passing exactly one of id or url and optional season filter, but does not explicitly state when to use this tool versus other IMDb tools like imdb_title or imdb_title_credits.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It states it 'returns' data, implying a read operation, but does not explicitly mention no side effects, rate limits, authentication needs, or what happens if the title is not found. The description lacks sufficient behavioral context for a data retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of two short sentences. The first sentence identifies the purpose, and the second provides critical usage guidance. Every part earns its place with no wasted words. It is well front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is minimally adequate given the tool's simplicity. It lacks details about the return format or fields (no output schema exists), but 'normalized public IMDb filming-location rows' gives some idea. Given the many sibling tools, a bit more context about the output structure would improve completeness. Score 3 reflects this balance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with descriptions for both parameters ('IMDb title id' and 'Absolute URL'). The description adds semantic value by specifying that exactly one of `id` or `url` must be passed, clarifying mutual exclusivity that the schema's optional flags do not convey. This goes beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool returns 'IMDb title filming locations' as 'normalized public IMDb filming-location rows'. It uses a specific verb ('returns') and resource ('filming locations'), and among many IMDb sibling tools, this one is uniquely focused on filming locations, making its purpose distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Pass exactly one of `id` or `url`', which is a clear usage constraint. However, it does not provide guidance on when to use this tool versus other IMDb title tools (e.g., for different data like goofs or reviews), but the parameter instruction alone is helpful and above average.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states 'Returns normalized public IMDb goof rows', which implies a read operation, but does not detail any behavioral aspects such as rate limits, pagination, or the possibility of no results. The description is minimal and lacks transparency about the tool's behavior beyond its output.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: the first states the tool's purpose, the second provides a clear usage rule. Every word is necessary, and the information is front-loaded. No redundancy or wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and annotations, the description is minimally adequate. It tells the agent what the tool does and how to call it, but does not describe the format of the returned goof rows or any edge cases. For a simple lookup tool, this may suffice, but more detail would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides descriptions for both parameters (id and url), so baseline coverage is 100%. The description adds value by clarifying that exactly one should be used, which is not enforced by the schema. This mutual exclusivity guidance is a meaningful addition beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the purpose: it returns IMDb goof rows for a title. The verb 'Returns' and the resource 'normalized public IMDb goof rows' are specific. It distinguishes itself from sibling tools like imdb_title_awards or imdb_title_credits by focusing specifically on goofs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states to pass exactly one of `id` or `url`, which is a clear usage instruction. However, it does not provide guidance on when to choose this tool over alternatives or when not to use it. The context of sibling tools implies its specific purpose, but no exclusions are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It meaningfully explains the dual transport mechanism (credential-free GraphQL API for basic requests, web-page transport for page 2+ or fromage), notes that the response shape is normalized across both, and explicitly states the sort default. This goes beyond a simple 'searches jobs' description and provides useful operational expectations, though it stops short of describing rate limits or failure modes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-organized and appropriately sized: it opens with a clear purpose statement, then adds two sentences of transport detail, and closes with the sort enum/default. Every sentence adds value, and there is no padding or redundancy. The structure is front-loaded and easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (6 parameters, no output schema), the description provides sufficient context by explaining the transport routes, normalization, and sort option. It does not describe the response shape, but the 'same normalized response shape' hint partially compensates. It could be improved by hinting at what fields are returned or by positioning it among sibling search tools, but it is largely complete for practical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers 100% of the parameters, so the baseline is 3. The description adds extra meaning by specifying that `sort` defaults to `relevance` (which the schema does not state) and by giving behavioral context to `page` and `fromage` as triggers for the fallback transport. This enriches the parameter understanding beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool searches Indeed job postings by keyword and location, using the verb 'searches' with a specific resource. It distinguishes itself from siblings like indeed_job (which likely retrieves a specific job) implicitly, but it does not explicitly name alternatives. Overall, the purpose is clear and specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives such as indeed_job or google_jobs_search. It does provide internal context about transport selection (page 1 vs page 2+ or fromage), which implies when certain features are used, but there are no explicit when/when-not guidelines or mentions of sibling tools. The usage context is only implied through the search-by-keyword-and-location framing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does disclose that the tool returns autosuggestions, aggregates across retailers, and uses public data, which implies a safe read operation. However, it omits details about authentication, rate limits, or response structure beyond 'suggestions,' leaving some behavioral uncertainty.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the core purpose. The third sentence ('Public data sourced from Instacart's own cross-retailer search') adds useful public-data context but is somewhat redundant with the second sentence's emphasis on cross-retailer search, so it is not maximally taut.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter tool with no output schema, the description is reasonably complete: it states the input context, the result type ('autosuggestions'), and the scope (all retailers near a postal code). It lacks explicit named alternatives and response format details, but for this search tool the information provided is sufficient for basic invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the parameters are already documented with clear descriptions ('Free-text search term' and 'US postal/ZIP code'). The description adds only modest context by calling q a 'keyword' and tying both parameters to the cross-retailer autosuggestion behavior, but it does not substantially enhance the schema's parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description has a specific verb and resource: 'Search Instacart product terms near a postal code.' It further distinguishes itself by clarifying that it returns 'search-term autosuggestions' across every retailer rather than one specific store, which separates it from sibling tools like instacart_search or instacart_stores.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use this tool: when you want autosuggestions aggregated across all retailers near a postal code. It explicitly contrasts with 'one specific store,' but it does not name an alternative tool such as instacart_search, so the guidance is clear but not fully explicit about alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It adds context by noting 'Public data sourced from Instacart's own store-discovery API', which signals a read-only, no-auth operation. However, it does not disclose response format, pagination, rate limits, or error behavior, leaving notable gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the core action. The second sentence slightly repeats 'Finds' but adds necessary detail about store types and returned identifiers. The public-data note is useful. No extraneous content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema, the description adequately explains what the tool does, the input, the output content (stores with identifiers), and the data source. It lacks explicit error handling or formatting details, but these are less critical for such a straightforward lookup.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema fully describes the only parameter (postal_code) with 100% coverage. The description essentially repeats this ('near a postal code', 'US postal code') without adding format constraints or detailed usage semantics, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Find Instacart stores near a postal code' with a specific verb and resource. It further defines the scope (US postal code) and distinguishes this tool from siblings by explaining it returns storefronts with identifiers needed for item lookups, which is distinct from item/search tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a usage workflow: use this tool to obtain store identifiers, then use those for item lookups ('each with the identifiers needed to look up its items and search suggestions'). This provides clear context, though it doesn't explicitly name alternative tools or exclusion conditions, which would merit a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses credential-free access and public data, implying read-only behavior. It does not mention rate limits or other constraints, but the essential safety traits are covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences, all informative and front-loaded with the purpose. No redundant text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers what the tool does, the required company identifier, and optional filters. It mentions 'detail is inline' and 'ATS JSON', but does not specify the output structure (e.g., array of objects). For a simple list tool, this is mostly adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds value by clarifying that 'company' is the Recruitee subdomain from the careers URL. Filters are listed but largely repeat schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists Recruitee offers with optional filters, and explains the company parameter. However, it does not explicitly distinguish from the sibling tool 'jobs_recruitee_offer' (singular), which likely retrieves a single offer.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for listing public Recruitee offers but provides no guidelines on when to use alternatives or when not to use this tool. It lacks explicit 'when to use' context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
In the absence of annotations, the description discloses important behaviors: it omits recruiter personal data, is credential-free (public), and returns JSON. This provides good transparency beyond the schema, though could mention error behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, clear and to the point with no wasted words. Could be slightly more structured, but effectively conveys the necessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema or annotations, the description covers the return content (jobAd description, omitted recruiter data) and the public nature. It is complete enough for a simple retrieval tool, though an explicit output format note would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both `id` and `company`. The description does not add additional parameter-level meaning beyond what the schema provides, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves a single SmartRecruiters posting, including the jobAd description, and specifies that recruiter personal data is omitted. It distinguishes from the sibling tool `jobs_smartrecruiters_postings` which lists postings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the tool retrieves a single posting, but does not explicitly provide when-to-use or alternatives like `jobs_smartrecruiters_postings` for listing. The mention of 'credential-free' is helpful but not a full usage guideline.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions it uses a GraphQL endpoint and reinforces type/limit behavior, but lacks details on rate limits, side effects, or return format, which is moderate given no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with purpose, and efficient with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main functionality and key parameters but does not explain optional parameters (country, language) or output structure, which is an adequate baseline for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers all parameters (100%), and the description adds specific constraints like 'Type accepts only all, movie, or show' and 'limit defaults to 20 and clamps to 50', providing extra clarity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets popular JustWatch titles, and it distinguishes from sibling tools like justwatch_search or justwatch_discover by focusing on popular items.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides parameter constraints (type and limit) but does not give guidance on when to use this tool over alternatives, such as justwatch_search for searching or justwatch_discover for browsing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries the burden. It explicitly states 'credential-free public Letterboxd data,' which discloses authentication requirements. It does not mention pagination, rate limits, or error handling, but the disclosure of public access is a key behavioral trait.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the primary purpose. No unnecessary words. It efficiently conveys the tool's function and optional scoping.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool returns a chart (likely a list), the description does not explain the return format or any additional context like sorting or limits beyond the input parameters. It is adequate but could be more complete for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so schema already documents parameters. The description adds the concept of 'scoping' but does not add significant meaning beyond what is in the schema parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb (Get), resource (popularity-ranked film chart), and optional scoping. It distinguishes this from other Letterboxd tools like letterboxd_film or letterboxd_search by focusing on a popularity chart.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use vs. alternatives. The description implies it's for popularity rankings, but does not mention alternatives like letterboxd_search for text search or letterboxd_film for individual film details.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but the description states 'Credential-free public Metacritic data,' which clarifies it requires no authentication and provides public data. This adds useful behavioral context beyond the implied read-only nature of 'Get'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences: the first states purpose and enumerates return fields, the second adds the credential-free note. No unnecessary words, front-loaded with core information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-resource retrieval tool with no output schema, the description covers all observed return fields (Metascore, user score, genres, platforms, etc.) and notes public access. It is sufficiently complete for an agent to understand the tool's output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'slug' has a schema description 'Metacritic game slug.' The tool description adds no further semantic information about the slug format or examples, so it provides no added value over the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The tool name 'metacritic_game' combined with the description 'Get a Metacritic game' clearly indicates it retrieves game-specific data. The description lists detailed return fields (Metascore, user score, genres, etc.), differentiating it from siblings like metacritic_movie or metacritic_tv.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like metacritic_game_critic_reviews or metacritic_game_user_reviews. The description lacks explicit context for choosing this over other Metacritic-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden. It discloses pagination, return fields, and that data is public. However, it does not mention sorting behavior, rate limits, or error conditions (e.g., invalid slug), leaving some gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences: action, return fields, and a note on accessibility. No wasted words. Front-loaded with the verb and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description partially covers return values but omits format details and sorting options. For a simple list tool, it is mostly adequate but missing some behavioral context like sort semantics.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds limited value beyond the schema. It mentions 'paginated' which contextually explains page/per_page, but sort order values are not explained. The return field list is helpful but does not directly clarify parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists Metacritic movie critic reviews, specifying it returns professional/publication reviews. It distinguishes from sibling tools for other media types (game, TV) and user reviews by explicitly saying 'movie's critic reviews' and 'professional/publication reviews.'
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving professional reviews for a Metacritic movie. It notes pagination and credential-free access, setting clear expectations. While it doesn't explicitly exclude alternatives, the context of sibling tools (e.g., metacritic_game_critic_reviews) makes the domain clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly states that 'upstream comment bodies are not exposed' and that data is derived from credential-free public sources, which are important constraints beyond what the input schema reveals.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: the first clearly states the core purpose ('returns normalized Metaculus question rows'), and the second adds vital behavioral context (credential-free, no comment bodies). No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so the description should better hint at the return format. 'Normalized Metaculus question rows' is vague; it does not specify fields or structure. Also missing pagination details beyond recency order. Adequate but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% description coverage for both parameters (limit and topic). The description does not add meaning beyond the schema; it only redundantly mentions 'default 10' in the first sentence? Actually, it doesn't mention parameter details. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns normalized Metaculus question rows for questions referenced by recent public comments, ordered by comment recency. This distinguishes it from sibling tools like metaculus_top_comments (which likely returns comment bodies) and metaculus_question (which returns individual question details).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for fetching questions that have recent comments, but does not explicitly state when to use this versus alternatives (e.g., metaculus_top_comments for actual comment text). The note about 'credential-free public Metaculus data' provides context but no exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the return contents and the supported query modes, but it does not specify what happens when no parameters are supplied (schema has no required fields), whether results are live vs. historical, or any limitations/error behaviors. This is a moderate level of disclosure, not a full behavioral picture.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: the first states the core purpose, the second lists return fields and query modes. It is front-loaded, every clause adds information, and there is no redundant or filler wording.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main intent and the obvious use cases for a schedule/scores tool. However, since no parameters are required and no output schema exists, it leaves ambiguity about default behavior (e.g., what happens with no args) and the exact response structure. The listed return fields partially mitigate this but do not fully specify edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds a little value by grouping parameters into 'one date or date range' and 'optionally filtered to a team,' but it does not provide format details or additional semantics beyond what the schema already states for each parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('the MLB schedule and scores'), then enumerates the return fields (games, teams, scores, status, probable pitchers, venue, series) and the query modes (one date/date range, optional team filter). This clearly distinguishes it from sibling tools like mlb_game, mlb_standings, or mlb_teams by scope and purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives clear context on when to use the tool: 'for one date or date range, optionally filtered to a team.' This conveys the primary use cases and parameter combinations, though it does not explicitly name alternative tools or state when NOT to use it (e.g., 'use mlb_game for a single game detail').
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full transparency burden. It does disclose the accepted group values, but it does not describe the return format, whether season is optional (though the schema shows it is), or any other behavioral detail like data granularity or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact at two sentences, with the main action front-loaded. Every sentence provides useful, non-redundant information without filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with no output schema, the description gives the essentials (one team, season, groups) but lacks a note on what the returned statistics look like (e.g., a list of stat categories). Given the existence of multiple MLB sibling tools, a bit more context on output shape or typical use cases would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes all parameters (100% coverage), providing a baseline of 3. The description adds specific valid values for 'group' (hitting, pitching, fielding), which is more informative than the schema's generic 'Statistics group'. Other parameters are not enhanced beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and the resource ('MLB team season statistics'), and further clarifies it returns one team's statistics. This distinguishes it from sibling tools like mlb_league_stats or mlb_player_stats by the 'one team' scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for fetching a specific team's season stats but does not explicitly state when to use this tool instead of alternatives such as mlb_league_stats or mlb_player_stats. No exclusions or alternative tool names are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It lists the types of transactions included, which is useful, but it does not mention other behavioral aspects like pagination, ordering, or what happens when no results are found. No contradiction with annotations exists since none are present.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences but slightly redundant—'List MLB transactions' is repeated in the second sentence with elaboration. It is still concise and free of unnecessary detail, though it could be tightened to a single sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with no output schema, the description covers the main purpose and enumerates transaction categories, helping an agent understand what types of data to expect. It does not explain optional filters like team_id or player_id, but these are fully described in the schema. Overall, adequate for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all four parameters. The description adds no parameter-specific information beyond what the schema provides; the mention of 'date range' simply maps to start_date and end_date already described. Thus the baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool's function: 'List MLB transactions' and enumerates specific transaction types (signings, trades, options, assignments, injured-list moves). This specificity distinguishes it from sibling MLB tools like mlb_schedule or mlb_team_roster.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states the tool operates 'for a date range,' providing clear context for when to use it. It does not explicitly mention alternatives or exclusions, so it does not warrant a 5, but the intended use case is evident.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It notes the data is public and lists return fields, but does not address rate limits, authentication, or edge cases, giving moderate transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded, but slightly redundant with 'full detail' repeated in both sentences. Overall it is efficient and no irrelevant content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description lists the key return fields, making it largely adequate for a simple lookup tool. It could mention error handling, but for this complexity it is complete enough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema fully documents the 'id' parameter (100% coverage), so the baseline is 3. The description adds no extra param details beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get a Pinterest pin's full detail' and enumerates specific fields (title, description, image, board, pinner, comment count, save count, creation time), distinguishing it from sibling tools like pinterest_search or pinterest_user.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The context implies usage when a specific pin ID is known, but it does not explicitly mention when to use alternatives or when not to use this tool, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses key behaviors: it returns pageable data, includes pagination via next_page, and is credential-free public data. However, it does not discuss rate limits, error handling, or whether data is read-only (though implicit).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the main action, and every sentence adds value. No unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description adequately covers purpose, parameters, and pagination. It could mention valid category UUIDs or error behavior, but it is fairly complete for a public data tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description enriches all four parameters beyond the schema: explains cc as region+currency, l as language, id as category UUID, and page with pagination behavior. This adds significant context for correct usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool browses a PlayStation Store category grid by UUID and returns per-item details plus filter facets. It is specific about the resource and action, but does not explicitly differentiate from sibling tools like playstation_browse or playstation_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains how to use parameters (pagination, region, language) but provides no guidance on when to use this tool versus alternatives. No exclusions or sibling comparisons are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses credential-free access, the API endpoint, and the 'macro' tag, but lacks details on pagination behavior, rate limits, return format, or error handling. The mention of 'keyset cursor' implies pagination but is not explained.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: the first clearly states the purpose, the second adds technical context. No extraneous information. Front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, so the description should compensate. It mentions 'normalized macroeconomic event rows' but does not specify fields, data types, or pagination structure. For a list tool, more detail on expected output is needed for full completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides descriptions for both 'cursor' and 'limit' (100% coverage). The description adds that the tool uses a specific API endpoint and tag, but does not elaborate on parameter usage beyond what the schema states. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'List' and clearly identifies the resource 'Polymarket macro dashboard events'. It distinguishes this tool from siblings like 'polymarket_events' by specifying that it returns macro dashboard events from a particular page.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly indicates when to use this tool (when macro dashboard events are needed) by naming the specific page and tag. However, it does not explicitly state when not to use it or list alternatives among the many sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It mentions credential-free access and lists enum values but does not disclose rate limits, mutation behavior, or pagination details beyond cursor/limit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: first states purpose, second explains key parameters. Front-loaded with no extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 6 optional params and no output schema, the description covers purpose, data source, and enums, but omits description of return value structure (e.g., fields of normalized event rows). Could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds meaningful context by listing all enum values for status, sort, and recurrence, and clarifying cursor and limit behavior. This supplements the terse schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists Polymarket predictions, specifies the data source (Gamma events/keyset JSON for /predictions page), and distinguishes from siblings like polymarket_events or polymarket_markets by focusing on predictions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly guide when to use this tool versus alternatives. While the enum details help, there is no comparison with similar Polymarket tools or conditions for preferred use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses that the data is public and no auth is needed, but does not mention rate limits, side effects, or any other behavioral traits beyond the basic read-only nature. The description is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is composed of two concise sentences with zero fluff. It front-loads the purpose and immediately provides key behavioral context, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of an output schema, the description does not explain the return format (e.g., order book depth per token). It adequately covers purpose and auth requirements but misses details that would fully inform an agent about expected output. For a simple tool it is sufficient but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single 'body' parameter described as 'Token ids request body'. The description adds the detail of 'up to 25 token ids' but does not specify the expected structure of the body (e.g., array of strings). Baseline 3 is appropriate as schema does heavy lifting but description adds minimal value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get', the resource 'Polymarket token order books', and the scope 'up to 25 Polymarket token ids'. It effectively distinguishes from the singular sibling 'polymarket_token_orderbook' by indicating bulk capability.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions that it uses 'credential-free public CLOB market-data JSON' and does not require authentication, providing context for when to use. However, it lacks explicit when-not-to-use guidance or direct comparison to alternative tools like 'polymarket_token_orderbook'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses a useful behavioral trait about handling 503 errors via the Retry-After header and notes that posts are 'normalized public posts'. This adds context beyond what the schema provides, though it does not cover all behaviors like pagination mechanics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (three sentences), front-loaded with the primary action, and every sentence adds value—purpose, return summary, and error handling. No wordiness or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description clearly states the tool's purpose and error behavior, but with no output schema, it leaves gaps about the response format and how to use pagination tokens (e.g., where to obtain 'after'). The parameter schema covers options but not response semantics.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameters are fully documented in the schema. The description does not add additional parameter semantics beyond what the schema already states, so a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'List' with the resource 'Reddit subreddit posts' and clarifies it returns posts from a specific subreddit. This clearly differentiates from sibling tools like reddit_search or reddit_domain_posts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for listing posts from a given subreddit but provides no explicit guidance on when to choose this over alternatives. It does mention handling a 503 Retry-After response, which is a usage note but not about tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that the tool is read-only ('Returns...'), uses public SEC data, and specifies the returned fields (owner, role, security, shares, price). No annotations are provided, so the description carries the full burden; it is adequate but could mention non-modification more explicitly.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences and front-loads key information. It is efficient but the first sentence is a fragment ('Insider transactions (Forms 3/4/5).') which could be integrated. Overall, it is clear and compact.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the data source, what is returned, input alternatives, and access method (credential-free). Given no output schema and simple parameters, this is sufficient for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and each parameter has a description. The description adds that 'cik' and 'ticker' are alternatives, which is already implied in the schema. No additional meaning beyond the schema is provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns insider transactions from Forms 3/4/5 filings, specifying the verb 'returns' and the resource 'company's recent insider transactions'. It distinguishes itself from sibling SEC tools by focusing specifically on insider ownership filings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions providing 'cik or ticker' and states 'Credential-free public SEC data', giving some context for use. However, it does not explicitly guide when to use this tool versus alternatives like sec_filing or sec_company_submissions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states that the tool 'Returns public Shop.app product categories,' which is transparent regarding the read-only nature. However, it does not disclose potential behavioral traits such as authentication requirements, rate limits, or pagination.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences with no wasted words. It conveys the essential information efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters, no output schema, and a simple purpose (listing categories), the description is fully adequate. It explains exactly what the tool returns and leaves no ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters, and the schema coverage is 100% (empty schema). According to the rubric, 0 parameters gets a baseline of 4. The description does not add parameter-specific information because there are none, but it correctly implies that no parameters are needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'List' and the resource 'Shop.app categories'. It also specifies that it returns public product categories, which is unambiguous and distinguishes it from other shop_app tools that deal with products, shops, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as other shop_app tools like shop_app_search or shop_app_product. There is no mention of prerequisites, context, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It correctly implies a read-only operation and notes the output is 'public', which is adequate for this simple retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (two sentences, 11 words) with no superfluous information, earning its place efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with one required parameter and no output schema, the description provides all necessary information: what it does, what it returns, and the required input.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'handle' has a description in the schema ('Shop handle'), and the tool description adds no additional meaning. With 100% schema coverage, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get'), the resource ('Shop.app shop'), and the output ('public Shop.app merchant profile details'), making the tool's purpose unambiguous and distinguishable from siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is provided on when to use this tool versus alternatives (e.g., shop_app_shop_locations). The agent must infer usage solely from the name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It notes the tool uses 'SofaScore's credential-free public JSON', indicating no authentication is required and it is a read operation. However, it does not disclose potential error handling, rate limits, or response structure, which limits transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, each serving a distinct purpose: naming the tool, describing output, and providing parameter sourcing advice. No redundant words or unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema, the description does not explain the return format (e.g., list of events with what fields). It adequately covers tool purpose and parameter origin, but lacks details on what 'fixtures' entails or error conditions, leaving some ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by telling the agent to obtain `id` from search and `season` from tournament-seasons, which is operational guidance beyond the schema's numeric descriptions. This enriches parameter meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns fixtures for one round of a competition season, using specific verbs ('Returns') and resources ('fixtures'). It distinguishes from sibling tools like sofascore_event (single event) and sofascore_standings by focusing on round-level data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides guidance on obtaining parameter values ('Get `id` from search and `season` from tournament-seasons'), implying usage context. However, it does not explicitly state when to use this tool versus alternatives like sofascore_standings or sofascore_live_events, leaving potential confusion among many sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description fully carries the burden. It discloses that the tool fetches anonymous Spotify credentials at request time and that caller-supplied tokens are not required. This adds valuable behavioral context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, highly efficient, and front-loaded with the core purpose. No wasteful or redundant content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (9 parameters, no output schema, no annotations), the description provides the core purpose and authentication mechanism but lacks details on return format, normalization behavior, or parameter relationships. It is adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description does not add any extra meaning to the parameters beyond what is already in the schema, so no additional value is provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches Spotify profiles and returns normalized profile search results. It uses a specific verb-resource pair ('Search Spotify profiles') and implicitly distinguishes from sibling tools like spotify_search and spotify_profile by focusing on profile search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for profile searching without requiring user tokens, but it does not explicitly differentiate from sibling tools or provide when-not-to-use guidance. Given the many sibling tools, explicit alternatives would help.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool is credential-free and returns a specific histogram format. However, it does not mention rate limits, data freshness, or potential missing data for new apps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two efficient sentences with no waste. First sentence introduces the core function, second adds detail on output granularity and credential-free access.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description should clarify return format. It mentions 'weekly/monthly rollups plus recent daily buckets' but does not describe structure, limits, or pagination. Adequate but leaves gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters. The description adds minimal extra value, only clarifying that language can be 'all'. Baseline is 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it gets the review up/down histogram for a Steam app, specifying positive/negative recommendation counts over time with weekly/monthly/daily buckets. This distinguishes it from other Steam review tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions it is credential-free but does not explicitly state when to use this tool versus alternatives like steam_reviews or datasets_steam_reviews_search. No guidance on context or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It notes the data is estimates, credential-free, and public JSON. However, it does not mention error handling, rate limits, or what happens with invalid appids. The disclosure about estimates is adequate but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with the main purpose, and no wasted words. Every sentence adds essential context: what it returns, that it's third-party, and that it requires no credentials.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema, the description covers purpose and data source. However, it lacks information about the return structure (e.g., JSON fields) or an example, which would help the agent fully utilize the response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'appid' has a schema description 'Numeric Steam app id' with 100% coverage. The tool description adds no further detail about the parameter beyond what the schema provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves SteamSpy third-party estimates (ownership, playtime, etc.) for a Steam app. It distinguishes itself from official Steam data and among many Steam-related siblings, this is the only one explicitly mentioning SteamSpy.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description emphasizes these are 'SteamSpy estimates, not official Steam figures,' implying when to prefer this tool (when third-party estimates are acceptable) and when not (when official data is needed). It does not name specific alternative tools but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears the full burden of behavioral disclosure. It states that it returns upcoming events and mentions the sort enum values, but it does not disclose pagination behavior (despite the page parameter), response structure, or any potential limitations. This is adequate but not extensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, consisting of three short sentences that convey the core purpose and a key parameter detail. There is no redundant or unnecessary information, and it is front-loaded with the primary function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a relatively simple list tool with 3 parameters and no output schema, the description covers the main functionality and sort options. However, it lacks details about pagination limits, the structure of returned events, and any prerequisites beyond the attraction ID, leaving some ambiguity for effective invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides descriptions for all three parameters (100% coverage). The description adds value by clarifying the sort enum accepts 'relevance' and 'date', which is not specified in the schema. This extra semantic detail justifies a score above the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'List an attraction's Ticketmaster events' with a specific verb and resource. It further clarifies that it returns 'upcoming Ticketmaster events for one attraction', distinguishing it from sibling tools like venue_events or search_events by its focus on a single attraction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates the tool is for retrieving events for a specific attraction, which implies it should be used when an attraction ID is available. However, it does not explicitly mention alternatives (e.g., ticketmaster_search_events for broader search or ticketmaster_venue_events for venue-based queries) or provide when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly conveys that the tool lists categories, supports pagination, and filters by section, which are key behaviors. It does not mention response shape or rate limits, but for a read-only list operation, this is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long and front-loaded with the primary purpose. The first sentence states the tool's function, and the second provides additional detail on the categories and section values. Every word earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with three optional parameters and no output schema, the description covers the core purpose, pagination, and section values. It does not mention the return format or default pagination settings, which could be useful, but the description is still reasonably complete for the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% coverage, so the baseline is 3. The description adds value by enumerating the exact accepted values for the 'section' parameter ('all', 'concerts', 'sports', 'arts-theater', 'family'), which the schema does not provide. It also reinforces the pagination semantics for 'page' and 'per_page', though it doesn't add default values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List Ticketmaster discover categories.' It specifies the resource (discover categories) and the action (list), and provides details about the types of categories included. While it doesn't explicitly differentiate from sibling tools, the resource is unique enough that the purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool (to list categories) and provides the valid values for the 'section' parameter, but it does not explicitly mention alternatives or when not to use this tool. No guidance is given, for example, for listing events or cities, which are covered by sibling tools like ticketmaster_discover_category_events.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses a key behavioral detail: the response is a zero-based paginated feed. With no annotations, it does not cover error handling, page size, or rate limits, but for a read-only listing tool, the risk is relatively low.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no fluff. The first sentence states the action, the second explains the paginated feed and the input dependency. Everything earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with all parameters documented, the description covers the essential workflow. However, without an output schema, it would benefit from mentioning what fields each event contains or default page size, but it is adequate for basic selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters have descriptive schema entries (100% coverage), so the baseline is 3. The description adds slight context by tying the city slug to the discover-cities endpoint, but this is a minor reinforcement of existing schema info.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List events') and the specific resource ('Ticketmaster discover city'). It uniquely identifies the input as a city slug from ticketmaster-discover-cities, distinguishing this tool from other event-listing tools like ticketmaster_search_events or ticketmaster_venue_events.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It implies the prerequisite workflow: first obtain a city slug via ticketmaster-discover-cities, then use this tool. This gives a clear usage context, though it does not explicitly discuss alternatives or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Mentions cursor-based pagination but lacks disclosure on rate limits, authentication requirements, or what fields are returned. Adequate but not detailed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-load the core action and pagination detail with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, so description should explain return format. It only covers pagination, not the structure of user objects. For a search tool, it adequately explains input but lacks output completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers both parameters with descriptions (100% coverage). Description adds value by explicitly noting 'cursor-based pagination', clarifying the cursor parameter's role beyond the schema. Baseline 3, slight improvement to 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches TikTok users by keyword with cursor-based pagination, using specific verb 'Search' and resource 'TikTok users'. It effectively distinguishes from sibling tools like tiktok_search_hashtag (hashtag search) and tiktok_search (general search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives, such as tiktok_search for general content search or tiktok_profile for single user details. Mentions pagination but no exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully convey behavioral traits. It discloses that the upstream API has specific parameter naming requirements, but does not mention whether the tool is read-only, requires authentication, has rate limits, or returns any side effects. The description is minimally transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of three concise sentences with no redundant information. The purpose is stated first, followed by what is returned, and then a critical usage note. It is appropriately sized and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the single parameter and no output schema, the description adequately explains the tool's purpose and usage. However, it lacks information about the structure of the returned detail, potential error scenarios, or any additional context needed for complete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% coverage for the single parameter 'material_id', but the description adds value beyond the schema by indicating that the upstream rejects other parameter names ('id' or 'materialId') and emphasizing the correct key. This helps avoid invoking errors.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Retrieve TikTok Top Ads detail' with the specific resource 'one TikTok Creative Center Top Ads material'. It uses a specific verb and resource, and implicitly distinguishes from sibling tools like 'tiktok_top_ads_list' which returns multiple items.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear guidance on which parameter to use ('Use `material_id`') and explicitly warns that the upstream does not accept other parameter names like 'id' or 'materialId'. However, it does not explicitly state when to use this tool versus alternatives like 'tiktok_top_ads_list'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description mentions it returns metadata and static enums, but lacks disclosure of behavior such as read-only nature, authorization needs, or any potential side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two efficient sentences. First sentence states purpose, second adds detail about return content. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Simple tool with 0 parameters. Description sufficiently explains what the tool returns and mentions both dynamic and static components, making it complete for its purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 0 parameters (100% coverage). Baseline for 0 params is 4. Description adds value by noting that static UI enums are included for specific fields, but this relates to return values, not parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool retrieves TikTok Top Ads filters, a specific resource. It distinguishes from sibling tools like tiktok_top_ads_list and tiktok_top_ads_detail by focusing on filter metadata.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied: retrieving filters before using other top ads endpoints. However, no explicit guidance on when to use this tool versus alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description alone must disclose behavior. It only states it returns enum values but does not mention safety (e.g., read-only, no side effects) or any potential constraints. This is minimally transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that front-loads the purpose and lists details. Every word earns its place with no waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and no output schema, the description covers the main purpose and lists enum categories. It could be slightly improved by noting that these enums are meant to be used with other TripAdvisor tools, but it is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With no parameters and 100% schema coverage, the baseline is 4. The description adds value by listing the categories of enums returned (locales, currencies, etc.), providing useful context beyond the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves TripAdvisor enum metadata and lists specific enum categories (locales, currencies, languages, etc.). It distinguishes from sibling tools like tripadvisor_search or tripadvisor_place, which serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used when you need enum values for TripAdvisor filters, but it does not explicitly state when to use it versus alternatives (e.g., other enum tools) or provide when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It mentions pagination and the public sitemap source, implying a read-only operation. However, it does not explicitly state that the tool is non-destructive or what rate limits apply. The description adds some behavioral context but could be more explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences that are efficient and front-loaded: first sentence states purpose, second adds context, third ties to sibling tool. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains that the response contains a paginated list with slugs, linking to the complementary endpoint for details. However, it does not specify other fields in the list entries (e.g., name, url), and there is no output schema. This leaves some ambiguity about the response structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with both page and page_size documented. The description adds no new parameter semantics beyond 'paginated list', which is already implied. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists all TrustMRR startups, specifies the source (public sitemap), and explains the output (slug for each startup). It distinguishes itself from the sibling tool trustmrr_startup, which retrieves a single profile.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description tells when to use this tool (to list all startups) and implies the complementary use of trustmrr_startup for full profiles via slugs. It also mentions the benefit of not needing the authenticated marketplace API. It lacks explicit when-not-to-use or alternatives beyond the implied pairing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavior. It notes ordering, exclusions, and limit clamping (default 20, max 100). However, it does not specify if the operation is read-only, what happens with empty results, or any authentication requirements beyond JWT. The behavioral coverage is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loading the core purpose. Each sentence adds necessary information: what the tool does, details about the results, and exclusions. There is no redundant or extraneous text, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description should clarify the return format. It states 'Returns recent client IP addresses' but does not specify whether each entry is a simple IP string or an object with additional fields like a timestamp. The exclusion of console, billing, usage, and user-management endpoints is clear, but the output structure ambiguity is a gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All four parameters are fully described in the input schema (100% coverage). The description adds no additional semantic value beyond the schema, such as explaining how 'range' presets work or providing examples. It merely restates the 'range=custom' relationship from the schema, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves recent API client IPs for the current authenticated user. It specifies the data source (JWT-authenticated user's product API traffic), ordering (by last seen time), and explicitly lists excluded endpoint categories, making the purpose distinct from sibling tools like usage_overview or usage_endpoints.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on what the tool returns and its scope (user-specific, recent IPs, excluding certain endpoints). However, it does not explicitly contrast with sibling tools or state when not to use it, such as for overall usage summaries or time-series data, which would improve guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It adds useful context by stating 'Public data, sourced from Vinted's own server-rendered item page,' which reassures the agent about accessibility and origin. However, it omits potential edge cases such as behavior for invalid/removed IDs, rate limits, or whether the response structure varies. This is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the core purpose. However, there is a slight redundancy: 'A single Vinted listing's detail.' is immediately followed by 'Returns a single Vinted listing's detail:...'. This could be tightened into one sentence without losing meaning, but overall it is concise and easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one parameter, no output schema, no nested objects), the description is sufficiently complete: it names the resource, lists expected return fields, and notes the data is public. It does not explain error handling or response format, but for a simple detail-fetch tool this is not a critical gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already covers the only parameter 'id' fully with a clear description: 'Numeric Vinted item ID, from a /vinted/catalog result's id field.' The tool description does not add any further semantic detail about the parameter. Per the rubric, with 100% schema coverage, baseline is 3, and the description earns no extra credit here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Returns a single Vinted listing's detail' and then enumerates the exact fields returned (title, description, brand, size, condition, material, color, price, category breadcrumb, photos). This clearly distinguishes it from sibling tools like vinted_catalog, vinted_brand, or vinted_member, which operate on different resources or collections.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly states it retrieves a single listing's detail, implying it should be used when an agent has a specific item ID and needs its full information. The parameter schema reinforces this by explaining the ID comes from a /vinted/catalog result. However, it does not explicitly mention alternatives or exclude other use cases, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the transparency burden. It discloses that an unrecognized id returns 404 and meaningfully lists the product details returned. It does not, however, mention auth requirements, rate limits, or whether this is a read-only operation, leaving some useful behavior undisclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-formed and informative, with the key purpose and output fields front-loaded. It repeats that phrase 'full detail' twice, which is slightly redundant, but overall every sentence contributes useful information and the length is appropriate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema, the description compensates well by enumerating the key returned fields, describing how to obtain the input id, and stating the 404 error condition. A complete, concise definition for a single-parameter retrieval tool, though it could mention whether the price includes currency or special cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already gives 100% coverage for the 'id' parameter, but the description adds explanatory value: it specifies that the id is Wayfair's own 'W'-prefixed identifier, gives an example, and explains where the id originates. This is more than the schema alone provides and reduces operation errors.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb and resource: get a single Wayfair product's full detail. It enumerates the returned fields (name, brand, price, stock status, ratings, images, variants, highlights), distinguishing it from more generic or composite endpoints. Although it is one of many product-detail tools, the domain and mapping are unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It explains that the id should come from a category result's product_id or a product page URL, implicitly signaling that this tool follows id discovery via category or page. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions such as needing to call a search endpoint first.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description takes full responsibility. It discloses the fetching behavior, output formats, render escalation, and content stripping. It also notes public pages only and term compliance. This is good transparency, though it could mention rate limits or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured. It front-loads the core purpose, then provides details about formats, render behavior, and content stripping. Every sentence adds useful information without repetition or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (general scraper with nested parameters) and absence of output schema, the description covers format options, render behavior, and constraints. Minor gaps include lack of default values, error handling, and timeout info, but overall it's quite complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has a single object parameter 'scrapeOption' with 100% coverage but minimal description. The description adds meaningful context by listing format options (markdown, html, etc.) and explaining special options like render and only_main_content. This adds significant value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool scrapes a URL into various formats (markdown, HTML, links, metadata). It uses a specific verb and resource. While it doesn't explicitly differentiate from sibling domain-specific scrapers, the name and general nature imply it's for any public URL, which is clear enough.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use (for a single public URL) and mentions respecting terms and robots.txt. However, it does not provide explicit alternatives or when not to use (e.g., for private pages or when domain-specific tools are better). This leaves the agent with moderate guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the data is public and sourced from Whatnot's GraphQL API, which implies read-only and external API constraints, but it does not disclose potential rate limits, pagination behavior, or error handling for invalid/live show IDs. This meets only the baseline.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded, but the first two sentences are somewhat redundant ('Get a Whatnot live show's current shop feed' and 'Returns a Whatnot live show's current shop feed'). It could be tightened, but overall it remains concise and informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter tool without an output schema, the description adequately explains the return content (products, auctions, giveaways with seller ratings) and data source. It does not mention what happens if the show is not live, but given the low complexity, it is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (the 'id' parameter is well-described as the Whatnot live show ID, e.g. from browse results). The description adds no extra parameter semantics beyond the schema, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches a Whatnot live show's current shop feed, with a specific verb ('Get') and resource. It lists contents (products, auctions, giveaways, seller ratings) and distinguishes from sibling tools like whatnot_browse and whatnot_categories by focusing on a live show's feed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: the tool requires a live show ID, and the parameter description mentions it comes from a browse result, implying a workflow with whatnot_browse. However, it does not explicitly name alternatives or exclusions, so it earns a 4 rather than a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It mentions 'supported trailing' hinting at limitations, but does not elaborate on data format, error behavior, or additional constraints like required symbol. It adds some context beyond a bare statement but remains minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently communicates the tool's purpose and scope. No filler or repetition of schema details; every word contributes.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description should explain more about what is returned (e.g., structure, range of years, units). It provides a high-level overview but leaves the agent without details on return shape or edge cases, making it adequate but not complete for a financial data tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds value by expanding the parameter values into fuller terms (income, balance sheet, cash flow) and by noting 'supported trailing', which indicates a limitation not explicitly in the schema. This helps the agent map parameters meaningfully.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns Yahoo Finance financial statements, specifying the available statement types (income, balance sheet, cash flow) and periods (annual, quarterly, trailing). This is a specific verb+resource combination that distinguishes it from sibling tools like dividends or earnings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies its use for financial statements but does not explicitly contrast it with alternatives such as yahoo_finance_ticker_earnings or yahoo_finance_ticker_info. No exclusions or when-not-to-use guidance is provided, so it relies on the name and obvious scope.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries the full disclosure burden. It explicitly discloses pagination behavior, sort order support, and the specific output fields (author, body, reaction counts, pin status). For a read-only list tool, this is strong behavioral transparency without unnecessary detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The core function is front-loaded and compact, covering result fields, sort, and pagination in one dense sentence. The opener 'Yahoo News comment replies' duplicates the tool name, and the sourcing remark 'Sourced from Yahoo's own comment platform gateway' adds little for an agent deciding how to invoke it, so only one point is lost.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description usefully names the returned data and pagination mechanism, while the schema provides all parameter-level context. The main gap is the missing connection to the sibling workflow: an agent also using yahoo_news_comments would receive the parent comment_id but the description does not state this explicitly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already covers all five parameters with helpful descriptions, including the cursor-only-from-previous-response semantics and the origins of comment_id and content_id. The description adds no parameter-specific meaning, so it sits at the baseline 3 for fully documented schemas.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies an exact verb and resource: 'Returns a page of a comment's replies,' and lists the data returned (author, body, reaction counts, pin status). It clearly distinguishes itself from the sibling yahoo_news_comments by targeting replies to a specific comment rather than top-level comments on an article.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is implied by the phrase 'a comment's replies' and the required comment_id/content_id, so an agent can infer it should be called to fetch replies to an existing Yahoo News comment. However, the description does not explicitly explain when to prefer this tool over yahoo_news_comments or how to first obtain the required comment_id, leaving routing partially to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full transparency burden. It discloses the key behavioral variation — output entries carry entity metadata only when Yahoo resolves the term to a known entity rather than a plain phrase — and the flat-list return shape. It does not mention rate limits or network access, but for a read-only autocomplete tool this is an acceptable disclosure level.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence that front-loads the tool's purpose, then precisely describes the return shape and the optional entity variant. Every clause earns its place; it reads slightly dense but contains zero filler words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity tool with two fully documented parameters and no output schema, the description adequately covers the use case, the response structure, and the metadata variant. The only shortfall is that it never explicitly calls out sibling alternatives like yahoo_news_suggest, but the Yahoo-web-search scoping largely compensates for that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so 'q' and 'count' are already fully documented, including the default of 10 and the 1..20 clamp. The description echoes the 'partial query' semantics and adds useful output context about entity metadata, but it does not add parameter-level syntax that the schema lacks. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: it returns Yahoo's own search-box autocomplete suggestions for a partial query. It is precise about the output shape — flat list of terms with optional knowledge-panel entity metadata (type, image, subtitle, description) — which distinguishes it at a glance from the many sibling suggest tools (google_suggest, bing_suggest, zalando_suggest) and from yahoo_search, which returns actual results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly situates the tool for partial-query autocomplete use and scopes it to Yahoo's web search box, differentiating it from engine-specific siblings like google_suggest or bing_suggest. It does not explicitly enumerate when-not-to-use conditions or point to an alternative sibling, but the context is unambiguous enough for an agent to select it correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the behavioral burden. It does disclose what the tool returns (teams, score, status, venue, broadcast info) and the data source ('sports.yahoo.com's own server-rendered scoreboard page'). However, it doesn't state behaviors like timezone handling, refresh behavior for live games, network dependency, or the shape of an empty day; these would be helpful for a server-rendered page scrape.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense and largely updates the agent with the league list. The opening 'Yahoo Sports scoreboard.' is redundant with the tool name, and the long league enumeration could arguably live in the schema as an enum, but the syntax makes efficient use of words. The key facts come early and the final cover is essential for parameter correctness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter read-only tool with no output schema, the description covers the essentials: what it takes evidence, what valid inputs are, and what fields come back. A small gap remains: it never says what happens on dates with no games, nor how the 'status' field behaves for postponed/final/live games. These are minor for a tool this simple.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema describes both parameters ('Date as YYYY-MM-DD; defaults to Yahoo Sports' current scoreboard date') and ('League key'), giving 100% coverage. The description then adds crucial semantics the schema lacks: a full enumeration of all accepted lowercase league codes. Without that, an agent relying solely on the schema could pass 'NFL' or 'nfl teams' and fail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Returns games (teams, score, status, venue, and broadcast info) for a league on a date' from Yahoo Sports. Naming the exact output fields and the league-plus-date scope makes the tool clearly identifiable and separates it from sibling sports tools like espn_scoreboard or yahoo_sports_golf_leaderboard.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage context is implied, not explicit. The description does not say 'use this instead of espn_scoreboard' or mention exclusions like 'not for individual games, standings, or player data.' The league list and date/scoreboard framing strongly hint at when it applies, but no alternative tools or when-not conditions are named.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It usefully discloses the data provenance (server-rendered team page, implying a static scraping source) and that the standing summary is 'current', which adds real context. However, it omits basics such as whether the call is read-only, how stale the data may be, and what happens with invalid league/team values, leaving the agent to guess at operational behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The core purpose is front-loaded in the first two sentences, and the long league enum earns its place because the schema has no enum to capture it. There is minor redundancy between opening 'Yahoo Sports team detail' and next sentence's 'Returns one team's detail', and the enum list inflates length, preventing a perfect score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a small two-parameter read-only detail tool, the description covers the return content types, data source, all valid league values, and how to obtain the team slug, which is enough for an agent to call it correctly. Gaps include no explicit note about handling invalid input or whether a team must be in the current season, plus no mention of the fact that no annotations exist for safety.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3, but the description clearly beats that: the schema's 'League key' is a placeholder, while the description enumerates all 23 accepted league values and gives concrete slug examples ('green-bay', 'la-lakers'). It also tells the agent where to fetch the slug, which materially enriches both parameters beyond the schema text.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource ('Returns one team's detail') with an explicit field inventory (identity, colors, conference/division, current standing summary) and a named source (sports.yahoo.com's own server-rendered team page). This clearly distinguishes it from siblings like yahoo_sports_team_roster, yahoo_sports_team_schedule, and espn_team without needing to open any schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives concrete sourcing guidance for the required team parameter ('Get a team slug from the scoreboard or standings response') with examples, which is genuinely helpful. However, it never explicitly states when to choose this tool over siblings such as yahoo_sports_team_roster, yahoo_sports_team_schedule, or espn_team, nor when not to use it; the intended selection logic is implied only by the field list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does a good job by disclosing a key behavioral trait: credential-free access (no login, API key, or cookie). It also reveals that it uses Yelp's real Android app backend, which hints at an unofficial integration. This goes beyond a typical minimal description, though it does not cover rate limits or output structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose, and every word adds value. It is efficient and well-structured without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 4 parameters and no output schema, the description is adequate but not complete. It covers the essential auth trait and search scope but does not describe the return format or any pagination behavior. Given the absence of an output schema, the agent would benefit from more detail on what results look like.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all four parameters. The description only mentions 'term and location' in a general sense, adding no new semantics beyond what the schema provides. It does not enhance understanding of limit/offset behaviors.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Search Yelp businesses.' It specifies the resource (Yelp businesses) and the action (search), which distinguishes it from other Yelp tools like yelp_business (details) and yelp_business_reviews. The added detail about using Yelp's real Android app business-search backend further clarifies its scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (for term+location business searches, credential-free) but does not explicitly state when to use this tool over alternatives or mention any exclusions. There is no reference to sibling tools or conditions where another tool might be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the tool uses YouTube's InnerTube API and returns normalized results, and explains pagination behavior. However, it does not address rate limits, authentication, or non-destructiveness, which are important for behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with four sentences, front-loading the purpose. Each sentence provides necessary information without redundancy or irrelevant detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers purpose, API source, pagination, and parameter aliases, but lacks details about the return format (no output schema provided) and does not explain the effect of other filter parameters. For a search tool with 9 parameters and no output schema, more context would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds value by clarifying that q is the primary parameter and search_query is an alias, and by explaining how to use continuation_token for pagination. This goes beyond the schema's individual parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Search YouTube' and the resource, with additional details about returning normalized results and using the InnerTube API. It distinguishes this tool from sibling YouTube tools like youtube_channel_search by being a general search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions pagination via continuation_token and the alias relationship between q and search_query, but does not provide explicit guidance on when to use this tool versus other YouTube search tools (e.g., youtube_channel_search, youtube_playlist). Usage is implied but not differentiated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral burden. It discloses that results are 'normalized' and 'public,' and states the required coordinate/region context, but it omits details such as pagination behavior, response size, or any error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary purpose, and every sentence adds information. There is no filler or repetition of schema details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 9 parameters, no annotations, and no output schema, the description should provide a more complete mental model. It explains the bounds/region-id workflow well, but leaves the required 'location' parameter's role ambiguous and does not describe the shape of the returned listings beyond 'normalized.'
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents all 9 parameters with 100% coverage. The description adds the concept of 'complete map bounds' and 'region id fallback,' but does not substantially expand on parameter semantics beyond what the schema provides, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Search Zillow listings' and clarifies it returns 'normalized Zillow public listing search results.' This distinguishes it from sibling tools like zillow_property and zillow_autocomplete by emphasizing the search-result output.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides clear, actionable usage guidance: 'Callers must pass complete map bounds from autocomplete when available, or a region id fallback.' This tells the agent when to use which parameters and references the autocomplete sibling, though it does not explicitly state when not to use the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It states the tool is read-only and publicly accessible, but lacks details on pagination behavior, rate limits, or output format. This is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (two sentences), front-loading the action ('Rank anime') and including essential context. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and no output schema, the description covers key aspects: purpose, data source, and filterability. It could mention pagination or default sort order, but overall it is sufficiently complete for a ranking tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, so the schema already documents all parameters. The description only reiterates filter categories without adding new meaning, meeting the baseline for a well-documented schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Rank' and the resource 'anime', specifying it returns a filterable, sorted ranking. It distinguishes from siblings like anime_search (general search) and manga_rankings (manga-specific) by focusing on anime rankings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions it is 'credential-free public AniList data', indicating no authentication needed. It lists filter options (season, year, format, genre, status) but does not explicitly state when not to use this tool versus alternatives like anime_search.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It uses read-only language ('Retrieve', 'Returns') and specifies the data source (Apple Books catalog page), clearly indicating a non-destructive operation. It does not mention edge cases like empty results or pagination, but overall it communicates the core behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two concise sentences, front-loaded with the main action. Every word serves a purpose, with no fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with three well-documented parameters and no output schema, the description adequately states purpose and return concept. It could clarify that the result is a list, but 'related audiobooks' implies a collection. Overall, it is complete enough for this tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% coverage with clear descriptions for id, lang, and country. The description adds no parameter-specific details beyond the schema, so it meets the baseline but does not exceed it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves 'Customers Also Bought' audiobooks, with the verb 'Retrieve' and specific resource. It distinguishes from sibling tools like apple_books_audiobook_search (search) and apple_books_book_similar (books) by focusing on related audiobooks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the description and name: use this to get related audiobooks for a given audiobook. However, it does not explicitly mention when to avoid it or how it compares to related tools like apple_books_audiobook or apple_books_audiobook_series.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It states that data is pulled from Apple Books' public catalog page, suggesting a read-only operation with no special access. It also reveals what is returned (author metadata, full ebook/audiobook bibliography) and includes a caveat ('where available') about audiobook inclusion, which adds context beyond the tool name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the primary action ('Retrieve an Apple Books author's bibliography') before elaborating on return contents. Every word earns its place, with no redundancy or filler. This is a model of concise, structured tool description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, no output schema, and no annotations, the description adequately covers what the tool does and what it returns. It gives enough detail for an agent to select it for author bibliography needs. However, it could be more explicit about the exact structure or fields in the returned bibliography (e.g., titles, formats, metadata), but the high-level overview is sufficient for basic selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides full descriptions for all three parameters: id (Apple Books numeric author ID), lang (result language tag), and country (two-letter storefront country code). Since schema coverage is 100%, the description does not need to add parameter details, and it does not. The baseline of 3 is appropriate because the schema does the heavy lifting, but the description adds no extra semantic nuance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Retrieve an Apple Books author's bibliography.' It specifies the resource (author) and the action (retrieve bibliography), and further details that it returns author metadata and full ebook/audiobook bibliography. This distinguishes it from sibling tools like apple_books_book or apple_books_search, which focus on individual books or search results, not author-centric bibliographies.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you need an author's bibliography from Apple Books, but it provides no explicit guidance on when to use this tool over alternatives such as goodreads_author_books or apple_books_search. No exclusions or alternative tool references are given, so the usage context is implied rather than explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries the burden. It explains it returns chart rankings from public feeds, which is transparent. However, it does not disclose rate limits, caching, or data freshness. For a simple chart retrieval, this is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences with no fluff. Front-loaded with the core purpose. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple chart retrieval tool with no output schema, the description is complete: it specifies source, supported collections, and parameter context. Could optionally mention output format, but not necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter descriptions. The description adds value by listing supported collections explicitly, which goes beyond the schema's generic 'Chart collection' description. Other parameters are standard and well-described in schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves Apple Podcasts chart rankings from public iTunes RSS JSON feeds, and specifies supported collections (`toppodcasts`, `topaudiopodcasts`). This distinguishes it from sibling tools like searches or show-specific tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for chart rankings but does not explicitly guide when to use this tool versus other Apple Podcasts tools (e.g., search, show details). No exclusions or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds useful behavioral context by explaining the effect of ids_only=true and the platform enum values, which go beyond the schema. However, it omits details about pagination, default language/country, and the exact return format, and with no annotations provided, the description carries the full burden.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences: the first states the core purpose, the second and third highlight key parameter behaviors. Every sentence is informative, with no repetition of schema information, making it concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool, the description covers the essential functionality and key flags (ids_only, platform). It doesn't describe the return format or explain pagination semantics, but the schema handles parameter details, and the absence of an output schema makes some gaps acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes all seven parameters with clear explanations, including the platform enum and ids_only behavior. The description adds minimal new meaning beyond confirming the same details, so it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search the App Store' with a specific verb and resource, and clarifies that it returns search results for a term. This distinguishes it from sibling tools like appstore_app (get app details) or appstore_reviews (get reviews), though it doesn't explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear context for when to use this tool: when searching the App Store for apps matching a term. It doesn't explicitly mention alternatives or exclusion criteria, but the purpose is direct and unmistakable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses that the data is credential-free public data sourced from Autotrader's server-rendered page, implies a read-only operation, and notes the limitation that only the first page of inventory is returned. This adds meaningful context beyond just saying 'get profile'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, with two sentences that front-load the purpose, detail the return value, and then note the data source. Every sentence contributes meaningful information without redundancy or padding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with a single parameter and no output schema, the description is quite complete. It explains the return values (normalized profile, inventory summaries, total listing count) and the data source, and notes the first-page limitation. However, it does not mention what happens on failure (e.g., invalid id) or whether further pages can be retrieved, leaving minor gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% coverage for the single `id` parameter, describing it as the numeric path segment of a /car-dealers/{id} URL. The description does not add additional parameter semantics, so a baseline score of 3 is appropriate given the high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb ('Get') and resource ('Autotrader dealer profile'). It enumerates the exact return fields (name, phone, address, rating, website, inventory, total listing count), making it distinct from sibling tools like autotrader_search and autotrader_vehicle.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear context (fetch a dealer profile by id) and notes it is credential-free public data, but does not explicitly mention alternatives or when not to use this tool. Compared to siblings, there is no explicit guidance on choosing between autotrader_dealer, autotrader_search, or autotrader_vehicle, so the usage is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It adds valuable context by stating the data is credential-free and sourced from Autotrader's server-rendered page, and it discloses the return type (normalized summaries plus total count). This goes beyond a generic 'search' description, though it stops short of discussing rate limits, pagination, or error behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each earning its place: purpose, return value, and data source context. The description is front-loaded, efficient, and free of redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 15 optional parameters and no output schema, the description provides key orienting information: what is searched, what is returned, and that no credentials are needed. It lacks explicit guidance on parameter dependencies and pagination, but the schema covers those. Overall, it's complete enough for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents each parameter's meaning. The description's mention of return fields (make, model, trim, year, mileage, pricing, images) loosely aligns with parameters but does not add meaningful semantics beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Search Autotrader vehicle listings,' a specific verb+resource combination that clearly identifies the tool's purpose. It further details that it searches new and used car listings and returns normalized summaries with specific fields, distinguishing it from autotrader_dealer and autotrader_vehicle.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for searching Autotrader listings and mentions credential-free access, but it does not explicitly contrast with sibling tools like autotrader_vehicle or autotrader_dealer. There is no 'when to use vs. alternatives' guidance, though the context makes the primary use case clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the full behavioral burden. It does clarify that results are sourced from the homepage's category carousel, which gives a sense of scope and provenance. However, it does not disclose pagination, rate limits, output structure details, or whether the list is static or frequently updated. For a read-only list tool, the description is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, with no wasted words. It front-loads the main purpose and immediately adds the useful detail about how the id can be used in another tool. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and no output schema, the description covers the essentials: what it returns, the scope, and usability of the id. The context signal 'Has output schema: false' means the description doesn't need to explain return values, but it could have added a note on whether the id is stable over time. Otherwise, complete enough for the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema is empty. The description correctly adds no parameter details because none are needed. It explicitly states 'Get Best Buy's top-level shopping departments' and notes each id is directly usable as input, which is the most important semantic context for a no-parameter tool. This exceeds the baseline for a 0-parameter tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get Best Buy's top-level shopping departments.' It specifies the resource (Best Buy departments), the scope (top-level), and the data format (name, category id, url). It also differentiates from sibling tools like bestbuy_category and bestbuy_categories_trending by explicitly noting it returns top-level departments from the homepage category carousel.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by explaining that returned ids are directly usable as bestbuy_category's category_id input, which provides a chain of use. However, it does not explicitly state when to use this tool versus bestbuy_categories_trending or bestbuy_category_subcategories, or mention any exclusions. It gives some context but lacks explicit when/when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral disclosure. It explains results are normalized, fetched from public Bing HTML/async pages, and may return 503 on challenges. This is transparent, though it lacks details on authentication or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences cover purpose, behavior, and error condition efficiently. No unnecessary words; each sentence adds value. Well-structured and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers purpose, locale, source, and error behavior. For a simple image search tool with no output schema, it is fairly complete, though it could briefly note the return format (e.g., 'returns image metadata').
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All 5 parameters are described in the schema (100% coverage). The description adds minimal new meaning—mostly repeating defaults. Baseline 3 is appropriate as schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches Bing images and returns normalized results. The verb 'Search' and resource 'Bing image results' are specific. Sibling tools like bing_search and bing_videos are for other media, making this tool distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions locale defaults and error behavior (503), implying when the tool might fail, but does not explicitly state when to use it over alternatives like bing_search for general search or bing_videos. No direct exclusion or alternative tool names are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses that data is public and sourced from a credential-free AppView API, which signals read-only, no-auth access. It also explains the reply-tree behavior including parent chains. Missing are pagination, rate limits, and error handling, but the core safety profile is covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary action, and every phrase earns its place. No filler or redundant content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description provides a high-level return summary (post, nested replies, parent chain) and the depth behavior. It lacks default depth and error details, but for a simple two-parameter tool this is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both uri and depth already documented (at:// URI format and depth range 1-10). The description adds no new parameter semantics beyond echoing 'depth levels deep', so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a Bluesky post along with its reply tree, including parent chains when the post is a reply. This specific verb+resource phrasing distinguishes it from sibling Bluesky tools like bluesky_author_feed (feeds) and bluesky_profile (profile).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving a post and its nested replies, but it does not explicitly contrast with alternatives such as bluesky_author_feed or threads_post_replies. No exclusions or when-not-to-use scenarios are provided, so guidance is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the public nature, the AT Protocol source, and the AppView API, and enumerates returned fields. It does not mention rate limits or errors, but for a read-only public profile tool this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, then details. No fluff; every sentence provides value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema, the description covers purpose, return fields, data source, and authentication. Minor gaps include lack of explicit usage alternatives and any rate-limit or error behavior, but overall it is complete enough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema fully documents the 'actor' parameter with examples. The description adds no additional parameter detail beyond what the schema provides, which is acceptable given 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a Bluesky account's public profile, listing specific fields (display name, description, images, counts). This distinguishes it from sibling bluesky tools like feeds, followers, and follows.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for retrieving profile information and states it is public/credential-free, but does not explicitly provide when/when-not guidance or name alternatives. Usage context is clear but not elaborated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It states 'Public data, sourced from the AT Protocol's public, credential-free AppView API', which clarifies authentication requirements and data publicness. While it does not mention rate limits or side effects, for a read-only search tool this adds meaningful context beyond the bare minimum.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the action ('Search Bluesky accounts'), and includes only essential information: what it returns, search fields, and data source. No redundant phrasing or unnecessary details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool with three parameters and no output schema, the description is reasonably complete. It explains the search fields, confirms public access, and states the return type (accounts). Missing details like pagination behavior or response format are partially covered by the schema's cursor parameter, so the overall context is sufficient for an agent to select and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already describes all parameters (q, limit, cursor) adequately. The description does not add extra meaning to parameters beyond mentioning that the query searches against display name, handle, and profile description. It stays at the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Search Bluesky accounts' and specifies that it returns accounts matching a query against display name, handle, and profile description. This specific verb+resource combination distinguishes it from sibling tools like bluesky_profile or bluesky_followers, which have different scopes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: use when you need to find Bluesky accounts by text search. However, it does not explicitly mention alternatives or when-not-to-use, nor does it provide guidance on choosing this over other Bluesky-related tools. The usage is clear from context but not formally differentiated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses that results are 'normalized' and that category/subcategory filters use a 'discoverable category taxonomy' — useful behavioral hints. However, it does not mention pagination behavior, rate limits, or response shape in detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the primary action. Every clause adds meaningful information: source, normalization, destination/date scope, optional filters, and discoverable categories. No waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 7 parameters, no annotations, and no output schema, the description covers the core: search scope, filters, and category discovery. It doesn't explicitly state the return format (e.g., list of attraction objects), but 'search results' implies it. Slightly more detail on pagination could push it to 5.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema descriptions cover 100% of parameters, so baseline is 3. The description adds little beyond the schema; it repeats the filter concept but doesn't provide additional syntax or relationship details. It does reinforce the taxonomy idea but not enough to exceed baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Search Booking.com attractions' — a specific verb+resource pair. It further clarifies that it returns normalized results for a destination/date range with optional filters, distinguishing it from sibling tools like booking_attractions_detail and booking_attractions_reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context: searching for attractions/things-to-do in a destination within a date range. It does not explicitly name alternatives or exclusions, but the context is clear. No misdirection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It explicitly says 'Search' and 'Returns normalized... offers', which implies a non-mutating operation and describes the output shape at a high level. However, it does not detail any potential side effects, pagination, or what 'normalized' entails, leaving some behavioral aspects undisclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences that cover the core purpose and the primary return behavior with no unnecessary words. Every phrase adds value, making it an efficient example of front-loaded, minimal documentation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 11 parameters, no annotations, and no output schema, the description provides a solid high-level overview: what is searched (Booking.com flights), the trip types supported, and the nature of the output. It leaves out detailed explanation of the 'normalized' format or relationship between type and return date, but the schema covers the mandatory/conditional parameters, so the tool remains usable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds the context that the search is 'between two Booking.com flight-search locations', reinforcing the meaning of the 'from' and 'to' parameters. It does not add further parameter-specific details beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Search' with the resource 'Booking.com flights' and clearly states the output: normalized round-trip or one-way flight offers between two locations. This distinguishes it from sibling tools like expedia_flights_search or booking_hotel_detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context of when to use the tool (to search Booking.com flights) and indicates the tool returns offers between two locations. It does not explicitly compare against alternatives, but the focus on Booking.com flights and the return type makes the usage clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description alone must convey behavioral traits. It states the tool returns data from a public page (indicating a safe read operation) and specifies output as summary fields and daily rows. It does not mention potential errors, rate limits, or authorization needs, but is adequate for a simple retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with purpose and immediately followed by usage guidance. Every sentence is informative with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema, the description gives a reasonable idea of what the tool returns ('summary fields and domestic daily rows'). It is complete enough for its complexity, though more detail on output format would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (all three parameters have descriptions). The description adds the value 'Pass exactly one of `id`, `path`, or `url`', which clarifies the mutual exclusivity but does not explain when to choose one parameter over another. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns normalized Box Office Mojo release summary fields and domestic daily rows from a public release page. It uses a specific verb ('returns') and resource ('release'), distinguishing it from sibling tools like boxofficemojo_brand or boxofficemojo_weekend_domestic.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description instructs to 'Pass exactly one of `id`, `path`, or `url`', which is clear guidance on input constraints. However, it does not provide context on when to use this tool versus alternatives, such as when to prefer this over other Box Office Mojo tools like boxofficemojo_title.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that results are fetched from public Brave Search video HTML and may return 503 on challenges, providing valuable error context. It also mentions default locale settings, offering reasonable transparency for a search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first clearly states purpose, second adds defaults and error behavior. Every sentence adds value with no redundancy. Front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 8 parameters with full schema, no output schema, and no annotation, the description covers purpose, source, errors, and defaults. It lacks output structure details but is fairly complete for a search tool. Agent can infer return type from name.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are well-documented. The description adds default values and context about data source/errors but does not enhance individual parameter meaning beyond the schema. Per guidelines, baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches Brave video results and returns normalized results for a query string. The verb 'search' and resource 'Brave video results' are specific, and it distinguishes itself from siblings like brave_search, brave_images, and brave_news by focusing on videos.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly provide guidance on when to use this tool versus alternatives (e.g., google_videos, bing_videos). It implies use for video search from Brave but lacks exclusions or comparisons, leaving the agent to infer context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the data is credential-free and sourced from CarMax's mobile-app search API, which is valuable insider context. It also enumerates the return structure (make, model, trim, year, mileage, colors, engine, fuel economy, pricing, store, images, facets, total count), offering transparency about what the agent will receive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact overall but has redundancies: the first sentence 'Search CarMax vehicle listings' is nearly repeated by the second 'Searches CarMax for used car listings.' This wastes a sentence, though the rest is efficiently packed and front-loaded with the most important information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Since there is no output schema, the description appropriately enumerates the return fields and notes the presence of facets and total count. It also mentions the data source and credential-free nature. It could be slightly more complete by explicitly noting pagination behavior, but the schema already covers the 'page' parameter with 48-per-page detail.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% parameter descriptions, so the baseline is 3. The description does not add extra meaning about parameters beyond what the schema already documents; it focuses on output rather than input semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description immediately uses a specific verb and resource ('Search CarMax vehicle listings') and elaborates with concrete output details: normalized vehicle summaries, search facets with live counts, and total matching count. This distinguishes it from sibling tools like carmax_vehicle or carmax_search_suggestions, which focus on specific vehicles or suggestions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context: it searches used car listings and is credential-free, which tells the agent no authentication is required. However, it does not explicitly mention when to avoid this tool in favor of siblings like carmax_vehicle or autotrader_search, so it lacks direct exclusions or alternative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral burden. It discloses that the data is credential-free, public, and sourced from CarMax's server-rendered page, which adds meaningful context. It does not cover error behavior or rate limits, but for a simple read operation this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose, and every phrase adds value: return fields, credential-free status, and data source. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter lookup, the description is nearly complete: it lists return content, notes the public/credential-free nature, and cites source. It does not mention how to obtain the id (e.g., via search), but this is a minor gap given the schema's clarity and the simple scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents the 'id' parameter. The description adds no extra parameter semantics beyond the schema's mention of the numeric path segment. Baseline for high coverage is 3, and the description does not compensate with additional value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Get') and a specific resource ('CarMax store (physical location) detail'), clearly distinguishing this from sibling tools like carmax_search or carmax_vehicle. It also enumerates the exact return fields, leaving no ambiguity about what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies usage: provide a store id to get details for that store. However, it does not explicitly mention alternatives (e.g., use carmax_stores to list all stores) or state when not to use this tool. Since siblings like carmax_stores exist, explicit differentiation would strengthen this dimension.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool lists categories/collections but does not mention any behavioral traits such as rate limits, side effects, or read-only nature. However, since the tool has no parameters and is a simple list, the lack of additional details is acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences of appropriate length, front-loading the main action and specifying the return content. Every sentence adds value with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters, no output schema, and a simple purpose, the description is complete. It tells what the tool does and what it returns. A minor improvement would be to mention that it is a read-only operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no parameters, so baseline is 4. The description adds value by explaining the content of the returned list (category groups, subcategory slugs, etc.), which is not evident from the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists Chrome Web Store categories and collections, and specifies the returned data: category groups, subcategory slugs, top-chart identifiers, and curated collection slugs. This distinguishes it from sibling tools like chromewebstore_category and chromewebstore_collection, which focus on single items.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining reference taxonomy before using list endpoints, but it does not explicitly state when to use this tool versus alternatives, nor does it provide exclusion criteria. Sibling tools exist but no direct comparison is made.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that sections are omitted when not present, which is a key behavioral trait. It also mentions support for the vs_currency enum, but does not cover possible errors, rate limits, or permission requirements. However, for a read-only data retrieval tool, the disclosure is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise at three sentences. The first sentence states the purpose, the second clarifies output behavior (omission of sections), and the third notes enum support. No unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 parameters, no output schema), the description is fairly complete. It explains the output behavior (sections omitted when absent) and relevant parameter detail (vs_currency enum). However, it does not explain what sections typically contain, which could aid understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% coverage with descriptions for all three parameters. The description adds value by noting that the endpoint supports the documented vs_currency enum and provides an example value for id ('ethereum'). This enhances understanding beyond the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool returns normalized sections from a CoinGecko public chain detail page. The name and description together specify verb+resource (chain detail) and differentiate it from siblings like coingecko_chains (list) and coingecko_coin (coin detail).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention common use cases or exclusion criteria, which is a significant gap given the many coingecko sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the data is public and sourced from Costco's fulfillment backend, which implies no authentication required. However, it does not mention error handling, rate limits, or caveats about delivery estimates, so it only partially covers behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loaded with the core action ('Get a Costco product's delivery estimate') and then elaborating on the output. No unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 3-parameter tool with no output schema, the description is sufficient. It specifies the required inputs (product id, destination) and the output (stock and delivery status), which is enough for an agent to select and invoke it. It does not detail the return format, but this is acceptable given the tool's low complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes all three parameters (id, state, postal_code) with 100% coverage. The tool description only adds that state and postal_code define a 'delivery destination,' which reinforces but does not extend the schema. Baseline of 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get a Costco product's delivery estimate' and further explains it returns stock and estimated-delivery status for a destination. This is a specific verb+resource combination that distinguishes it from sibling tools such as costco_product, costco_search, and costco_product_reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: use this tool when you need stock and delivery estimate for a specific Costco product at a given US destination. It does not explicitly mention alternatives or exclusions, but the intended usage is unambiguous given the tool's name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses that only public products are returned, lists result fields, and identifies the data source as Costco's own search backend. However, it does not explicitly state side effects, authentication requirements, or result limits; the 'Search' verb implies read-only behavior but is not made explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core action ('Search Costco products') and immediately followed by useful detail. No filler or redundant content; every sentence contributes to the agent's understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool with no output schema, the description adequately covers return fields, data source, and search scope. It does not explain behavior when both parameters are omitted, but the schema marks them optional, and the core use case is clear. It is complete enough for typical usage without excessive detail.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters are fully documented in the schema with descriptions ('Search text' and 'Costco category slug...'). The description adds only that they can be combined ('and/or'), which is already implied by the optional, unrequired fields in the schema. No significant new meaning is added.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Search' and resource 'Costco products', clearly stating it returns public products matching a text query and/or category slug. It also lists return fields (title, brand, model, image, rating), distinguishing it from sibling tools like costco_product (single product details) and costco_categories (category listings).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: searching by text query and/or category slug. It does not explicitly name alternatives or exclusions, but the scope is well-defined enough for an agent to infer when this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that certain facets remain empty until enrichment coverage is high, which is a key behavioral trait. It also mentions suppressed counts, but does not explain suppression reasons or confirm read-only nature. Given no annotations, the description carries the burden and provides moderate context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is information-dense and front-loaded with the primary action. It efficiently conveys enums and exceptions without unnecessary repetition. Slightly long but earns its length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and high parameter count, the description explains what the tool returns (suppressed counts) and relates to search, but does not describe the output structure or suppression mechanics. Adequate but has gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (baseline 3). The description adds value by explaining facet enum meanings (e.g., 'admin1 (top subdivision)'), listing room_type values, and noting reliability thresholds for certain facets, going beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool facets the Airbnb markets dataset and returns suppressed distribution counts. It distinguishes from sibling tools like datasets_airbnb_search by mentioning it honors the same filters, and the dataset focus is explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for aggregated counts by listing facets and group_by enums, and links to search filters. However, it does not explicitly state when to use this tool over alternatives or provide when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It accurately describes a read operation ('Get', 'Returns') and adds value by mentioning the 'when hydrated' condition and listing returned data categories (lifetime grosses, year history, etc.). It does not contradict any annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose ('Get a Box Office Mojo title'), and includes necessary detail without padding. Every sentence earns its place, and the structure is easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter lookup tool with no output schema, the description is reasonably complete. It explains what is returned and the hydration caveat, and the schema covers the parameter. Some ambiguity remains about how to obtain the title_id, but sibling search tools likely provide it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% coverage of the single parameter 'title_id', including an example. The description adds minor context by explaining the id format ('IMDb tt… id used on Box Office Mojo title pages'), but this repeats schema information rather than adding new meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb ('Get') and resource ('Box Office Mojo title from the dataset'). It distinguishes from sibling tools by emphasizing it returns a single dataset record by title id, unlike search or facets tools. The included field list further clarifies its scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by providing the required parameter (title id) and notes the record includes specific fields when hydrated. However, it does not explicitly state when to use this tool versus alternatives like datasets_boxofficemojo_search or boxofficemojo_title, nor does it mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It indicates the operation is read-only (returns a snapshot) and specifies the id format. However, it lacks details on authentication, error handling, or data freshness. Basic behavioral info is present but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that conveys all essential information without unnecessary words. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema), the description adequately covers what it does and what it returns. It mentions the type of returned items (extension, theme, app snapshot) and the id format. Minor gap: no mention of error behavior or response structure, but overall sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameter id is described in the schema as 'Chrome Web Store item id'. The description adds the constraint that the id is 32 characters, which clarifies the format beyond the schema's generic description. This provides useful additional context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets a Chrome Web Store dataset item, and specifies it returns one stored extension, theme, or legacy app snapshot by its 32-character id. This differentiates it from sibling tools like search or changes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a specific 32-character id is known, but does not explicitly state when to use this tool versus alternatives (e.g., search or other datasets tools). No exclusions or prerequisites are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It discloses that the record is 'crawled' (implying a dataset snapshot rather than live data) and that exactly one record is returned by id. However, it does not mention error handling, data freshness, or response fields, leaving some behavioral aspects undisclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the action ('Get a Goodreads book'), followed by a precise detail about the record source. Every word earns its place; there is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter item lookup with no output schema, the description adequately explains the purpose, the input, and the return ('one crawled Goodreads book record'). It lacks specifics about the record structure or failure modes, but these are less critical for a straightforward retrieval from a dataset.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully describes the single `id` parameter with an example ('2767052'). The description adds that the retrieval is 'from dataset id enum value `goodreads-books`', clarifying the dataset context, but it does not enrich the parameter's meaning beyond what the schema provides. With 100% schema coverage, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Get a Goodreads book from dataset' and 'returns one crawled Goodreads book record by id', naming the specific dataset enum value `goodreads-books`. This distinguishes it from sibling tools like search or facets, which operate on collections rather than single items.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the use case: retrieve a single record when you have a Goodreads book id and want the crawled dataset copy. It does not explicitly mention alternatives like search tools, but the phrase 'by id from dataset' clearly signals when this tool is appropriate, providing clear context without exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It does state the return type ('one Instagram user record') and the dataset source, but it does not mention error behavior (e.g., what happens if the username does not exist), rate limits, or side effects. Since this is a simple getter, the missing edge-case behavior is a noticeable gap, but the core behavior is disclosed. A 3 reflects this balance.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loaded with the action ('Get an Instagram user'), and includes the essential dataset enum value. Every sentence earns its place; there is no redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema, no nested objects), the description covers the core behavior and dataset source. It could be more complete by mentioning error handling or the absence of an output schema, but for a straightforward lookup tool, the provided information is largely sufficient for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides a complete description of the single parameter `username` (including leading @ and max length), giving 100% schema coverage. The description mentions 'by username' but adds no additional semantic information beyond what the schema already says. Per the rubric, baseline is 3 when schema coverage is high, and no extra value is added.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'Get an Instagram user from the dataset' and specifies it returns one record by username from dataset id `instagram-users`. This distinguishes it from sibling tools like `datasets_instagram_users_search` (which searches) and `datasets_instagram_users_facets` (which provides facets). The verb 'Get' and resource 'Instagram user' are specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description conveys the primary use case: retrieving a single Instagram user by username. The phrase 'Returns one Instagram user record by username' implies this is for direct lookups, not exploratory search. However, it does not explicitly mention alternatives like using `datasets_instagram_users_search` when you need to filter or browse, nor does it state when not to use this tool. This is close to a 'clear context, no exclusions' case, so a 4 is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral transparency. It explicitly states the return behavior (returns one posting, 404 when absent), which is good. It does not cover authorization, rate limits, or side effects, but for a simple read-only item retrieval, these are less critical. The description is transparent enough for an agent to understand the expected outcomes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—three sentences that deliver essential information without any redundant words. Every sentence adds value: the action, the resource, the identifier, and the 404 behavior. There is no fluff, making it efficient for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-item retrieval tool with one parameter, the description covers the core functionality completely. It does not detail the return structure (no output schema exists), but the agent can infer that it returns a job posting object. Some additional context about what fields are included or the dataset schema could improve completeness, but it is adequate for the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers the sole parameter 'id' with a description 'Dataset posting id'. The tool description adds no further semantics about the parameter (e.g., format, source, or example). Since schema description coverage is 100%, the baseline is 3, and the description does not exceed this baseline. No additional value is provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('Get a single posting'), the resource ('from the jobs dataset'), and the key identifier ('by its dataset posting id'). It explicitly mentions the 404 response when absent, leaving no ambiguity about what the tool does and how it behaves. This strongly distinguishes it from sibling search/list tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly tells you to use this tool when you have a specific dataset posting ID, but it does not explicitly state when to use it versus alternatives like datasets_jobs_search or datasets_jobs_nearby. No 'when not to use' guidance or alternative tool names are provided, which is a gap for an agent choosing among many similar item retrieval tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the tool returns 'one crawled' record, implying a read-only fetch and indicating data origin, but it doesn't address error handling, rate limits, freshness, or the structure of the returned record.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, with the main action in the first sentence and clarifying details in the second. No unnecessary words or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-record lookup, the description adequately conveys the purpose, source dataset, and return type. However, the lack of an output schema means the description could do more to describe what a 'fund record' contains, but it is sufficient for an agent to decide to call it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully documents the 'id' parameter with an example. The description only restates that retrieval is 'by id' and adds no additional parameter meaning, so it meets the baseline for 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('PitchBook fund'), specifies it returns a single record by id, and names the exact dataset enum value. This distinguishes it from sibling search/facets tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The context is clear: use this tool when you have a specific PitchBook fund id and need the crawled record from the 'pitchbook-funds' dataset. It does not explicitly mention alternatives like datasets_pitchbook_funds_search or pitchbook_fund, so it lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses return data (maker, products, footprint) and error behavior (404 for missing username), but does not discuss rate limits, auth requirements, or data freshness. Adequate for a simple lookup tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three succinct sentences, front-loaded with the main action, and provides essential information without any fluff. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple lookup tool, the description covers input, output (maker, products, footprint), error handling (404), and the dataset id. Without an output schema, it provides enough context for the agent to understand the expected response. Minor gap: no mention of pagination or data limits, but not critical here.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one param (username) described. The description adds context about the dataset id and return structure, but does not significantly enhance parameter semantics beyond the schema's example and type.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get', resource 'Product Hunt maker from the dataset', and specifies the unique identifier (username). It distinguishes from sibling search/facets tools by focusing on a single item retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the tool retrieves a maker by username, including products and footprint, and returns 404 if not found. It implies usage when a specific username is known, but does not explicitly contrast with sibling search/facets tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full burden. It discloses the return type (terms-aggregation counts), the scoping to search filters, and details the revenue_band buckets. This adds value beyond the schema by explaining behavior and the revenue_band breakdown.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences that front-load the purpose and then provide essential details (facet enum and revenue_band buckets). No redundant information; every word is purposeful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main behavioral aspect (facet aggregation) and scoping to filters. It lists all facet options. However, it does not elaborate on how the filter parameters (q, sic, etc.) affect the results, though the schema covers them. Given the tool's simplicity and the absence of an output schema, this is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description lists the facet enum values (already in schema) and explains revenue_band buckets (not in schema). This adds marginal value but does not significantly enhance parameter understanding beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to return terms-aggregation counts for a single facet of the SEC companies dataset. It lists the facet enum values and explains the revenue_band buckets, making it distinct from sibling tools like search or item.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by context: the tool is for faceting, not full search. It mentions 'scoped to the same filters as search' but does not explicitly state when to use this vs. other tools like search or financials. No direct alternatives or when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the burden. It discloses the return type (aggregation counts) and scoping, but lacks details on limits, pagination, or potential performance implications. Adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, and no unnecessary words. Highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 7 parameters, no output schema, and a standard facets pattern, the description adequately explains the return type and enum. Missing details like max count or pagination, but overall sufficient for agent invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the bar is higher. The description adds value by explaining that filter parameters work the same as in search, providing context beyond individual parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it facets the TrustMRR dataset, returning terms-aggregation counts for one facet, and lists the enum of available facets. This is specific and distinguishes it from sibling tools like search, item, or history.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It implies use for faceted breakdown by mentioning 'scoped to the same filters as search', but does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly states that the search operates on the 'Android mobile guest catalog' (indicating a public, guest-facing data source) and that no account or token is required, which is valuable for the agent. It does not mention rate limits or pagination, but for a search tool this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded: the first sentence states the core purpose, followed by additional context about the catalog and auth requirements. Every sentence earns its place with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 parameters) and the absence of an output schema, the description covers the essential context: what is searched, where it searches, and the authentication requirement. It does not describe return values, but for a search tool this is usually implicit. The description is sufficiently complete for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no specific parameter semantics beyond what the schema already provides, apart from the general note that 'optional result filters' are supported, which is already evident from the schema's parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Search DoorDash pickup restaurants.' It specifies the resource (DoorDash pickup restaurants), the action (search), and additional context about the Android mobile guest catalog. However, it does not explicitly distinguish itself from sibling tools like doordash_explore or doordash_feed, which may offer overlapping search functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: when searching for pickup restaurants near a location, especially without authentication ('No DoorDash account or caller-supplied token is required'). It does not mention exclusions or alternative tools, but the phrasing implies this is the go-to for unauthenticated pickup restaurant searches.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It explicitly states that no DoorDash account or caller-supplied token is required and that it uses the Android mobile guest search experience, adding valuable context beyond the name. However, it does not describe the response format or potential rate limits, though these are less critical for a simple read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences that are front-loaded with the primary action. Each sentence contributes meaningful detail: the first defines the tool's purpose, and the second adds context about the return type and authentication-free nature. No redundant or wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple 3-parameter schema and no output schema, the description provides the essential purpose and context, including the no-auth requirement. It lacks an explicit description of the return value structure, but for an autocomplete tool, the level of detail is sufficient for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds only minimal context beyond the schema, such as 'near a location' linking to latitude/longitude. It does not provide additional syntax or format details for the parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb and resource: 'Get DoorDash pickup search suggestions.' It further specifies it returns pickup restaurant matches from the Android mobile guest search experience, distinguishing it from sibling tools like doordash_search or doordash_explore by focusing on autocomplete suggestions for pickup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for generating search suggestions but does not explicitly state when to use this tool over alternatives such as doordash_search or doordash_feed. No exclusions or alternative tools are mentioned, leaving usage guidance solely implied by the action described.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does add useful context: no DoorDash account or caller-supplied token is required, and it scopes the data to the 'Android mobile guest search experience.' However, it does not describe potential response format, pagination, or any other behavioral traits, leaving some uncertainty.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loaded with the core purpose ('Get DoorDash search filter options'), followed by concise details on output and authentication. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 well-documented parameters, no output schema, no annotations), the description covers the essential context: what it returns, for whom (guest search), and that no auth is needed. It could have mentioned typical use cases or relationship to search tools, but for this scope it is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% parameter coverage with clear descriptions ('Consumer latitude' and 'Consumer longitude'). The description adds minimal parameter-related meaning beyond confirming that the parameters define a 'location.' Baseline 3 is appropriate since the schema handles the semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and a specific resource ('DoorDash search filter options'). It further clarifies the output: cuisines and filter values for a location. This distinguishes it from sibling tools like doordash_search (which searches stores/items) and doordash_feed (which returns a feed).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: it returns filter options for a specific location, implying use when an agent needs cuisines or filter values to construct or refine a search. However, it does not explicitly mention alternatives or state when not to use it, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It does disclose that no authentication is required and identifies the data source as the Android mobile guest experience. However, it does not mention response format, pagination, rate limits, or explicitly state that the operation is read-only, leaving gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three short sentences, front-loaded with the main purpose. Each sentence adds distinct value: what it does, what it returns, and the auth requirement. There is no redundancy or unnecessary details, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the essential aspects for a simple read tool: it states what it returns (ratings and reviews), notes the auth-free access, and gives the source context. However, since there is no output schema, it would benefit from more detail on the response structure or potential limitations such as pagination. Still, it is sufficiently complete for basic usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage for all three parameters, so the baseline is 3. The description adds minimal parameter meaning, only hinting via 'for a location' that latitude and longitude correspond to the delivery area. This does not exceed the baseline, so a 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets DoorDash store reviews and specifies it returns store ratings and customer reviews. The verb 'Get' and resource 'DoorDash store reviews' are specific, and it distinguishes itself from sibling DoorDash tools like doordash_store_info and doordash_store_menu by focusing on reviews. The mention of 'Android mobile guest experience' adds clarity without ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for retrieving DoorDash store reviews for a location, which is clear context. It also provides a key prerequisite by stating no DoorDash account or caller-supplied token is required. However, it does not explicitly name alternative tools or state when not to use it, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full behavioral disclosure burden. It discloses important traits: result normalization, page-based pagination, the redirect-decoding behavior (always returns decoded destination URL, never raw redirect), and the data source (server-rendered search page). This is strong, though it stops short of mentioning potential rate limits or error behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long, front-loaded with the primary purpose, and each sentence adds substantive detail: output fields, pagination, redirect handling, and data source. There is no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of annotations and output schema, the description does well to specify return fields, pagination, and the key redirect behavior. It is sufficiently complete for a simple search tool, though it could be slightly more explicit about the output structure (e.g., a list of result objects) and any error conditions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all parameters are already documented. The description adds only minor context (query string, page-based pagination) that largely overlaps with the schema. It does not add meaningful semantics beyond what the input schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb+resource: 'Search DuckDuckGo web results.' It clearly states the return fields (title, destination URL, description, hostname) and pagination, which distinguishes it from sibling DuckDuckGo tools like duckduckgo_image, duckduckgo_news, duckduckgo_shopping, and duckduckgo_video.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for general web searches but does not explicitly state when to use this tool instead of alternatives (e.g., other DuckDuckGo media searches or other search engines like google_search). The scope is clear enough from the phrase 'web results,' but there is no explicit when/when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the return payload fields and that it accepts id or name, but does not describe error behavior (e.g., not found) or any side effects. Given it's a read-only profile fetch, this is acceptable but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two clear sentences, front-loaded with the main action, no redundant wording. Efficiently conveys purpose and input.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter GET operation with no output schema or annotations, the description adequately covers purpose, input, and key return fields. It lacks information on error states or when to prefer sibling search tools, but overall is sufficient for this simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the description's 'Accepts a numeric shop id or a shop name' simply restates the schema's description. No additional semantic value is added beyond the structured input schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description uses a specific verb+resource ('Get Etsy shop profile') and lists return fields (seller, headline, rating, sold count), clearly distinguishing from sibling tools like etsy_shop_listings or etsy_shop_reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Clearly implies this tool is for fetching a shop's profile when you have a numeric id or shop name. However, it does not explicitly mention alternatives or exclusions (e.g., use etsy_shop_search when only a query is available), so it falls short of full guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden of behavioral disclosure. It does mention 'Returns normalized... results' and the input criteria, which adds some transparency. However, it omits details like pagination, result limits, ordering, or any potential side effects. For a search tool, it gives basic but not comprehensive transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 17 words, front-loaded with the primary action and resource ('Search Expedia activities'). It avoids redundancy and every phrase contributes to understanding the tool's purpose and inputs.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a nested object parameter with no properties defined in the schema, no output schema, and no annotations. The description hints at the required search criteria but does not explain how to structure the 'option' payload or what the normalized results contain. This is a critical gap for correct invocation and interpretation, especially given the opaque schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% coverage with a single property 'option' described as 'Activity search payload', which is vague. The description adds meaning by specifying 'free-text destination and date range', helping the agent understand what the opaque nested payload should capture. It doesn't provide the exact structure inside the option object, but this extra context pushes it above the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Search' and the resource 'Expedia activities', and further specifies 'Expedia Things To Do (activities/tours)'. It also defines the scope with 'free-text destination and date range'. This distinguishes it from sibling tools like expedia_properties_search and expedia_flights_search, which target different Expedia offerings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: searching for activities/tours by destination and date. However, it does not explicitly name alternatives or state when not to use it. The context is unambiguous enough for an agent to select this over property or flight searches, but explicit exclusions are absent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It discloses that the tool uses a 'real browser-rendering backend' and sources public data from server-rendered Fiverr pages, which hints at potential latency and scraping behavior. It also states the data is 'normalized,' adding context about output transformation. This goes beyond a simple description but could still mention error cases or rate limits, so it is not a 5.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and efficient: two sentences. The first sentence gives the core purpose, and the second lists the return fields and data source. Every sentence earns its place, with no irrelevant fluff or repetition of the tool name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema, no annotations), the description is fairly complete. It lists return fields, which is valuable because there is no output schema, and explains the data sourcing method. It could mention failure modes (e.g., invalid username, seller not found) or explicitly state that it returns a single object, but overall the description provides sufficient context for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already covers the sole parameter 'username' with a clear description and example (from a search result's seller_username field). Since schema description coverage is 100%, the description adds little beyond the schema. It confirms that the tool fetches a seller profile but does not elaborate on parameter syntax or edge cases. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb and resource: 'Get Fiverr seller profile.' It enumerates the exact fields returned (display name, country, seller level, etc.), which distinguishes it from sibling tools like fiverr_search or fiverr_gig. The purpose is unambiguous and immediately understandable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a Fiverr seller profile is needed, but it does not explicitly state when to use this tool versus alternatives like fiverr_gig or fiverr_search. The parameter description 'e.g. from a search result's seller_username field' provides some context on where the input comes from, but there are no explicit exclusions or comparisons to sibling tools. Usage is implied rather than clearly scoped.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It mentions public events and normalization but lacks details on pagination limits, rate limits, or output structure beyond high-level fields.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences delivering the essential purpose and output description. No redundant information, well front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but the description gives a clear high-level view of return values (page of events normalized to type, repo, timestamp). Adequate for a simple list tool, though more detail on pagination could help.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters are documented in the schema (100% coverage). The description adds value by explaining the output is normalized to type, repository, and timestamp, aiding in tool selection.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists a GitHub user's recent public activity, with a specific verb and resource. It distinguishes from sibling tools like github_user or github_user_repos by focusing on events.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like github_user_repos or github_trending. Usage is implied but not clarified with exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly states the tool returns a normalized profile with specific fields and that data is credential-free. However, it does not disclose potential error states (e.g., invalid author ID), rate limits, or any side effects. The description adds meaningful context beyond the input schema (which only describes the parameter).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long with no wasted words. The first sentence states the action, the second enumerates return fields. Every word earns its place, making it easily parseable for an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (single parameter, no output schema). The description covers the core purpose and return data comprehensively for a lookup tool. It could optionally mention the return format or error handling, but given the low complexity, it is largely complete. Sibling tools exist but are not discussed, which slightly reduces completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (the single parameter 'id' has a description 'Goodreads author id'). The description implicitly identifies the parameter as the author identifier but adds no new semantics about its format, source, or validation rules. Baseline 3 is appropriate since the schema already documents the parameter adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a Goodreads author and lists the specific profile fields returned (bio, birth/death dates, etc.). The verb 'Get' is specific, and the resource is unambiguous. It distinguishes from sibling tools like goodreads_author_books (which returns books by an author) by focusing on author profile data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when you need an author's profile details, but it does not explicitly state when to avoid this tool versus alternatives (e.g., goodreads_search for finding authors by name, or goodreads_author_books for book listings). No when-not-to-use guidance is provided, and the context of credential-free access is useful but not sufficient for comparative decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses pagination and credential-free access, but does not mention error handling, empty results, rate limits, or sorting behavior. Adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two concise sentences. The first sentence states the purpose, and the second details return fields and access. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with 2 parameters and no output schema, the description covers the essentials: what it does, what it returns, and pagination. It could mention default ordering or page size limits, but is mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents both parameters. The description adds 'paginated works list' which reinforces the page parameter's role, but does not add new semantic information beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and the resource 'a Goodreads author's books', specifying what is returned (paginated works list with fields). It distinguishes itself from sibling tools like goodreads_author (author info) and goodreads_book (single book).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions 'Credential-free public Goodreads data', indicating no authentication needed. It implies usage when you have a Goodreads author ID and want their books, but does not explicitly state when not to use or name alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It discloses pagination, the exact return fields (quote text, tags, like count, and conditional book title/id/work id), and the credential-free nature of the data. This goes beyond the minimum but stops short of discussing error behavior or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences with no waste. It front-loads the core action, then provides return-field details, and ends with the credential-free note. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema and no annotations, the description covers the essential points: what is listed, the pagination behavior, the structure of returned items, and the fact that no credentials are needed. This is nearly complete for a simple list-oriented tool, though it could mention how to get the author id.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the `id` and `page` parameters are already well documented in the input schema. The description reinforces pagination and the author context but does not add substantial new meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'List a Goodreads author's attributed quotes', a specific verb+resource+scope that clearly distinguishes it from siblings like goodreads_author_books and goodreads_author. The additional detail about paginated return fields reinforces its unique purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies its use case ('List a Goodreads author's attributed quotes') and notes 'Credential-free public Goodreads data', but it does not explicitly state when to use this vs. alternatives like goodreads_author_books or how to obtain the required author id. No exclusions or alternative tools are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that the tool is credential-free, uses public data, and returns only book results. However, it does not mention rate limits, pagination behavior, or whether edits are possible (implied read-only). Some behavioral aspects are uncovered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise sentences. First sentence states the core purpose, second elaborates on search criteria, third adds technical detail about the endpoint and data source. No redundant or wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 2 parameters fully covered by schema and no output schema, the description explains the data source (autocomplete endpoint) and scope (books only). For a simple search tool, this is reasonably complete, though more detail on return format would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents both parameters. The description adds context that search is by title/author, but this is aligned with the schema's query description. No additional value added for the limit parameter. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches Goodreads books by title/author, and specifies it uses the autocomplete endpoint. It distinguishes from sibling tools like goodreads_author, goodreads_book, etc., which have specific focuses on details rather than search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates the tool is for searching books by title/author and returns only book results. It implicitly tells when to use (when needing a book search) but does not explicitly exclude cases like searching for authors or non-book content. Given sibling context, it's reasonably clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries the full burden of behavioral disclosure. It names exactly what the tool returns (official title, tree position, related symbols, scope-note), clarifies that it accepts symbols at any level, and states that the data is public and sourced from Google Patents' search API. The description lacks specific error-handling or response-format details, but for a read-only lookup tool the key behavior is well covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, well-structured, and front-loaded with the core purpose. Every sentence contributes: purpose, return content, accepted input forms, and data source. No repetitive or wasteful phrasing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter, read-only lookup tool without an output schema, the description covers the critical context: what the tool does, what inputs are valid, and what output fields to expect. It is sufficiently complete for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents the single 'code' parameter, but the description adds substantial meaning by explaining the accepted forms and giving explicit examples ('A', 'A61', 'A61K', 'A61K31/00'). This goes beyond 'CPC classification symbol' and helps the agent construct a valid input.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the tool's function: look up a Cooperative Patent Classification (CPC) symbol and return its title, tree position, related symbols, and scope-note. It is not a tautology and clearly identifies the resource, but it does not explicitly contrast this with sibling tools like googlepatents_search or googlepatents_detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context: use this tool when you need classification metadata for a CPC symbol at any hierarchical level. It provides useful input guidance (e.g., 'A', 'A61', 'A61K31/00'), but does not explicitly state when to prefer this tool over a Google Patents alternative or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the behavioral disclosure burden. It discloses the data source ('Google Patents' own sitemap'), public data nature, one-week scope, and return payload fields (publication number, title, detail-page URL). However, it omits behavior such as result count, ordering, pagination, empty-week handling, and latency — acceptable for a simple browse tool, but not fully transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three short, information-dense sentences with the core function front-loaded, followed by the return payload and a quick usage context. No filler or tautological repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter browse tool returning a simple list, the description covers what the tool does, what the parameter means, where the data comes from, and what the response contains. It lacks details like ordering or limits, but these are minor for a simple browse/resource tool with no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the schema already defines 'week' as 'ISO 8601 week, format YYYY-Www.' The description restates this format, adds a concrete example ('2026-W20'), and clarifies that the week maps to a sitemap index. This adds marginal value, but the schema already carries the essential meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description states a specific verb and resource: 'Browse patent publications indexed by Google Patents for one ISO week.' It also implicitly distinguishes itself from sibling search tools by noting it is for browsing 'without a search query,' which isolates it from googlepatents_search and similar query-based tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a clear use case: 'useful for browsing recently published patents without a search query.' This tells an agent when to prefer this tool, and the reference to lacking a search query implies the alternative is a search-based tool, though it does not explicitly name sibling tools or describe when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description mentions it returns 'normalized public' data and 'known-for rows' but omits error handling, authentication, or rate limits. Adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff, front-loaded with purpose. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Two parameters, no output schema; description covers input constraint and output content. Lacks return format details, but sufficient for a simple retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with basic descriptions; description adds the critical constraint 'Pass exactly one of id or url', which is not in schema, providing significant added value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
States it returns 'IMDb person metadata and known-for rows', which is specific and distinct from sibling tools like imdb_name_awards or imdb_name_credits.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Specifies 'Pass exactly one of id or url', which clarifies parameter usage but does not compare to alternatives or state when to use this tool versus other imdb_name_* tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the output is 'normalized public' trivia rows, indicating read-only and source quality. However, it lacks details about potential side effects, rate limits, or authentication requirements. The behavior is adequately, but not richly, described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exceptionally concise, using two sentences to convey purpose, output nature, and parameter rule. The key information is front-loaded with the tool name and immediate clarification.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and simple parameters, the description covers essential aspects: what the tool returns, input requirements, and data type. It does not address pagination or limits, but for a straightforward retrieval tool, it is largely sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage describing 'id' and 'url'. The description adds the critical rule that exactly one must be used, which is not enforced by the schema (required: []). This helps the agent avoid invalid calls.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'normalized public IMDb trivia rows for a title,' specifying both the action (returns) and resource (title trivia). It distinguishes from sibling tools like imdb_title_goofs or imdb_title_quotes by explicitly naming 'trivia.'
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a usage constraint ('Pass exactly one of `id` or `url`') but does not compare this tool to alternatives or specify when to use it over other IMDb title sub-tools. The context of sibling tools suggests many similar functions, but no explicit guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that data is 'credential-free public data' and explains the rendering mechanism ('through proxied browser renderers'), adding important context about access requirements and data source. It does not cover potential limitations like rate limits or freshness, but it does provide meaningful transparency beyond a simple 'get report' statement.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long, with no fluff. It front-loads the action ('Get an ImportYeti company report'), uses the second sentence to list key data components, and the third to clarify the data source and access. Every sentence serves a distinct purpose, making it appropriately sized and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity and lack of an output schema, the description provides a solid overview of what is returned: identity, shipment-volume metrics, supplier list, and recent bill-of-lading activity. It also notes the data is 'normalized' and public. It is reasonably complete for a read-only report tool, though it stops short of detailing exact output structures or potential edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully describes the single parameter 'slug' (100% coverage), including its meaning as the last path segment of a /company/{slug} URL. The description adds no additional parameter-level detail beyond what the schema provides, establishing a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a specific verb and resource: 'Get an ImportYeti company report.' It then enumerates the report's contents (identity, shipment metrics, supplier list, bill-of-lading activity), distinguishing it from sibling tools like importyeti_search by its focus on a single company's full report.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies usage (when you need a company report for a given slug) but does not provide explicit guidance on when to choose this tool over alternatives such as importyeti_search, nor does it mention any exclusions or prerequisites. The usage context is implied, not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Discloses return format and auth-free nature, but lacks details on error behavior, rate limits, or what happens if job not found.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three front-loaded sentences with no wasted words. Every sentence provides distinct information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers return fields and auth status. Lacks error handling or limitations, but overall adequate for a simple read-only tool with no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and description does not add meaning beyond schema descriptions for 'id' and 'token'. Baseline score of 3 appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Get a single Greenhouse job' and specifies return fields (HTML/text description, department, offices). It distinguishes from sibling tools like jobs_greenhouse_board, which likely lists multiple jobs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Mentions 'Credential-free public ATS JSON,' implying no authentication needed. Provides context but no explicit when-to-use vs. alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Clearly states 'Credential-free public ATS JSON', indicating no authentication needed. Also notes that structured compensation is returned only 'when the board exposes it', setting expectations about data availability. Does not cover rate limits or error handling, but the key behavioral traits are disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, highly concise. The first sentence is the action verb + resource, front-loaded. No redundant information. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description mentions return of 'full HTML/text description and structured compensation'. Provides context about data freshness ('when the board exposes it') and authentication. Lacks details on possible errors or missing data, but for a simple fetch tool, it is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% description coverage for both parameters (id and company). The description adds no additional parameter semantics beyond the schema's built-in descriptions. Baseline score of 3 is appropriate with high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Get a single Recruitee offer', specifying the verb and resource. It distinguishes from the sibling 'jobs_recruitee_offers' (plural) by indicating a single offer. Mentions return details (description, compensation).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage context is implied (fetch a specific offer by id and company subdomain), but there is no explicit guidance on when to use this tool versus alternatives like 'jobs_recruitee_offers' or other job board tools. No when-not-to-use or alternative suggestions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior. It accurately states the tool is read-only ('Credential-free public ATS JSON') and describes the output fields. However, it does not address error handling (e.g., job not found) or rate limits, but for a simple retrieval operation, this is largely sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise with three sentences: first states the action, second lists return fields, third clarifies the ID and authentication. No redundant information, well-organized for quick parsing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-item retrieval tool with well-described parameters, the description provides sufficient context about input and output. It lacks details on error responses or edge cases, but these are less critical for agents given the straightforward nature of the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides clear descriptions for both parameters ('Rippling job uuid' and 'Rippling board slug'). The description adds slight value by clarifying that 'id' comes from a listing, but this does not significantly extend meaning beyond the schema. Baseline 3 is appropriate given 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the action ('Get a single Rippling job'), the resource (a specific job), and what it returns (full HTML/text description, employment type, work locations). It also explains the 'id' parameter's origin, making it distinct from sibling tools like 'jobs_rippling_board'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
While the description implies usage for retrieving a single job by ID from a listing, it does not explicitly state when to use this tool versus alternatives (e.g., 'jobs_rippling_board' for listing jobs). No exclusion criteria or context for selection is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description confirms it returns data (read operation) but does not disclose any behavioral traits like rate limits, auth, or side effects. Minimal but not misleading.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences that are clear and front-loaded. Every word adds value with no unnecessary details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 5 parameters, 1 required, and no output schema, the description covers the core functionality. It lacks details on pagination or result format, but for a simple query tool, it is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (all 5 parameters described). Description adds a concrete example for the 'genre' parameter and clarifies the 'type' parameter's valid values, which enhances understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: getting popular titles for a JustWatch genre short name. It provides an example ('act') and distinguishes from sibling tools like justwatch_genres.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus other JustWatch tools (e.g., justwatch_popular or justwatch_discover). Usage is implied but not contrasted with alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions 'credential-free public Letterboxd data' and the data source, which is valuable behavioral context given no annotations. It could mention error behavior or rate limits, but overall it provides good transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the action and returned fields, followed by source context. Every sentence earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description lists key returned fields, which is helpful. It omits details about field structures or error handling, but is sufficiently complete for a simple data retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with the parameter description 'Letterboxd film slug'. The tool description does not add extra meaning or examples beyond what the schema already provides, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a Letterboxd film and lists specific fields like synopsis, director, cast, etc. It distinguishes itself from sibling tools like letterboxd_search or letterboxd_film_reviews by focusing on a single film via slug.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you have a film slug, but does not explicitly guide when to use this tool versus alternatives like search or review tools. No 'when-not-to-use' or contrast with siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It notes that the data is 'credential-free public Letterboxd data,' indicating no authentication. However, it does not disclose rate limits, error handling, pagination behavior, or what happens with invalid slugs. Adds moderate value beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two efficient sentences: first sentence clearly states purpose and return fields, second adds credential-free context. No fluff, front-loaded with key information. Excellent conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so description should explain return values, which it does (listing fields). It mentions 'popular reviews' implying sorting, but doesn't explicitly state ordering or pagination mechanism. For a tool with moderate complexity (2 params, no nested objects), this is fairly complete but could be slightly more explicit.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with both 'slug' and 'limit' described in the schema. The description adds no new meaning beyond what the schema already provides (e.g., 'Letterboxd film slug' is repeated). Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets a Letterboxd film's popular reviews, specifying the returned fields (reviewer, rating, date, text, like/comment counts, spoiler flag). It distinguishes from sibling tools like letterboxd_film (film details) and letterboxd_film_rating_histogram (rating distribution) by focusing on reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (for popular reviews) but does not explicitly exclude alternatives or state when not to use. However, the sibling tools are distinct enough that an agent can infer the appropriate context. No explicit 'use this for reviews, other tools for other data' guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It states credential-free, public data, and lists return fields. It implies read-only behavior via 'search' and description of returned data, but doesn't explicitly disclose pagination or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, mostly informative. The first sentence ('Search manga.') is redundant with the name, but the rest efficiently conveys purpose, data source, and return fields.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lists return fields and data source, which is good for a search tool with no output schema. However, it does not explain pagination (page, per_page), error cases, or result ordering (beyond schema). Schema descriptions fill some gaps, but the description could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions. The description only elaborates on the 'query' parameter (free-text). It adds no additional meaning beyond what the schema provides, thus baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches manga by free-text query, specifies the data source (AniList), and lists return fields. It distinguishes from siblings like anime_search (anime) and manga_rankings (different operation).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates use case: searching manga by query. It mentions 'credential-free public data' which sets expectations. However, it lacks explicit when-to-use or when-not-to-use guidance compared to sibling tools like manga_title or manga_rankings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It mentions pagination and that it's a read operation on public data. However, it does not disclose rate limits, destructive actions (none), or other behavioral traits beyond what the schema already implies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences (30 words), front-loaded with the verb 'List', and every sentence adds value. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 4 parameters and no output schema, the description adequately covers input requirements and return fields. However, it lacks details on sorting options and the exact output structure, which would be beneficial given no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds no extra parameter meaning beyond what the schema provides. It does not explain sort options or other parameter nuances, but the baseline expectation is met.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists user reviews for a Metacritic movie, specifies the returned fields (author, score, quote, date, helpfulness, spoiler flag), and distinguishes from sibling tools like metacritic_movie_critic_reviews and metacritic_game_user_reviews by the resource type and review category.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates credential-free public data, implying no authentication needed. It does not explicitly state when to use this tool vs siblings, but the name and context clearly differentiate it from critic reviews and game reviews, providing implicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries burden. Lists return fields (author, score, quote, date, helpfulness, spoiler flag) and mentions pagination. Does not disclose rate limits, data freshness, or error handling, but covers essential behaviors.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with purpose. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Lists all returned fields, notes pagination, and public data access. Missing explanation of sort parameter or how to obtain slug, but overall sufficient for a list tool without output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all parameters with descriptions (100% coverage). Description adds minimal semantics beyond declaring pagination and listing return fields. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'List a Metacritic TV show's user reviews', specifying verb and resource. Differentiates from sibling tools like metacritic_tv (show details) and metacritic_tv_critic_reviews (critic reviews).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Mentions 'Credential-free public Metacritic data' indicating no auth needed. Does not explicitly exclude alternatives, but the context and name make it clear this is for user reviews only.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the parsing source (server-rendered job detail page) which adds useful context, but does not mention error behavior, rate limits, or what fields are returned. It is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with the core purpose. Every clause adds value—scope, id source, and parsing origin—with no redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter detail lookup with no output schema or annotations, the description covers the essential inputs (id provenance), purpose, and data source. It does not explain return values, but for such a simple tool the description is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a minimal description 'Meta job id'. The tool description adds that it is a numeric id that comes from search or list, providing provenance beyond the schema. This is a modest addition, so a 3 (baseline for high schema coverage) is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns a single Meta Careers posting by numeric job id, using the verb 'Returns' with a specific resource. It distinguishes itself from siblings like meta_jobs_search and meta_jobs_list by explicitly saying 'single posting' and referencing the id from search or list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context on when to use the tool: after obtaining an id from search or list. It implicitly points to sibling tools for finding ids, but does not explicitly state exclusions or alternative scenarios, so it falls short of a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations at all, the description carries the full burden, and it does a solid job: it discloses the return fields (name, address, phone, coordinates, distance, store page URL) and the well-formed empty result for no-match locations. It stops short of covering areas like pagination limits or error conditions, but for a simple store-finder read it gives meaningful behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, zero filler: the first establishes the action, the second specifies the source and return shape, and the third covers the empty-result edge case. The information is front-loaded and every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, so the description's explicit list of returned store fields fills that need well. Combined with the empty-result behavior and the schema's defaulted parameters (page, radius_miles), an agent has enough to call the tool and interpret the response correctly; the only minor gaps are pagination semantics and error-handling detail.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so lat, lng, page, and radius_miles are all described within the input schema itself. The description reinforces the 'coordinates and radius' concept but adds no new syntax, unit clarification, or edge-case detail beyond what the schema already provides, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
"Find nearby Nike stores" states a concrete verb and resource, and the next sentence pins it to Nike's physical retail store locator. This clearly differentiates it from nike_product, nike_categories, and nike_search, which deal with the online catalog rather than brick-and-mortar locations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the intended use case—geographic proximity lookup by coordinates and radius—but it never explicitly names sibling alternatives or states when not to use it. An agent can infer the right moment from the wording, but the guidance is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It notes that this is credential-free public data from numbeo.com, indicating no authentication needed. It also specifies the return structure (aggregate + city breakdown), adding behavioral context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loading the purpose and adding essential details about output and data source. No redundant or vague language.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with two simple parameters and no output schema, the description covers purpose and basic behavior. It could be improved by referencing how to discover valid index families, but it is sufficient for this level of complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for 'country' and 'index'. The tool description does not add further meaning, such as listing valid index families or specifying the format for country names. It provides baseline clarity but no enrichment.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a Numbeo country's data for an index family, including aggregate data and city breakdowns. It distinguishes from siblings like numbeo_indices_city and numbeo_indices_rankings by focusing on country-level data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies data retrieval but does not explicitly state when to use this tool vs alternatives like numbeo_indices_city or numbeo_indices_rankings. No exclusions or conditions are provided, leaving the agent to infer context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations to lean on, the description discloses a crucial behavioral trait: this is a best-effort search that falls back to recommended results for obscure or nonsense keywords, with no reliable signal to tell a true keyword match from fallback. It also states the return shape (pricing, review scores, purchasable color variants). It does not mention pagination quirks or read-only side effects, but search tools are reasonably assumed non-mutating.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The core purpose and brand mapping are front-loaded into the first two sentences. The second half about fallback behavior is a dense caveat, but every sentence carries necessary operational information. There is no filler, though the prose is slightly long.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a three-parameter tool with no output schema, the description covers the essential return content and the critical fallback caveat. The omission of page-size or response-field details is a minor gap given the context signals, but the description tells an agent enough to invoke the tool correctly and interpret its output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already has 100% parameter descriptions, so the baseline is 3. The description adds the exact enum-like values for brand (`on`, `gap`, `br`, `at`), the default (`on`), and clarifies keyword interpretation by exposing the fallback behavior for obscure or nonsense terms. This goes well beyond the schema descriptors.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Search') and a definite resource ('Old Navy, Gap, Banana Republic, or Athleta products'), and further defines the resource as 'product listings' with a 'normalized product summaries' return. It distinguishes from product-detail/category sibling tools only implicitly, so it stops short of the strongest sibling-differentiating statement.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It tells the agent how to select the storefront via the `brand` parameter, including exact values and the default (`on`). It also warns about fallback behavior for obscure keywords. However, it never explicitly says when NOT to use this tool or points to alternatives such as oldnavy_product, oldnavy_category, or oldnavy_categories.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavior. It mentions that it returns author, text, and per-category ratings, and notes it is credential-free. However, it lacks details on pagination behavior (beyond schema parameters), ordering, rate limits, or potential errors, making it only moderately transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary action, and every sentence adds value. It is appropriately concise with no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the essential details for a simple paginated review tool: the resource, the output fields, and the credential requirement. While it lacks an output schema, the description compensates by listing return fields. Minor omissions like ordering or error behavior prevent a perfect score but do not significantly hinder use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes all three parameters (page, size, restaurant_id) with 100% coverage, so the baseline is 3. The description does not add additional semantics beyond what the schema provides, though it implicitly relates 'page' to the page-based retrieval mentioned in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Get a page of an OpenTable restaurant's diner reviews.' It uses a specific verb ('Get') and resource ('OpenTable restaurant's diner reviews'), and mentions page-based retrieval. This distinguishes it from sibling tools like opentable_restaurant and opentable_restaurant_menus.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context by specifying the source (OpenTable restaurants) and that it is 'Credential-free,' which informs usage prerequisites. However, it does not explicitly mention when to use this tool over alternatives (e.g., other review tools) or any exclusions, so it falls short of fully explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It reveals that the API is credential-free, returns normalized rows, and explicitly lists enum values for window and sort_by. However, it does not mention rate limits or pagination behavior, but for a simple read-only tool this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences with no wasted words: first states purpose, second adds source/processing context, third lists parameter specifics. Highly efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool with 3 basic parameters and no output schema, the description covers purpose, source, processing (normalized), and parameter values. It does not describe the exact return fields, but 'normalized trader leaderboard rows' is reasonably informative.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema descriptions are minimal ('Leaderboard sort', 'Leaderboard time window'), but the description adds concrete enum values ('1d', '7d', '30d', 'all' for window; 'profit', 'volume' for sort_by), which is valuable beyond schema. It also clarifies limit defaults and max.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List Polymarket leaderboard rows' and specifies the source (credential-free Data API). Among sibling tools like polymarket_markets, polymarket_events, etc., this is uniquely for the leaderboard, setting clear differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention conditions, exclusions, or comparisons to other Polymarket tools, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries the full burden. It explicitly states that no authentication (user token, wallet signature, cookies) is required, clearly indicating a credential-free public endpoint. This goes beyond what annotations would typically provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: the first states the core action, the second adds key behavioral context. No superfluous words; front-loaded with the essential purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description adequately covers purpose and authentication requirements. It could mention the return format (normalized market JSON) but remains largely complete given the low complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With schema coverage at 100% (the schema describes 'id' as 'Polymarket market id'), the description adds no additional meaning or context about the parameter. It meets the baseline but does not enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and the resource ('Polymarket market detail by id'), effectively differentiating it from sibling tools like polymarket_events (list events) or polymarket_markets (list markets). No ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when credential-free access is needed, but does not explicitly explain when to use this tool over alternatives such as polymarket_clob_market or polymarket_market_liquidity. No direct guidance for selection among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description indicates a read-only operation ('list') and specifies return format ('normalized tag rows'). No annotations are provided, so the description carries the burden. It is clear but could mention potential empty result behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no filler. Efficiently conveys action, resource, and return type. Every sentence is necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description covers the core purpose and return type. It is complete enough for an agent to select and invoke correctly, though more detail on the return structure would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with a description for the 'id' parameter. The description adds no new information beyond what the schema already provides ('Polymarket market id'). Minimal added value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states action ('List tags'), resource ('Polymarket market'), and return type ('normalized tag rows attached to one Polymarket market id'). It distinguishes from sibling tools like polymarket_tags (which likely lists all tags) or polymarket_event_tags.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives, but the tool name and description imply usage when you have a specific market id and need its tags. Sibling names provide contextual differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the tool uses credential-free public CLOB market data, returns buy and sell prices, and supports an optional side parameter. While it omits details like rate limits or error handling, the disclosed traits are sufficient for basic understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with two sentences. The first states the core purpose, and the second adds critical details about the side parameter and authentication. No extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complex nested input schema and lack of output schema, the description is insufficient. It fails to detail the body's structure (e.g., how to pass token IDs) and does not describe the response format, leaving agents guessing about how to invoke the tool and interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has a nested 'body' parameter with minimal description. The description adds meaning by explaining the side enum and batch limit. However, it does not specify the exact JSON structure for the body (e.g., whether it expects an array of IDs), leaving ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Polymarket token prices, specifying it returns public CLOB buy and sell prices for up to 25 token IDs. It distinguishes itself from sibling tools like polymarket_token_price (single token) and polymarket_tokens_midpoints by mentioning the batch capability and the side enum.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use this tool, emphasizing it requires no authentication and can handle up to 25 token IDs. However, it does not explicitly contrast with alternatives like polymarket_token_price for single token queries, which would strengthen guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It does disclose that the tool returns 'flat public comment entries' (data shape) and includes a valuable operational detail about 503 throttling with Retry-After handling. However, it omits other behaviors such as pagination mechanics, result field specifics, or authentication requirements, so it is only partially transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose and followed by a crucial error-handling note. There is no redundant language or filler; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the tool's purpose, scope (latest-comments feed), and a key error scenario. The schema documents pagination parameters, so not repeating them is fine. Since there is no output schema, a brief mention of what a 'comment entry' includes would improve completeness, but the existing content is comparatively strong for a simple list tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema descriptions cover 100% of parameters (subreddit, after, limit) with clear meanings. The tool description adds no parameter-specific information beyond what the schema already provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb+resource construction: 'List Reddit subreddit comments' and further distinguishes the tool by specifying 'from a subreddit latest-comments feed.' This effectively separates it from sibling tools like reddit_subreddit_posts or reddit_user_comments. It is not a tautology and clearly communicates the tool's scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context that this tool retrieves a subreddit's latest comments feed, which is enough to infer when to use it (when you need recent public comments from a subreddit). It does not explicitly name alternatives or exclusions, but the context is unambiguous. A slight deduction for not mentioning related tools like reddit_comments or reddit_user_comments.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It adds useful context: output is 'normalized,' only public posts are returned, and a 503 with Retry-After indicates throttling with a specific retry guidance. However, it does not mention auth expectations, pagination response shape, or other error modes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no filler. The first sentence states the core purpose, and the second adds a valuable operational note about throttling. It is well-structured and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a simple list tool with three parameters, all schema-documented. The description covers purpose, output normalization, public-only scope, and an important throttling behavior. With no output schema, return details are somewhat vague, but for a straightforward feed-listing tool this is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters (username, limit, after) are already described in the input schema, with limit's default and clamp behavior explicitly documented. The description adds little beyond the phrase 'submitted feed,' which is a minor clarification rather than significant new parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a specific verb and resource: 'List Reddit user posts.' It further clarifies scope by noting it returns 'normalized public posts from a public Reddit user's submitted feed,' which clearly distinguishes it from sibling tools like reddit_user_comments or reddit_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by emphasizing 'public Reddit user's submitted feed,' but it does not explicitly state when to choose this over alternatives such as reddit_user_comments, reddit_subreddit_posts, or reddit_search. No exclusions or alternative-tool guidance are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description adds transparency about the data source (public browse pages) and authentication (credential-free), but does not disclose rate limits, response structure, or other behavioral traits. It sufficiently communicates that this is a read-only operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with three sentences front-loading the purpose and following with technical details. Every sentence earns its place without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple browse tool with no required parameters, the description is fairly complete. It explains what it returns and supported options. Without an output schema, it could mention return format, but it remains adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description reinforces valid values for list and sort, but adds minimal additional meaning beyond the schema. It does not introduce new constraints or formatting details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized TV series rows from Rotten Tomatoes browse pages, using credential-free JSON-LD data. It specifies supported list and sort values, distinguishing it from sibling tools like rottentomatoes_browse_movies and rottentomatoes_series.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lists supported values for list (tv_series_browse) and sort (popular, newest), giving clear context for usage. While it doesn't explicitly mention when not to use it, the specificity of values implies appropriate use cases versus other TV-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the burden of disclosing behavior. It clearly states the return payload: one product's full detail including pricing, availability, images, rating, and review count. No side effects are stated, but the tool is framed as a retrieval operation, which is sufficient for this simple get-by-id tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one cohesive block but is slightly redundant, repeating 'full detail' twice and saying 'Sam's Club product' three times. The first sentence could easily be merged with the following phrase. It is not verbose relative to the value of the return-field list, but it is not as tight as it could be.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter lookup tool with no output schema, 'the description covers the input source, the returned fields, and the scope—one specific product. It does not discuss error states or what happens if the id cannot be found, but these are not essential to successfully invoking it.'
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes the 'id' parameter fully ('Numeric Sam's Club product id, from a product page's /ip/{slug}/{id} URL'), and schema coverage is 100%. The description restates roughly the same source-of-id guidance and adds no new semantic details such as example values or validation behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Get') on a specific resource ('a Sam's Club product's full detail') and enumerates the returned content: name, brand, description, category breadcrumb, pricing, availability, images, rating, review count, and item number. This clearly distinguishes it from sibling tools like samsclub_category or samsclub_product_related.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the correct use case: when you have a specific Sam's Club product's numeric id from its /ip/ URL and want its full detail. It does not mention when-not conditions or differentiate from alternatives, so it stops short of a 5, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description discloses key behaviors: enrichment is best-effort with degraded sources listed without failing the core response, and data is credential-free and public. This adds transparency beyond the schema, though it does not mention rate limits or pagination.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured, front-loading the main purpose and then detailing optional enrichment. It is concise at 5 sentences, with no redundant phrases. Could be slightly tighter but effectively communicates complex information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lists what is included in the 360 overview (profile, financial snapshot, filings, events) but does not describe the output structure or format. Given the complexity and no output schema, more detail on the response shape would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% but the description adds significant context: explains enrich as a comma list, clarifies keying for market/news (ticker) and hiring (ATS + slug), and delineates Workday-specific parameters. This meaningfully supplements the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides a 'Company 360 overview from SEC data' aggregating profile, financial snapshot, filings, and events into one call. It specifies input methods (cik or ticker) and distinguishes from sibling tools like sec_filing or sec_financials by offering a consolidated view.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains how to identify the company (cik or ticker) and details the enrichment options, including source-specific requirements. However, it does not explicitly state when to use this tool versus alternatives like sec_company_submissions or sec_financials, nor does it provide conditions for not using it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description mentions 'clean text' output and credential-free access, but lacks details on idempotency, error handling, or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words; first sentence states purpose, second provides input guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers basic inputs and output format, but lacks mention of missing item handling or return structure. No output schema, so additional explanation would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline met. Description adds examples ('1A Risk Factors, 7 MD&A') and explains relation between cik/ticker and accession, but does not elaborate on max_chars.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs ('Extract') and identifies the resource ('10-K/10-Q/8-K item sections'), clearly distinguishing it from sibling tools like sec_filing (full filing) and sec_financials.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
States required inputs ('Provide accession plus cik or ticker') and context ('Credential-free public SEC data'), but does not explicitly contrast with alternatives or specify when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description carries the full burden of explaining behavior. It does disclose the response granularity (one page, each question with all answers) and the return fields, which is helpful. However, it omits other behavior an agent might need, such as pagination metadata, rate limits, or whether the response can be empty.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact, efficient, and front-loaded with the core purpose in the first sentence. Every sentence adds unique information: the resource being accessed, the return fields, pagination behavior, and the exact linkage of product_id to another tool's output. There is no redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with only two parameters, no annotations, and no output schema, the description covers the most important context: what is returned, the identity of the required parameter, and the new product_group_id mapping. It does not explain the page size or how many results appear per page, which is a minor gap but not a fatal one for an agent to call the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% coverage by describing product_id and page with defaults. The description goes beyond the schema by explaining that product_id is the Sephora productGroupID and maps it to the same value returned by /sephora/product as product_group_id, including an example. This removes ambiguity about how to obtain the identifier.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb-resource pair: it Returns one page of a Sephora product's customer Q&A. It further enumerates exactly what each returned item includes, such as text, author, brand answer status, and helpful votes, which makes the tool's function unambiguous and distinguishes it from related tools like sephora_product_reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives useful context by explaining the one-page behavior and how to obtain product_id, but it does not explicitly explain when to use this tool versus alternatives such as sephora_product_reviews or product search tools. The correct usage is implied rather than stated, so an agent receives guidance but no explicit when-not or exclusion phrasing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It mentions 'credential-free public JSON', indicating no authentication required and a read-only operation. This adds useful behavioral context beyond the tool name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: the first could be seen as slightly redundant with the tool name, but overall concise and front-loaded with the key action and result. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with no output schema, the description adequately explains the output and its usage. However, it lacks details on the return format (e.g., list of objects with season IDs and names) and potential error cases, which would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter that is well-described in schema. The description adds marginal value by providing context for the output's usage, but does not enhance parameter understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('returns'), resource ('season list'), and scope ('for a competition'). It distinguishes itself by explicitly mentioning the downstream usage with standings and round-events endpoints, providing differentiation from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states 'Use a returned season id with the standings and round-events endpoints', giving clear guidance on when and how to use this tool. However, it does not explicitly state when not to use it, such as when the season ID is already known.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Given no annotations, the description carries the burden. It discloses that credentials are fetched internally, which is useful, but lacks details on other behaviors like caching, rate limits, or response structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the verb 'Retrieve', and contains no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the essential purpose and auth behavior, but could be improved by briefly describing the response format (e.g., what normalized shelves and items look like) since no output schema is provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description does not add extra meaning beyond the schema's parameter descriptions, which are already clear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Spotify home sections, specifies the source as normalized shelves and items from Pathfinder, and distinguishes from other Spotify endpoints by noting it fetches anonymous credentials.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates when to use it (for home sections without requiring user auth) by mentioning anonymous credential fetching, but does not explicitly mention when not to use it or compare to siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description discloses key behaviors: returns sorted percentages, empty list if no stats, and 'Credential-free public Steam WebAPI JSON' indicating no auth required and response format. Missing details like rate limits or data freshness, but sufficiently transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences: action, return format, and edge case/credential-free note. No wasted words, information-dense.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers main functionality and edge case (empty list). No output schema, so return structure is implied but not fully detailed (e.g., fields per achievement). For a simple tool with one param, fairly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. Description mentions 'a Steam app' implying appid usage but adds no extra meaning beyond the schema's description. Adequate but no enhancement.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'Get', resource 'global achievement completion percentages for a Steam app', and scope. Distinguishes from sibling 'datasets_steam_achievements_search' which likely focuses on searching achievements rather than global percentages.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage for retrieving global achievement stats, but no explicit guidance on when to use this vs. other Steam tools or when to prefer the sibling 'datasets_steam_achievements_search'. Provides edge case (empty list) but no exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description discloses that the upstream serves a fixed batch, is credential-free, and does not support tag filtering or deep pagination. Lacks info on rate limits, error handling, or data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single paragraph, 4 sentences, each adding value. Front-loaded with main purpose. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Describes output structure (author, playtime, etc.) and limitations. No output schema, so description compensates well. Missing explicit batch size or pagination details, but sufficient for a feed tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% so the baseline is 3. The description adds context by grouping filters (e.g., 'review kind/sort') but does not significantly extend the schema's own descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it fetches community-recommended reviews across the whole store, listing returned fields (author, playtime, etc.). This distinguishes it from siblings like steam_reviews which are per-app.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly lists filter dimensions (review kind, playtime window, language, region) and notes limitations: no deep pagination, no tag filtering without auth. Context is clear but no explicit 'when to use vs alternatives' statement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses pagination behavior (zero-based and page 50 maximum) which is useful beyond the schema. However, it does not cover other behavioral aspects such as authentication, rate limits, or response field details. Since no annotations are provided, the description carries the transparency burden but remains partial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences that quickly state the purpose and the key pagination detail. There is no filler, redundancy, or unnecessary elaboration, making it highly concise and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with three documented parameters, and the description covers the purpose and pagination constraints effectively. Without an output schema, it does not define what fields a 'written review' contains, which is a minor gap for agents needing to interpret the response, but it is not a blocker for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes all three parameters with 100% coverage, providing a baseline of 3. The description adds value by specifying the upstream maximum page (50) and reiterating the zero-based pagination, which is critical for correct invocation. It does not mention default values but still enriches the semantic meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List Target product reviews' and further clarifies 'Returns paginated written reviews for a Target item.' This is a specific verb+resource combination that distinguishes it from sibling tools like target_product or target_questions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage through its purpose statement but does not explicitly state when to use this tool versus alternatives. It lacks exclusions or references to sibling tools, leaving the agent to infer selection based on the tool's name and purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that only the public first page is returned and that logged-out search lacks a continuation cursor. This is meaningful behavioral context about pagination and access scope, though it could also mention rate limits or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the core purpose, no wasted words. It covers the essential information efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter search tool, the description is adequate. It states what it returns and a key limitation. However, since there is no output schema, it does not describe the shape of the results, which is a minor gap for a tool that returns a page of results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully describes the single parameter 'q' as 'Search query (1-100 characters)'. The description adds no extra semantic value beyond echoing the concept of a query, so it does not improve on the schema's 100% coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Search public Threads posts.' It uses a specific verb and resource, and further specifies that it returns the first page of results. This distinctly separates it from other Threads tools like threads_post or threads_profile.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage through its search-oriented wording but provides no explicit when-to-use guidance or alternatives. It notes a limitation (no continuation cursor) but does not compare with sibling search tools or state when this tool should be preferred over others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states that the tool returns autocomplete suggestions, indicating a read-only, non-destructive operation, but it omits details about result format, limits, or error behavior. The description is adequate but thin.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loaded with the primary verb and resource, and contains no redundant or filler content. Every word contributes to understanding the tool's purpose and behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a simple one-parameter tool with no output schema, so the description carries the burden of explaining inputs and outputs. It covers the core behavior (suggestions for partial queries) sufficiently for an autocomplete utility. It could detail the suggestion payload structure, but for a suggest tool this is often unnecessary and the description remains complete enough for basic selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema fully covers the sole parameter q with a description that already states 'Partial artist, event, team, or venue query'. The tool description repeats this information but omits 'teams', adding no new semantic value. With 100% schema coverage, a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Suggest' and names the resource types (artists, events, venues), clearly distinguishing it from full-search siblings like ticketmaster_search_events. The phrase 'autocomplete suggestions for a partial query' precisely conveys the tool's autocomplete role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It clearly signals the intended use case: providing autocomplete suggestions as a user types a partial query. While it does not explicitly exclude alternatives or name sibling tools, the partial-query phrasing makes the use case obvious. No misleading guidance is present.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions cursor-based pagination but does not disclose other behavioral traits such as authentication needs, rate limits, or error handling. The description is somewhat transparent but incomplete for a tool with no annotation safety net.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: two sentences that clearly state the purpose and key feature (cursor-based pagination). Every sentence earns its place; no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (simple list tool with two parameters and no output schema) and presence of sibling tools like tiktok_challenge and tiktok_search_hashtag, the description covers the essential functionality and pagination. However, it could be more complete by hinting at the response structure (e.g., what fields are returned in each video). Still, it is adequate for selection and basic invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters have descriptions. The description adds value by clarifying that the 'id' parameter is a 'Hashtag id returned by the hashtag detail endpoint', which provides context for obtaining the id. The cursor parameter is briefly described. This extra context justifies a 4 rather than baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves TikTok hashtag posts for a given hashtag id with cursor-based pagination. It uses specific verb 'Retrieve' and resource 'TikTok hashtag posts', distinguishing it from sibling tools like tiktok_challenge (hashtag details) and tiktok_search_hashtag (hashtag search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly indicates use when you have a hashtag id and want videos, but it does not explicitly state when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. While the sibling list provides context, the description itself lacks explicit usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It indicates the tool returns a payload for a public handle, implying read-only behavior. However, it lacks details on payload contents, limitations, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences with front-loaded purpose. No unnecessary words; every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool without output schema, the description is sufficient. It covers the essential functionality and context among siblings, though it does not detail the return payload structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline is 3. The description adds no new information beyond the schema's parameter description (both state 'without the leading @'), so no extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a TikTok profile, using specific verb 'Retrieve' and resource 'TikTok profile'. It distinguishes from sibling tools like tiktok_post and tiktok_search by specifying it returns the profile payload for a public handle.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing profile data for a public TikTok handle, but does not explicitly state when not to use it or mention alternatives. It provides clear context for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It adds useful context by stating the tool returns one page, lists included fields, and notes that the data is credential-free. It does not mention ordering or potential rate limits, but for a simple read-only list this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences front-load the main action, then provide return fields and access context. Every sentence adds value with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with two optional parameters and no output schema. The description explains what is returned and the pagination behavior. It could be slightly more complete by explicitly noting ordering by popularity, but the tool name and current wording make this inferable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the schema already documents page and limit well. The description adds no additional parameter-specific semantics, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List') and names the exact resource ('popular people on TMDB'). It distinguishes itself from siblings like tmdb_person by clearly indicating this is a directory list, not a single-person lookup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for browsing TMDB's Popular People directory and notes it is credential-free, but it does not explicitly contrast with alternatives like tmdb_search or tmdb_person. No exclusions or when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral traits. It states that revenue figures are verified and describes the output structure (25+25 items). However, it does not disclose update frequency, caching behavior, or any limitations (e.g., rate limits). For a tool with no annotations, this is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences that front-load the purpose and include relevant details (counts, ranking methodology, verification). No extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple no-parameter tool without an output schema, the description provides a clear picture of what is returned. However, it lacks information about whether the snapshot is real-time or cached, and if pagination or filtering is possible. Still, given the simplicity, it is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so schema coverage is effectively 100%. The description adds no param info, which is acceptable; baseline for 0 parameters is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it gets a 'TrustMRR marketplace snapshot' and specifies the exact content: the 25 most recently listed startups and the 25 best deals ranked by a recency-aware deal score. This is distinct from sibling tools like trustmrr_startup (single startup) and trustmrr_startups (likely a different list).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for obtaining a curated marketplace overview, but it does not provide explicit guidance on when to use this over other trustmrr tools, exclude certain scenarios, or mention alternatives. Usage context is implied but not fully specified.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It explains that it returns public data, names the underlying source (Twitch GraphQL API), and describes the live-status conditionality ('when live'). This gives the agent a good mental model of what the operation does without asserting any unsafe side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two focused sentences, no filler. The core action is front-loaded, followed by concrete return values and a source note. Every sentence contributes usable content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter tool with no output schema or annotations, the description is complete enough: it names the input, enumerates the return fields, and states provenance and live-state behavior. It does not describe error cases or exact formatting, but neither is necessary at this level of simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single login parameter is already fully described in the input schema, and the description reinforces it by mentioning 'login'. Since schema description coverage is 100%, the description adds little beyond the schema, which is acceptable at the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a precise verb ('Get') and resource ('a Twitch channel's profile and live status') and details the exact return fields. It is clearly distinguished from sibling tools like twitch_streams and twitch_top_games because it is about a single channel's profile and live state, not stream lists or game rankings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies it is for fetching a single channel's static profile and current live status, and is distinct from search/discovery tools. However, it does not explicitly state when to prefer this over alternatives like twitch_streams or twitch_schedule, or include exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full transparency burden. It adds useful context: 'Credential-free public UberEats data' clarifies access requirements, and 'normalized' indicates data standardization. However, it does not disclose failure modes, potential incompleteness, or any other behavioral traits like rate limits or data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the action, and every clause adds value. It succinctly lists the return fields and the access constraint without fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (one parameter, no output schema), the description is quite complete. It enumerates the key return fields and the menu structure, and notes the credential-free nature. Minor gaps like no mention of potential errors or data source caveats exist, but they are not critical for a simple fetch operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of parameter semantics: store_id is described as 'UberEats store UUID, as returned by the search endpoint's storeUuid field.' The tool description adds no additional parameter-level detail, but the schema already provides sufficient guidance, so a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action and resource: 'Get an UberEats store.' It then lists the specific data returned (address, phone, rating, cuisine tags, hours tagline, full menu), which distinguishes it from sibling tools like ubereats_store_menu (menu only) or ubereats_store_reviews (reviews only).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool: when you need a normalized store with comprehensive details including the full menu and basic info. It doesn't explicitly name alternatives or exclusions, but the context implies this is the primary store detail tool, while siblings like ubereats_store_menu or ubereats_store_reviews serve narrower purposes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It states that data is 'Public data sourced from Upwork's own server-rendered job pages via a real browser-rendering backend,' informing the agent about the data source and potential behavior (e.g., real browser rendering, scraping). It also notes the output is 'normalized,' which adds useful context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the verb. It efficiently lists the returned fields in a single sentence, avoiding redundancy. The closing sentence about public data and browser backend adds value without bloat. No filler words or unnecessary details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one required parameter, no output schema), the description is sufficiently complete. It lists the returned data fields extensively and explains the data source. It does not detail the output structure, but that is implicitly a JSON object. For a detail-fetch tool, this covers the essential context for selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides a clear description for the sole parameter 'id' ('Upwork job id, e.g. from a search result's id field'), achieving 100% schema coverage. The tool description does not add any additional parameter-specific semantics, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Get Upwork job posting detail,' a specific verb+resource construction that clearly states the tool's function. It enumerates the returned fields, distinguishing it from sibling tools like upwork_search (which likely returns job lists) and upwork_freelancer (which targets freelancer profiles).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or alternatives are named. The description only states the action and data source. The parameter schema hints that the id comes from search results, but the tool description itself does not clarify that this is for supplementing search results or how it differs from upwork_search. Usage is implied but not articulated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the disclosure burden. It adds useful behavioral context: data is public, sourced from Upwork's server-rendered search pages via a real browser-rendering backend, and results are normalized summaries. It implies a read-only web scrape but does not discuss potential rate limits or pagination behavior, making it reasonably but not fully transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded purpose, efficient enumeration of returned fields, and a valuable note on data source. No filler words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 2-parameter search tool with no output schema, the description is fairly complete: it states purpose, returns (including field list), and data source. It lacks explicit details on result sorting, page behavior, or error conditions, but the schema covers the page parameter. Slight gaps are acceptable for this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema is fully covered at 100% with clear descriptions for q and page. The description repeats the keyword notion but adds no parameter-specific semantics beyond the schema. Baseline 3 applies because the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description begins with 'Search Upwork job postings' – a clear verb+resource combination. It further specifies free-text keyword search and enumerates the returned normalized job summaries (title, budget, experience level, duration, posted date, description snippet, skill tags), distinguishing it from siblings like upwork_freelancer and upwork_job.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use this tool (searching public Upwork job listings) but does not explicitly mention alternatives or exclusions. Given sibling tools like upwork_freelancer and upwork_job, the description could have stated 'use this for keyword search; use upwork_job for a specific posting.' Absent that, guidance remains implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that the tool uses 'credential-free public Walmart data' and is 'rendered from the product page through proxied browser renderers', providing important behavioral context beyond the basic operation. No annotations to contradict.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Concise two-sentence description that efficiently conveys purpose and key behaviors. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lists the returned data fields and explains the data source, providing sufficient context for an agent to understand what the tool does and what to expect. Without an output schema, it could benefit from more structural details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameter is fully described in the schema with a clear explanation of how to obtain it from the URL. The description does not provide additional parameter semantics beyond what the schema already offers.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the verb 'Get' with the resource 'Walmart product', and lists the returned fields (price, availability, etc.), clearly differentiating it from 'walmart_search' and 'walmart_product_reviews'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implicit usage context is provided by listing the returned fields (product details), but there is no explicit guidance on when to use this versus walmart_search or walmart_product_reviews.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description shoulders the behavioral disclosure burden. It reveals the output shape (flat list, no product data) and the edge-case behavior for zero matches ('returns a normal, empty result rather than an error'). It does not cover rate limits, auth, or formatting, but these are less critical for a low-level suggest endpoint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two tight sentences, zero wasteful language. The first sentence delivers the core purpose, and the second adds a relevant edge case. It is front-loaded and easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no annotations and no output schema, the description provides the input, return shape, and no-error edge case—enough to call it correctly. Its only noticeable gap is not explicitly directing the agent to wish_search for cases where product data is actually desired.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already has 100% description coverage for the query parameter ('Partial search term'), so the baseline is 3. The description adds light extra meaning by placing the query in the typeahead context, but it doesn't materially expand beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a clear verb and resource: 'Get Wish search suggestions.' It then specifies exactly what is returned—'Wish's own search-suggestion (typeahead) result' as a flat list of suggested search terms—and explicitly notes 'no product data,' which distinguishes it from product-search siblings like wish_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage context is implied clearly: it is for partial search terms and typeahead suggestions. However, it never explicitly states when to prefer this over alternatives or when-not to use it, relying on the 'no product data' clause to rule out product lookup.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full burden. It discloses that the tool returns public data and includes a quoted post preview when present. However, it does not mention any auth requirements, rate limits, or what 'visible metrics' specifically include. While not misleading, it leaves gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the verb 'Retrieve', and contains no filler. Every sentence adds value, making it efficient for an AI agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the lack of an output schema, the description adequately covers what is returned (author, text, visible metrics, quoted post preview). The term 'visible metrics' is somewhat vague but acceptable for a basic retrieval tool. No major gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters. The description adds behavioral context for the optional 'username' parameter, explaining that mismatched authors return a 404. This goes beyond the schema and helps the agent understand error conditions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Retrieve an X post') and resource, and lists the return fields (author, text, visible metrics, quoted post preview). It distinguishes the tool from siblings like x_profile_posts by focusing on single post retrieval by numeric ID.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving a single post by ID, and the optional username parameter adds context. However, it does not explicitly state when to use this tool versus alternatives like x_profile_posts, nor does it provide when-not or alternative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that it returns only the first page payload and does not paginate certain views. No annotations provided, so description carries burden. However, it does not mention side effects, rate limits, or mutability. Adequate but not outstanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, no unnecessary words. Efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with 2 parameters and no output schema, the description covers key behavioral aspects (first-page only, excludes certain tabs). No missing critical info for basic usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so schema already explains both parameters. Description adds minimal extra meaning beyond restating schema details (e.g., limit defaults/range). No output schema to describe return values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb 'List' and resource 'public X profile posts'. Distinguishes from sibling tools by specifying it returns only the first-page payload and does not paginate replies, media-only tabs, or search results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Clearly states what the tool does and its limitations (no pagination for certain tabs). Provides context on when to use (to list main profile posts). Lacks explicit comparison to siblings but is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the information source—'Yahoo Autos's own server-rendered homepage'—and the fields returned, but it does not mention output shape, whether the feed is paginated, or any rate-limiting behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that do their job: the first names the resource, the second details the return fields. No filler, no repetition of the schema, and no unrelated context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, read-only feed tool with no output schema, the description tells the agent everything essential: what it returns and where the data comes from. The absence of comments about array shape or pagination is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and zero required fields, so the schema coverage is complete and there isnothing unknown for the description to compensate for. The baseline for a zero-parameter tool applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Returns') and resource ('Yahoo Autos's homepage editorial story feed'), and explicitly lists the returned fields. This distinguishes it from sibling tools like yahoo_autos_article and yahoo_autos_category, which target different content scopes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes the tool's purpose easy to infer but does not explicitly say when to use this tool instead of the sibling article or category tools. There is no mention of alternatives or exclusion conditions, leaving usage guidance mostly implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the basic behavior (listing types) but lacks details such as whether the list is static or dynamic, or if any prerequisites exist. Since no annotations are provided, the description carries the full burden but only partially meets it.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that front-loads the purpose. Every word is meaningful, with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that the tool has no parameters, no output schema, and performs a simple listing, the description is nearly complete. It could mention that the output is a list of calendar type labels/identifiers, but it is sufficient for understanding the tool's basic function.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, and the schema coverage is 100%. The description does not need to add parameter information, so the baseline is 4. It correctly implies that no input is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool lists global Yahoo Finance calendar types supported by the integration. It uses specific verbs ('Lists') and identifies the resource ('calendar types'), distinguishing it from sibling tools like yahoo_finance_calendar_results which likely retrieves actual calendar events.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies that the tool is used to discover available calendar types, but it does not explicitly state when to use this tool versus alternatives like yahoo_finance_calendar_results. No exclusions or alternative suggestions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description bears the burden of behavioral disclosure. It identifies the source as Yahoo Sports' own public tournament-schedule JSON API and enumerates the returned data fields, which is helpful. It does not discuss response format, pagination, freshness, or any other operational behaviors, so coverage is moderate rather than strong.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only three sentences and each earns its place: the return value, the API source, and the tour enum plus id usage. The opening phrase is slightly redundant with the tool name, but otherwise it is tight and front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter tool without an output schema, the description covers everything needed: exact call intent, accepted tour values, optional season semantics, and a pointer to how results connect to the leaderboard tool. A reasonable agent can select and invoke this correctly without further inference.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage of parameters is 100%, so the baseline is 3. The description adds real value by listing all accepted values for the tour parameter even though the schema only says 'Golf tour key', and it explains how the tournament id relates to the leaderboard endpoint. The season default is left to the schema, but the added enum detail is meaningful.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Returns') and resource ('golf tour's tournament schedule for a season'), and enumerates the returned fields: name, dates, status, purse, and venue. It also ties the tool to its sibling by noting tournament IDs feed the golf-leaderboard endpoint, sharply distinguishing this schedule tool from the leaderboard tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes it clear the tool is for golf tournament schedules and points to the leaderboard endpoint as the consumer of tournament IDs, which implies a workflow. However, it never explicitly states when to prefer this tool over alternatives or when it should not be used, so the guidance remains implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, and it does add context: it identifies the source as a server-rendered page and specifies a race list fields to the caller can predict the output shape. Yet it does not talk about potential rate limits, data freshness, or effects of invalid series values, and it does not contain any declaration about read-only or side-effect behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise—three sentences—and each sentence supplies an indispensable piece of information: general scope, exact return fields, and accepted series keys. There is no fluff or repeated schema information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema, the description fully specifies the return object's fields and the accepted enum values, along with the data source. The tool is simple enough with no nested options and two parameters, so skipping explicit output schema is acceptable. Minor gaps include no mention of refresh behavior or edge cases, but these are not critical for making the call.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes both parameters (100% coverage), so the baseline is 3. The description adds essential value by providing the exact values for `series`. It also complements the schema by hinting that `season` is optional, even though the schema does that explicitly. This extra enum info is crucial and not available from structure alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description precisely identifies the verb level — 'Returns a series' season race list' — and enumerates the exact fields returned, which clearly distinguishes this schedule tool from the sibling yahoo_sports_motorsports_race. Even without explicit sibling differention, the description unambiguously scopes the tool to season schedules rather than individual races.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The context of getting a season race schedule is imput, and the description notes the valid `series` values, so an agent can infer when to call this tool. However, it does not explicitly state when to prefer this over yahoo_sports_motorsports_race or other Yahoo Sports schedule tools, nor does it mention any restrictions or fallback options.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It adds valuable context by stating the data is fetched 'via Yelp's real Android app backend' and that it is 'credential-free: no login, no API key, no cookie required from the caller.' This clearly addresses authentication requirements and the backend source, though it does not discuss rate limits or return structure in detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loads the core purpose, and adds only relevant backend and credential information. Every sentence earns its place with no unnecessary filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter read-only tool, the description covers the purpose, the input identifier, and credential requirements. It lacks an explicit output schema, but the phrase 'Fetches menu items' gives a basic sense of the return value. Minor gaps like failure modes or pagination prevent a perfect score.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides full coverage of the single parameter 'id' with the description 'Yelp business alias or encoded id.' The tool description does not add further meaning beyond the schema, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb and resource: 'Get Yelp business menu' and 'Fetches menu items for a Yelp business.' This distinguishes it from sibling Yelp tools like yelp_business, yelp_business_photos, and yelp_business_reviews, which have different data focuses.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used when the caller needs menu items for a Yelp business, but it does not explicitly state when to use this tool versus alternatives or provide exclusions. No alternative tools are mentioned, so usage guidance is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the tool uses Yelp's 'real Android app backend' (a non-obvious scraping mechanism) and explicitly states 'no login, no API key, no cookie required', which is valuable behavioral transparency about authentication. It does not mention rate limits or error behavior, but for a read-only gallery fetch this is reasonably sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose, and every clause adds value (backend source, no credentials). No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple: one required parameter, no output schema, no nested objects. The description covers what it does and key operational context (backend, credentials). It does not describe the response structure, but for a simple photo gallery fetch, the given info is largely sufficient. A few words on return format would push it to 5, but it is not critical here.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (id, limit, offset all have descriptions), so it meets the baseline. The description adds no parameter-specific meaning beyond the schema; limit and offset are self-explanatory and the id description is clear. With full schema coverage, a score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get Yelp business photos') and the resource ('photo gallery for a Yelp business'). It is specific and distinguishes from sibling tools like yelp_business_reviews and yelp_business_menu by focusing on photos.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly mention alternatives or when to use this tool over others. It implies usage for retrieving business photos, and notes the credential-free aspect, but there is no direct guidance such as 'for reviews use yelp_business_reviews'. This is implied through the tool name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries burden. States it is a read operation retrieving captions, but does not explain what 'caption cues' are (timed segments?), any rate limits, or prerequisites. Adequate but not detailed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words, front-loaded with the primary action. Efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Low complexity with 2 params, no output schema. Description covers purpose and return type, but lacks details on format of 'caption cues' and any error conditions. Slightly incomplete but adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with clear parameter descriptions. Description adds minimal extra value like 'auto-generated or human'. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb 'Retrieve' and resource 'auto-generated or human captions' for a specific YouTube video. Distinguishes from siblings like youtube_transcript by specifying 'caption cues' rather than full transcript.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage for obtaining timed captions, but lacks explicit when-not-to-use or alternatives like youtube_transcript. Given sibling list, some guidance would help, but purpose is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool retrieves metadata and captions, implying a read-only operation. However, it does not address error handling (e.g., invalid video ID) or rate limits, but for a simple retrieval tool, this is mostly sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences, front-loading the verb 'Retrieve'. Every sentence adds value with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description specifies return fields (title, description, stats, captions), which is helpful. However, it could be more complete by detailing the format of captions or stats, but it's sufficient for a basic understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter 'id'. The description adds no new meaning beyond the schema's description ('YouTube video ID (11-char code)'), but the parameter is self-explanatory, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: retrieve video metadata and captions. It specifies exact fields returned (title, description, stats, captions) and distinguishes from sibling tools like youtube_captions and youtube_transcript which focus on captions alone.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage context is implied through the description, but there is no explicit guidance on when to use this tool over alternatives (e.g., youtube_captions for just captions). No prerequisites or limitations are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It adds valuable behavioral detail: it returns Zara's own typeahead suggestions and explicitly states that nonsense queries get an empty suggestions array rather than fallback results. This is beyond what a basic read operation would imply.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is not overly long but has redundancy: the first sentence and the first half of the second sentence express nearly the same idea. The empty-suggestions behavior is valuable and the purpose is front-loaded, but the repetition could be trimmed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema, the description covers purpose, source, and a relevant edge behavior. It does not detail the exact response shape beyond mentioning 'a suggestions array', but the tool's simplicity and the clarity of that mention make this mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes 'query' as 'Partial search keyword', and the description merely repeats the same wording. It does not add new parameter semantics (e.g., min length, format, example values). With 100% schema coverage, baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Get') and resource ('Zara search-box suggestions for a partial keyword'), explicitly framing this as the typeahead suggestions shown while typing into Zara's search box. It also distinguishes between Zara-specific suggestions and full search-results calls, making the purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear usage context: use for partial keyword suggestions, not for full search results. It does not explicitly name alternatives like zara_search or provide when-not-to-use conditions, but the focus on typeahead and partial keyword is enough to guide an agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively communicates that results are normalized and may include semantic aliases and arrays, and it warns about preferring complete bounds metadata, which is useful for downstream search. However, it does not mention safety, error behavior, rate limits, or authorization requirements, which leaves some gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, each contributing meaningful information: what it does, what it returns, and a quality hint about candidates. There is no redundancy or filler, and the key action is front-loaded in the first sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (3 parameters, no output schema), the description gives a reasonable overview, mentioning normalized candidates and specific fields like region_id and bounds. However, without an output schema, it does not fully specify the response structure or error cases, which would be helpful for an agent to know exactly what to expect. The mention of 'semantic candidates' and 'bounds metadata' may be cryptic without further definition.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% coverage of the three parameters with descriptions for each, so the baseline is 3. The description does not add parameter-level details beyond the schema; the note about preferring bounds metadata relates to output rather than input semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Autocomplete Zillow locations' and specifies it returns normalized candidates. This distinguishes it from sibling tools like zillow_search, which performs property searches. The verb 'autocomplete' and resource 'Zillow locations' are specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for obtaining location candidates to feed into Zillow search, especially the note to 'prefer complete bounds metadata for Zillow search when present.' However, it does not explicitly state when to use this tool versus alternatives such as zillow_search or geocoding_search, nor does it provide exclusions or conditions. The usage context is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses pagination, returned fields (name, native name, image, favourites), and credential-free access. It doesn't mention rate limits or other constraints, but the provided information is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: the first states the core purpose, the second adds details on results and pagination. No wasted words, well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description explains the return format (summaries with specific fields) and pagination. The tool is simple and the description covers all necessary context for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters (page, query, per_page) are already described in the input schema with 100% coverage. The description adds 'paginated' and 'by name' but does not provide additional parameter-level meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches anime & manga characters by name, returning paginated summaries. It distinguishes from siblings like anime_search (which searches titles) and anime_character (likely single character details).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for character name searches but does not explicitly state when not to use or provide alternatives. No guidance on excluding other search scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the tool reads from Apple Books' public catalog page (implying no auth), returns series metadata and the full ordered list of audiobooks, and highlights the domain distinction. It does not cover pagination or error behavior, but for a read-only retrieval this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the primary action. The first and second sentences overlap slightly (both mention retrieving the series and its list), but the third sentence adds a valuable distinction. Efficient overall, with minimal fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema and annotations, the description adequately explains what the tool does, where the data comes from, and how this resource differs from a book-series. It lacks return-format specifics, but for a straightforward retrieval tool the essentials are covered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% — all params (id, lang, country) already have descriptive definitions. The description does not add param-specific meaning beyond what the schema provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb+resource ('Retrieve an Apple Books audiobook series and its full audiobook list') and clearly states the output (series metadata and ordered audiobook list). It also distinguishes from the sibling apple_books_series tool by explicitly noting that an audiobook-series is distinct from a book-series, even for the same conceptual series.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool versus alternatives by clarifying that an audiobook-series is a distinct catalog resource from a book-series. This helps an agent choose between apple_books_audiobook_series and apple_books_series, though it does not explicitly name the alternative or provide exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the source (modern podcasts.apple.com charts page) and the coverage of algorithms/types, but does not mention return format, pagination, limits, or any edge-case behaviors. It clarifies the operation is a retrieval (read-like), but lacks deeper behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary action and target. Every clause adds value — the first sentence captures purpose, the second adds source detail and differentiates from the sibling tool. No wasted words or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains the key dimensions (algorithm, type, genre) and the source, but does not describe the return structure or pagination behavior. With no output schema and no annotations, the agent receives only partial context; it knows what the tool does but not what it returns for various input combinations. Still, it is adequate for a simple chart retrieval.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of parameters, giving a baseline of 3. The description adds the key insight that chart algorithms are 'crossed with' entity types, explaining the combinatorial relationship between `chart` and `type` parameters, which is not explicit in the schema. This enriches parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Apple Podcasts chart rankings by algorithm, type, and genre. It names specific algorithms and entity types, and explicitly contrasts with the legacy RSS-based sibling endpoint, making its scope and differentiation unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides clear context by noting this is a 'richer, differently-sourced capability' than the legacy `/apple-podcasts/charts` endpoint, guiding the agent to prefer this for modern charts. However, it does not spell out exhaustive when-to-use/when-not-to-use scenarios or list other alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It credibly discloses that the data is credential-free public data sourced from Autotrader's server-rendered page, which goes beyond the tool name. It does not mention rate limits or failure behavior, but for a read-only fetch tool this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-load the primary action, then enumerate return categories. Every phrase adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter lookup with no output schema, the description fully covers the return payload (spec, images, pricing, description, seller), the data source, and access requirements. Nothing essential is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% coverage for the single 'id' parameter, including its meaning as the numeric URL path segment. The description adds no additional parameter-level detail, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a specific verb plus resource: 'Get Autotrader vehicle listing detail.' It enumerates the returned data (spec, description, seller), clearly differentiating this from the sibling autotrader_search and autotrader_dealer tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool is for retrieving a single listing once you have its ID, but it does not explicitly state when to choose it over autotrader_search or autotrader_dealer, nor does it mention exclusions like 'use search to find listings first.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full, so the explicit statement that only page 1 with up to 20 reviews is returned is valuable. It also discloses the source (dedicated reviews page) and the fields provided, giving an agent a clear picture of the tool's behavior and limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with the main action and resource, followed by useful return data details. The list of fields is informative rather than redundant, and nothing appears to be filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema, the description sufficiently describes the return fields, source, and page limit. It is complete for a simple one-parameter read tool, though it stops short of explicitly covering ordering, filters, or alternative sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes sku as 'Numeric Best Buy SKU' (100% coverage), and the description adds helpful context on how to discover it on bestbuy.com pages and URLs. This goes beyond the schema and helps an agent know where to locate the value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a precise verb (Get), a specific resource (Best Buy product's customer reviews), and details what the returned data contains. This makes the tool's purpose immediately clear and distinguishes it from at least related sibling tools like bestbuy_product, bestbuy_product_questions, and bestbuy_product_related.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use it: when a caller needs customer reviews for a specific Best Buy product. However, it does not explicitly contrast with alternatives or state when not to use it, such as when product questions or related products are the actual goal.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses that the data is from a public page and that output is normalized release rows, implying a safe read operation. However, it does not describe pagination behavior, rate limits, or any edge cases, leaving some behavioral traits undisclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the tool's purpose, and includes key usage guidance. Every sentence earns its place, with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core purpose, data source, and selector constraint. Given no output schema, it only vaguely mentions 'normalized release rows' without detailing fields or sorting/pagination behavior. It is adequate but not rich.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with descriptions for all six parameters. The description adds a critical constraint that exactly one of id, path, or url must be passed, which is not present in the schema. This provides meaningful semantic guidance beyond the structured fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized release rows from a Box Office Mojo genre page, identifying the tool as genre detail. It distinguishes from siblings like boxofficemojo_genres (which likely lists genres) by specifying the detail scope. The verb 'returns' and resource 'genre page' make the purpose explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context: it's for genre detail pages and requires exactly one of id, path, or url. This gives a concrete usage rule. However, it does not explicitly name alternatives or state when not to use this tool, so it lacks exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It adds valuable context: an empty list is a normal result (not an error), and the data is credential-free public data from CarMax's mobile-app API. These details set expectations for response handling and authentication, going beyond a simple purpose statement.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured. The first sentence states the main purpose, the second lists return values, and the third handles edge cases and data source. No redundant or irrelevant information is included; every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with two required, fully described parameters and no output schema, the description is complete. It explains what the tool returns, acknowledges the empty-list edge case, and notes that no credentials are needed. An agent has sufficient information to select and invoke this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema fully documents the two parameters. The tool description does not add further parameter-specific meaning beyond referring to 'a listing' and 'store location' in the return fields. Baseline of 3 is appropriate given the schema already handles parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get CarMax similar vehicles recommendations for a listing.' It specifies the resource (a listing) and the action (get similar-vehicle recommendations), and distinguishes this tool from siblings like carmax_vehicle or carmax_search by focusing on recommendations. The listing of returned fields further clarifies what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage through its purpose ('for a listing') and mentions data source, but it does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions. No sibling tools are referenced for contrast. However, the context is clear enough for an agent to infer primary use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It states it returns 'item cards' and lists defaults, but does not disclose pagination, data structure, or potential limits. This is adequate but lacks depth for a tool that returns a list of items.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loading the purpose and then providing examples, reference, and defaults. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the moderate complexity (4 params, 1 required, no output schema), the description covers usage and defaults but does not describe the return format or mention pagination. It is sufficient for a simple listing tool but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage, but the description adds value by providing example values (e.g., 'productivity/tools' for category) and stating defaults (num=50, country=us, lang=en). This helps agents understand parameter usage beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List items in a Chrome Web Store category' with specific verb and resource. It provides example category slugs and references /chromewebstore/categories, distinguishing it from sibling tools like chromewebstore_categories or chromewebstore_item.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description directs users to use /chromewebstore/categories for taxonomy reference and states default values for num, country, lang. While it does not explicitly contrast with sibling tools, the context implies this tool is for batch category-based listing, not for search or individual items.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description provides good behavioral transparency. It explains that thin cells are suppressed, enrichment-derived fields may remain empty if coverage is low, FX conversion is approximate, and guest_favorite_pct is an observed lower bound. It does not mention rate limits or authentication, but overall it is transparent about data characteristics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is long but well-structured. It front-loads the core purpose and then logically explains parameters, return fields, and behavioral notes. Every sentence adds value, though it could be slightly more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately explains return fields and key behaviors (aggregate-only, thin cell suppression, enrichment-derived fields). It covers sort enum values and parameter constraints implicitly. It is complete for a search tool, though it does not explicitly mention pagination constraints beyond what the schema provides.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant meaning beyond the parameter schema. It explains the group_by enum values in detail, including when they stay empty, and clarifies the meaning of return fields like median_price_usd, guest_favorite_pct, and avg_person_capacity. With 100% schema coverage, this exceeds the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches the Airbnb markets dataset and returns aggregate short-term-rental market rollups. It explicitly says 'Aggregate-only: each row is a market cell, never an individual listing,' which distinguishes it from tools like airbnb_search that may return individual listings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains what the tool does but does not explicitly state when to use it versus sibling tools like airbnb_search or datasets_airbnb_facets. It implies aggregate market analysis use case but lacks direct guidance on selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that it returns terms-aggregation counts and enumerates valid facet values and gross_band values. However, it doesn't describe the output structure (e.g., bucket keys, missing buckets), behavior when filters yield no results, or whether all filter parameters from search are fully supported despite the 'same filters as search' claim.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise at two sentences, front-loading the primary purpose and then enumerating supported facets and gross_band values in a compact, scannable format. Every word earns its place; no fluff or repetition of schema details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 17 parameters, no output schema, and no annotations, the description provides the core behavior and key enums but lacks detail on the exact response shape (e.g., list of buckets with counts) and edge cases. The schema descriptions cover parameters, but the description doesn't fully compensate for the missing output schema and annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by listing the facet enum values and the gross_band enum values (which are not in the schema enums but only in descriptions), and by clarifying that filters are scoped like search. This goes beyond the schema's parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Facet the Box Office Mojo dataset. Returns terms-aggregation counts for one facet...' This uses a specific verb ('Returns'), identifies the resource ('Box Office Mojo dataset'), and differentiates from sibling tools like search by focusing on aggregation counts and referencing 'same filters as search'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool by stating it returns facet counts scoped to the same filters as search. This implies usage for analytical aggregation on filtered data, but it doesn't explicitly exclude scenarios like returning individual records or mention alternatives such as the item or search tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. The description implies a read operation ('Get') but does not explicitly confirm non-destructive behavior or other traits like rate limits. A moderate score is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences, no redundant information, and front-loads the core purpose. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 15 parameters and no output schema, the description provides core semantics but lacks details on pagination, result structure, or behavior when no items match. It is adequate but incomplete for complex use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description goes beyond by stating that filters match the search endpoint and the sort is fixed. This adds meaningful context to the parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get trending Chrome Web Store items' with specific details about the ranking criteria (latest observed user and rating-count movement) and the fixed sort order. It effectively distinguishes this tool from its sibling search tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains that filters match the search endpoint and sort is fixed to trending_desc, which implies usage for trending data. However, it does not explicitly state when to avoid this tool or provide clear alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosure. It explains that the tool returns terms aggregation counts and warns that category facet values are exact locale-specific labels that may contain non-ASCII characters or punctuation, telling agents to pass them unchanged. This is useful behavioral context, though output structure and edge cases are not detailed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary purpose, and includes the facet enum and the critical category-value caveat. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 17 parameters and no output schema, so the description must compensate. It explains the core facet behavior but does not discuss how facets interact with q, filters, sorting, or output details. The rich schema covers parameters, but the description leaves some contextual gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds value by enumerating the facet options and specifying that category values must be passed unchanged to the category filter, including non-ASCII and punctuation handling, which goes beyond the schema's descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool's function: faceting stored Google Maps businesses and returning terms aggregation counts. It distinguishes itself from sibling tools like datasets_google_map_search and datasets_google_map_item by focusing specifically on facet counts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage through 'pass a returned value unchanged to the category filter,' but it does not explicitly state when to use this tool versus alternatives or provide exclusionary criteria. No direct comparison with other Google Maps dataset tools is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It goes beyond the schema by explaining the meaning of `rating: null` (no aggregate rating), `review_count: null` (Google didn't return a count) vs. `0` (confirmed zero reviews), and the effect of `min_rating` on unrated businesses. It also cautions about category localization/non-ASCII values. This is valuable behavioral context, though it does not mention pagination behavior or sorting, so a perfect score is not warranted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first sentence, followed by targeted guidance on category filtering and null semantics. It uses four sentences with no redundant filler. It is slightly longer than necessary, and the rating/review_count explanation could be tightened, but every sentence contributes useful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (8 parameters, no output schema), the description covers key nuances: the target dataset, category exactness, and rating/review_count interpretation. It does not describe the result items' structure, but this is somewhat mitigated by the dataset context. It is reasonably complete but would benefit from a note about pagination or the relationship to `datasets_google_map_item`.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides descriptions for all 8 parameters (100% coverage), so the baseline is 3. The description adds some context about `category` (localized, non-ASCII, punctuation) and `min_rating` behavior, but these largely overlap with schema descriptions. The description also focuses on output fields (rating, review_count) rather than parameter semantics, so it adds limited value beyond the structured schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Search nearby stored Google Maps businesses.' It clearly identifies the dataset (`google-map-businesses`), the coordinate-based search, and implicitly distinguishes from sibling tools like `datasets_google_map_search` (text search) and `datasets_google_map_item` (single item retrieval). This is a precise, differentiating statement.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use this tool (search businesses near a coordinate) and includes practical usage guidance for the `category` parameter (use the category facet to discover exact labels) and `min_rating` semantics (excludes unrated businesses). However, it does not explicitly name alternative tools or state when not to use this tool, so it falls short of a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description effectively conveys the behavior: it returns one record by default, or a monthly series when `history=true`, including envelope structure and sorting. However, it does not disclose potential issues like data staleness, authentication requirements, or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph of about 6 sentences, front-loading the core purpose. Every sentence adds information, though it could be slightly more structured (e.g., bullet points) for readability. Still efficient and concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description covers essential aspects: supported enums, defaults, and the history mode behavior. It omits error handling and exact response format for single records, but overall is sufficiently complete for a data retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All parameters have schema descriptions (100% coverage). The description adds value by listing enum values for region_type and property_type explicitly, stating defaults, and explaining the effect of the `history` parameter on the response structure.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the action (Get a US housing market record), the resource (dataset id `housing-markets`), and the key identifiers (region_type, table_id). Distinguishes from sibling tools like datasets_housing_markets_search and datasets_housing_markets_facets by specifying it returns a single record.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides details on parameters and their defaults but lacks explicit guidance on when to use this tool vs siblings like datasets_housing_markets_search (for multiple records) or datasets_housing_markets_facets (for aggregations). No 'when-not' or alternative recommendations are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses the data source (discovered company board registry), the meaning of sponsors_visa (certified DOL LCA filings), and the important caveat that results are historical evidence. It also provides enums for provider, status, and sort. It lacks explicit mention of pagination or rate limits, but those are partially covered by schema params.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense but well-structured: opening verb phrase, then explanation of data, a usage tip, a caveat, and enum lists. The enum lists are long but necessary for tool usage. No redundant sentences, though the paragraph could be slightly tightened without losing information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 8 optional params, no required params, and no output schema, the description explains the core purpose, filters (especially provider/status/sort), and the nature of the data. It does not explain min_open_roles, but that is self-evident from the schema. The sibling context includes many job tools, and the description's emphasis on company-level evidence helps disambiguate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining sponsors_visa in detail (recent DOL LCA data), and critically provides the full provider enum which the schema only labels 'Provider filter.' This goes beyond what the schema offers, raising the score to 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Find which companies are hiring' and specifies it searches 'the discovered company board registry' returning companies, ATS providers, and open role counts. This specific verb+resource pairing distinguishes it from job-level search tools like datasets_jobs_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (company-level analysis vs. specific role search) with 'This is company-level historical evidence, not a guarantee for a specific role or candidate,' but it does not explicitly name alternative tools or provide when-to-use/when-not-to-use guidance. The usage guidance is present implicitly but not contrasted with siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the facet dimensions, aggregation over all open postings, the remote share inclusion, and the seniority mutual-exclusivity rule with omission of ambiguous occupations. This exceeds a simple purpose statement, though it does not cover response structure or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a dense single paragraph that front-loads the core purpose. Each clause adds specific information (facet list, provider filter note, seniority quirk), though the lengthy list makes it slightly heavier than necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given one optional parameter and no output schema, the description adequately enumerates the returned facets and notes behavioral caveats (seniority, provider filtering via search). It does not detail the exact result format, but the facet list is sufficient for a facet tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter `size` is fully described in the schema (default 20, max 100). The description does not mention `size`, but with 100% schema coverage, the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Facet the jobs dataset' and enumerates specific aggregations (top companies, provider, department, location, etc.), making the action and resource clear. It distinguishes itself from sibling search/item tools by explicitly focusing on aggregates and the 'live hiring-market snapshot'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says provider filtering is done via /datasets/jobs/search's `provider` parameter, implying this tool is for unfiltered aggregates while search handles filtered queries. It provides clear context as a market-level snapshot, but does not explicitly name alternative tools or give when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses meaningful behavior: only geocoded postings participate, coordinates are back-filled by a geo-enrich worker, and open roles are the default. It could add return format or pagination details, but it covers significant caveats and default behavior, going beyond a simple summary.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is reasonably concise, with the core purpose stated in the first sentence. The provider enum list is lengthy but necessary and placed at the end. Minor redundancy exists ('Find postings near a coordinate' restated by the next sentence), but the overall structure is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 7 parameters, no annotations, and no output schema, the description covers the essential usage: coordinate-based search, radius, ordering, geocoding caveat, and provider filter. It lacks explicit description of the return fields or pagination behavior, but for a proximity search tool the provided context is solid and mostly sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 100% schema description coverage, the description adds value by explaining the provider enum values explicitly and clarifying the default of 'open roles only' which relates to include_closed. It also gives semantic context for radius_km and lat/lon, enhancing the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Find postings near a coordinate,' which clearly states a specific verb and resource. It further scopes the tool to geocoded job postings within a radius, ordered by distance, distinguishing it from sibling tools like datasets_jobs_search that likely search by text or filters.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for location-based job searches ('within radius_km of a lat/lon') and gives context like 'nearest first' and 'open roles only by default.' However, it does not explicitly state when to use this tool vs. alternatives such as datasets_jobs_search or when not to use it, leaving the choice mostly inferential.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden and handles it well by disclosing the exact-vs-best-effort nature of filters and the absence of an authoritative CUSIP-to-CIK mapping. It does not discuss pagination limits, response shape, or error behavior, but the join-caveat is the most critical behavioral nuance here and is clearly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three well-organized sentences: what the dataset is, how to filter reliably, and what sort options exist. No filler, front-loaded purpose, and each sentence earns its place. The most important caveat is embedded naturally without bloating the text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is a search endpoint with six optional parameters, no output schema, and no annotations, so the description must explain core search semantics. It explains the data source, the two search intents, and the key limitation, which is sufficient for the agent to invoke correctly. Minor missing context includes return-shape hints, but pagination details are already in the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3, but the description exceeds that baseline by explaining the reliability hierarchy among parameters (manager_cik as exact, issuer_name/cusip as best-effort) and enumerating allowed sort values. This contextual glue is not present in the schema descriptions and materially helps an agent choose parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies a specific action ('Search') and a specific resource ('SEC institutional positions dataset' with quarterly 13F holdings). It accurately conveys what the tool returns, but it does not explicitly distinguish this from closely related sibling tools like sec_institutional_holdings or datasets_sec_institutional_positions_facets, leaving that differentiation to the agent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides concrete guidance on when to use each filter path: manager_cik for a reliable full-portfolio lookup, and issuer_name/cusip for best-effort reverse lookup, including the important caveat about missing CUSIP-to-CIK mapping. It doesn't explicitly reference alternative tools or exclusion conditions, so it stops short of a full when-to-use-vs-alternatives statement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions the data source (public JSON) but does not disclose rate limits, potential missing data, or other behavioral aspects. Since annotations are absent, the description carries the burden but only partially fulfills it.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, no redundancy. Every sentence adds value: purpose in first, enum details in second.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description lists the main return fields, which is helpful. It could mention if additional metadata (e.g., links, stats) is included, but overall it is sufficient for a simple retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of parameters, and the description adds crucial semantics by listing all valid enum values for sport and league explicitly, which the schema only labels as 'Sport key' and 'League key'. It also notes the league must be valid for the sport.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns one athlete's bio/overview with specific fields (name, position, jersey, physicals, current team). It distinguishes itself from siblings like espn_team or espn_team_roster by focusing on individual athlete data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context about credential-free access and enum values for sport and league, but does not explicitly state when to use this tool versus others (e.g., espn_team_roster for a team's roster). No when-not-to-use guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations available, so description carries full burden. It notes the data comes from ESPN's credential-free public JSON, indicating no auth needed. However, it does not disclose rate limits, data freshness, or that it is read-only, which would be helpful.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no fluff. The first sentence states the purpose, the second details parameters. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, so description should clarify return format. It mentions grouping by conference/division but could be more specific. However, for a standings tool, the implied output is clear enough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema descriptions are minimal (e.g., 'Sport key'). Description adds explicit enum values for sport, league, and seasontype, and states season defaults to current. This adds significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description states tool returns league standings grouped by conference/division, which is a specific verb+resource. It clearly distinguishes from sibling tools like espn_scoreboard (scores) and espn_team (team info).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance. The purpose is implied but not contrasted with alternative tools. Would benefit from stating this is only for standings, not other ESPN data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden. It states the data is from ESPN's credential-free public JSON, implying no authentication is needed and it's a read operation. However, it does not explicitly state that the tool is read-only, nor does it mention rate limits, performance, or side effects beyond the implied safety of a public API.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact, consisting of two well-structured sentences. The first sentence states the core purpose and output fields, while the second enumerates the valid parameter values. No extraneous information; every sentence contributes directly to tool understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description provides a useful summary of the response fields (identity, colors, record, standing summary), which is adequate for an agent to understand the tool's data. However, it does not specify the format or structure of those fields, and the total completeness is slightly held back by the lack of details on how the data is presented.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant meaning beyond the input schema. It lists all valid enum values for 'sport' and 'league', which are absent in the schema descriptions. It also clarifies that 'league' must be valid for the chosen sport, providing critical dependency information that the schema's brief descriptions lack.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns one team's detail (identity, colors, record, standing summary) from ESPN's public JSON. It distinguishes itself from sibling tools like espn_teams (multiple teams) and espn_team_roster (roster) by specifying it returns a single team's full detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (when you need a single team's details), but it does not explicitly differentiate from espn_teams or other team-related tools. No when-not or alternative guidance is provided; the usage context is inferred from the output specification.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It clearly frames the tool as read-only and aggregate (Returns how many...), and the sentence 'Public data, sourced from Google Patents' own search API' discloses the data provenance and does not suggest authentication or mutation. It could mention output format or response size, but for a zero-parameter coverage tool the main behavioral surface is well covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is organized with a short title-like first sentence followed by an expanded returns sentence and a provenance note. It is not overly long and is still readable, but the first and second sentences essentially state the same grant-per-country-per-year idea twice, making the structure slightly redundant rather than maximally concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no parameters and no output schema, the description provides enough context to call it correctly: it states the data source, the granularity (per patent office/country and per year), and that it covers all authorities. The agent knows what will happen when invoked and roughly what to expect in the response. More detail about the exact response shape or whether the result is a single object or paged would make it even more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero declared parameters and the input schema is empty, matching the low parameter count exactly. There are no parameter names, defaults, enums, or formats to document, so the baseline score of 4 applies and the description justly adds no parameter-level detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description gives a specific resource (Google Patents database coverage), a clear verb (returns), and a precise scope: how many grants and applications are indexed per patent office/country per year across every covered authority. It cleanly distinguishes this from sibling tools such as googlepatents_search, googlepatents_recent, googlepatents_detail, and googlepatents_classification by saying it reports aggregate coverage rather than individual records.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly tells an agent to use this tool when any aggregate patent coverage count is needed, and the phrase across every authority it covers signals it needs no partitioning or filtering. However, it never explicitly says when to use it versus the other googlepatents_* tools, nor does it mention specific alternatives or exclusion cases, leaving the routing to inference from the tool family.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It addresses this well by stating the data is 'Public data' and 'sourced from Google Patents' own search API,' signaling that no authentication is needed and clarifying the provenance. It also says output mirrors the suggestions shown on the real UI, which sets expectations about what the response represents, but it does not cover details like response shape, error behavior, or rate limits, which are common for autocomplete endpoints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately brief at three sentences, with the core intent front-loaded: 'Autocomplete an inventor or assignee name for Google Patents search.' The second sentence adds useful context about the matching advanced-search-page behavior, though it repeats 'autocomplete' and 'inventor or assignee name' from the first sentence. The data-source sentence is compact and earns its place, but the redundancy keeps it from a 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a straightforward tool with two fully documented parameters, no annotations, and no output schema. The description adequately covers when to use it, where the datacomes from, and that it is public data. It somewhat addresses the unspecified output by stating the helper 'Returns Google Patents' own autocomplete suggestions,' which tells an agent that the likely output is a list of names, but does not specify the precise return structure. Given the simplicity of the tool, this is adequate and warrants a 4.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with both 'field' and 'value' descriptively documented, so the baseline score is 3. The description reinforces the parameter purpose ('inventor or assignee' for field, 'as the user types' for value) but adds no material insights beyond the schema, such as how partial name matching works, case sensitivity, or whether the field supports other values. Thus, the description does not meaningfully expand parameter meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Autocomplete an inventor or assignee name for Google Patents search.' It clearly distinguishes this from the sibling googlepatents_search (full-text patent search) and googlepatents_detail by focusing solely on the autocomplete behavior for the Inventor/Assignee fields. The mention of matching the advanced search page's suggestions further reinforces its unique role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies the appropriate use case: retrieving autocomplete suggestions as the user types a partial inventor or assignee name. It specifies that these suggestions align with the Inventor/Assignee fields on Google Patents' advanced search page, giving the agent context about the intended purpose. However, it doesn't explicitly name alternative tools (e.g., googlepatents_search) or state when NOT to use this tool, so it falls just shy of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It states the tool returns data (implying read-only), but does not disclose authentication needs, rate limits, or potential side effects. The description is adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences, front-loaded with the tool's identity, then usage instruction. Every word earns its place with no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description should explain what the returned credits look like (e.g., cast list vs crew roles). It only says 'normalized public IMDb full cast and crew sections', which is vague. For a data-returning tool, this is a gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% coverage with descriptions for both parameters (id and url). The description adds critical context: 'Pass exactly one of `id` or `url`', which clarifies the optional-but-one-required constraint not apparent from the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'normalized public IMDb full cast and crew sections', distinguishing it from other IMDb tools like imdb_title (which returns title details) or imdb_search. The verb 'returns' and resource 'cast and crew sections' are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Pass exactly one of `id` or `url`', providing a clear usage constraint. However, it does not elaborate on when to use this tool versus alternatives (e.g., for awards vs credits), nor does it mention any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey all behavioral traits. It states the output is 'normalized public IMDb quote rows' but does not disclose potential side effects, error conditions, data freshness, or authentication needs. The description is adequate but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two short sentences with no unnecessary words. It conveys the core purpose and a critical usage rule efficiently, earning its place without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two optional parameters and no output schema, the description is adequate but could be more complete. It does not describe the structure of the returned quote rows, pagination, or behavior when parameters are both provided or missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes both parameters with 100% coverage. The description adds value by specifying that exactly one of `id` or `url` should be passed, clarifying their mutual exclusivity beyond the schema's description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'normalized public IMDb quote rows for a title'. It uses a specific verb ('Returns') and resource ('quote rows'), and distinguishes from sibling tools like imdb_title_reviews or imdb_title_trivia by focusing on quotes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear usage instruction: 'Pass exactly one of `id` or `url`'. However, it does not explain when to use this tool over alternatives, such as other imdb_title_* tools, which are numerous in the sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the data is credential-free public data, the source is ImportYeti's JSON API, and notes the distinct behavior from the human-facing page (which has a bug). It also tells what fields are returned, which is helpful. Minor omission: no mention of rate limits or pagination behavior, but the schema covers page.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences plus one subsidiary clause. It is front-loaded with the main purpose, then returns fields, chaining, and source/credential context. Every sentence earns its place, though it could be slightly more concise by trimming redundant phrasing like 'Searches ImportYeti for companies...' after the first sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with no output schema, the description covers the key return values and the chaining workflow to importyeti_company. It also explains credential-free access and the API source. It could be more complete by mentioning pagination in the description, but the schema already provides that. Overall, it is sufficiently complete for an agent to select and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% coverage with clear descriptions for both q and page. The description adds little beyond the schema—it restates 'by name' and mentions return fields, but does not provide additional parameter context. Baseline 3 is appropriate because the schema handles parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches ImportYeti companies and suppliers by name, with a specific verb and resource. It lists the returned fields (kind, slug, country, address, shipment stats) and distinguishes itself from the sibling importyeti_company by explaining how a company result's slug chains into that tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool: for searching by name. It explicitly mentions the chaining to GET /importyeti/company, indicating that for detailed company data, use that tool after search. However, it does not provide explicit exclusions or compare with other search tools, leaving some implicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries burden. Discloses credential-free public access and inline detail. Does not mention rate limits, pagination, or data freshness, leaving some behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences with no fluff. Front-loaded with primary action and resource, followed by details. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema provided, and description says 'detail is inline' but doesn't specify format. Agent lacks return structure, but the description is adequate for selection and parameter usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions. Description adds value by clarifying 'company' is the Lever slug from careers URL and explains filtering semantics, enhancing understanding beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the verb 'list' and resource 'Lever postings'. Specifies it's public, credential-free, and distinguishes from sibling tools like jobs_lever_posting (singular) by mentioning plural and filtering options.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explains when to use: to list a company's public Lever postings with optional filters. Provides context about company slug and credential-free access. Does not explicitly compare to alternatives or state when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that the tool returns timestamps, but does not mention any behavioral aspects such as side effects, rate limits, or authentication needs. The tool appears read-only, but this is not explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two sentences with no redundant words. The first sentence clearly states the tool's purpose, and the second elaborates on the output. Highly front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple metadata tool with no parameters and no output schema, the description provides sufficient context. It explains exactly what is returned and for what purpose, making it complete for the agent to understand its usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters, and schema coverage is 100% (empty schema). The description adds meaning by explaining what the output represents, which is above the baseline of 4 for zero parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns cutoff timestamps for historical data migration. It specifies the resource (cutoff timestamps) and the action (returns), distinguishing it from siblings like kalshi_historical_market which provide actual market data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The description implies it is a prerequisite for historical data queries, but does not state when or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden, and it does well: it states the data is flattened out of the shared header nav, that URLs are read directly from the nav rather than guessed from labels, and that filtering by section reduces results. It even notes the output is designed to feed the category tool's parameters. This goes significantly beyond the minimal 'returns categories' and provides useful sourcing/behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact paragraph but a bit of a run-on, packing in several important details. The key function (browse categories, returns categories with names/paths/exact IDs) is front-loaded, and the detail about provenance (nav URLs, not guessed) adds value in one longer sentence. It earns its place, though splitting into two sentences would be slightly cleaner.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple browse tool with one optional parameter and no output schema, the description is almost complete. It explains what is returned, the source, the parameter behavior, and the downstream use. It does not state that the version of the data is a snapshot or that no external API or requires no API for the section values, but that is not a major gap for an agent to call it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameter's basic meaning is fully documented. The description adds some value by clarifying that 'section' filters to a top-level nav section and that the returned data supplies the parameters expected by another tool, but it doesn't enumerate valid values or a format beyond what the schema says. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb and resource: 'Browse lululemon's storefront category navigation', and details exactly what is returned: every navigable category with display name, breadcrumb path, and the exact category/cdp_hash pair. This distinguishes it from sibling tools like lululemon_category (singular) and other retailer category tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context well: it is the storefront navigation browsing tool, and the optional section parameter filters to a top-level nav section. It does not explicitly name alternatives or exclusions (e.g., lululemon_category for a single category's products), but the clear scope makes when-to-use obvious. Without an explicit 'use X instead' statement, it gets a 4 rather than 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It discloses that the data is public and credential-free, but lacks details about rate limits, response format, or any side effects. The description does not contradict annotations (none exist), but it is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is mostly concise with two sentences, but the first sentence is repeated verbatim. The key information is front-loaded. Minor redundancy reduces efficiency slightly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core functionality, output (paginated title cards with scores), and access (public). It does not explain error handling, rate limits, or output structure beyond what is implied. Given the tool's simplicity, this is adequate but could be more detailed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All 5 parameters have schema descriptions (100% coverage), but those descriptions are terse (e.g., 'Sort order'). The description adds meaningful context by listing example sort values (Metascore, popularity, release date) and mentioning genre and content type. It does not fully enumerate allowed values, but it enhances understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Browse Metacritic titles' with specific filtering, sorting, and pagination. It distinguishes from sibling tools (e.g., metacritic_game, metacritic_movie) which target individual items rather than listings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates when to use: for browsing Metacritic titles with optional genre and sort options. It notes 'Credential-free public Metacritic data,' implying no authentication. However, it does not explicitly state when not to use or name alternatives, though the sibling context implies that for specific titles, other tools are appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It mentions data is 'Credential-free public Numbeo data', indicating no auth needed, but does not disclose rate limits, freshness, or other behavioral traits. Adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the main purpose, no redundancy. Every sentence provides distinct information without waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool (one parameter, no output schema), the description fully explains what the tool returns (itemized prices and city indices) and data source, making it complete for agent invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter 'country'. The description adds value by noting the country name must be 'as Numbeo spells it', implying exact spelling matters, which is beyond the schema's definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'Numbeo country's cost-of-living prices', and specifies the output includes aggregate itemized prices and city indices, uniquely identifying this tool from siblings like numbeo_cost_of_living_city.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for country-level overview with city indices, but does not explicitly guide when to use this vs. alternatives like numbeo_cost_of_living_city or ranking tools. No direct comparison or exclusions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Given no annotations, the description fully discloses behavioral aspects: that it returns teaser content, that most numeric figures are gated and come as empty cells, not fabricated. This is transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, three sentences, front-loaded with purpose, no wasted words. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema, the description provides a comprehensive overview of what the tool returns (specific fields) and its limitations (paid gating). It covers the key aspects an agent needs to know.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with brief descriptions. The description adds that id and url are mutually exclusive, which is helpful but does not add significant semantic depth beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool returns the free/teaser content of a PitchBook fund profile, listing specific fields like strategy, status, manager, size, vintage, and previews. It distinguishes from siblings by the tool name and content type, though not explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear guidance that exactly one of 'id' or 'url' must be passed. Also explains the limitation that paid content returns empty cells, setting user expectations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It clearly states that numeric figures and full lists are gated behind a subscription and 'come through as empty cells rather than being fabricated', which prevents agent hallucination. It also normalizes missing FAQ sections as a non-error condition. This provides valuable context about output behavior and limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and information-dense, covering purpose, content, limitations, and usage in five sentences. The opening 'PitchBook limited partner profile.' is slightly redundant with the tool name, but the rest of the sentences all contribute meaningful details. Overall, well-structured and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simple schema (2 optional params), no annotations, and no output schema, the description is quite complete: it explains what content is returned, what is missing due to paywall, how missing content appears, and the parameter constraint. It does not describe the exact return structure, but the listed content types give a good preview. It is adequate for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are already documented. The description adds an important semantic constraint: 'Pass exactly one of id or url', which is not explicit in the schema since both are optional. This extra clarification helps the agent avoid invalid invocations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as returning a PitchBook limited partner profile and specifies the content types (overview, description, contact, fund commitment preview). It explicitly names the entity type, distinguishing it from sibling tools like pitchbook_company, pitchbook_fund, and pitchbook_investor. The verb 'Returns' and resource are precise.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for fetching free/teaser profile data and notes that paid figures appear as empty cells, suggesting this is for teaser content. However, it does not explicitly state when to use this tool versus alternatives (e.g., search tools for finding LPs, or the full datasets_pitchbook_limited_partners_item for complete data). No exclusions or alternative tool names are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses cursor-based pagination and legacy parameter behavior but does not mention read-only nature, rate limits, or any side effects. Basic transparency is achieved.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. First sentence states purpose, second sentence gives pagination and legacy info. Perfectly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description does not explain the response structure (e.g., product list with pagination cursors). It is adequate but could be more complete by mentioning that the response includes an end_cursor for further pagination.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds significant value by explaining which parameters are legacy and how cursor pagination works. This goes beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Product Hunt category products, now backed by topics, with cursor-based pagination. It is specific and distinct from sibling tools like producthunt_product or producthunt_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit pagination instructions using cursor and page_size, and clarifies that page, featured_only, order, and tags are legacy parameters that no longer affect results. However, it does not contrast with similar tools to help decide when to use this one.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It mentions 'credential-free' suggesting no auth needed, and 'normalized' indicates data transformation. However, it lacks details on pagination, rate limits, or data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, each concise and informative. The first states the core function, the second provides a key usage detail. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is adequate for a search tool but lacks details on return format, filtering logic, ordering, and default behavior. With 9 parameters and no output schema, more context would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% so baseline is 3. The description adds value by explaining that region_id/region_type can be passed from autocomplete to skip location resolution, clarifying the relationship between location and these parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches Redfin listings and returns normalized results. It distinguishes itself from sibling tools like redfin_property and redfin_similar by focusing on listing search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description hints at using region_id/region_type to skip location resolution, but does not explicitly state when to use this tool over alternatives like redfin_property or redfin_estimate. No exclusions or context for sibling tools are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only mentions 'credential-free JSON-LD ItemList data' without disclosing rate limits, pagination behavior, or whether results are cached. More transparency is needed for a read-only browsing tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Concise, no filler sentences; front-loaded with purpose, then enumerates parameters efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequately covers tool purpose and parameter usage, but could improve by indicating the output structure (e.g., fields in 'normalized movie rows') since no output schema exists.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Description adds significant value beyond the input schema by enumerating valid enum-like values for list and sort and specifying constraints, even though schema descriptions are present.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool returns normalized movie rows from Rotten Tomatoes public browse pages, distinguishing it from other Rotten Tomatoes tools like search or individual movie details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly lists supported list and sort values with their constraints (e.g., 'top_box_office' only valid with 'movies_in_theaters'), but does not provide when-to-use versus sibling tools beyond implicit browsing context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It explains the tool returns reviews with pagination metadata from a public JSON source, but it does not mention rate limits, authentication requirements, or any potential restrictions on scraping. The term 'hydrated' implies some processing, but the behavior is adequately but not fully transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long, with the first sentence stating the primary purpose. Every sentence adds essential information (what it returns, usage constraint, allowed types). No redundant or extraneous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description should compensate by detailing the return structure. It mentions 'normalized critic or audience reviews including pagination metadata,' which is adequate but generic. It does not specify the format (e.g., a list of reviews with `page_info`), which would aid an AI agent in understanding the response shape.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already describes all parameters. The description adds value by explaining the mutual exclusivity of `path` and `url`, and by listing the allowed `type` values explicitly (which are not defined as enums in the schema). This provides clarity beyond what the schema alone offers.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized critic or audience reviews from Rotten Tomatoes, with pagination metadata. It distinguishes itself from siblings like rottentomatoes_movie (which likely returns movie details) and rottentomatoes_search by specifying the resource (reviews) and source (review page JSON).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on how to use the tool: pass exactly one of `path` or `url`, and lists supported `type` values. It does not, however, compare directly with sibling tools or explain when to use this over alternatives like rottentomatoes_movie, which slightly reduces the score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It mentions 'credential-free public series page', implying no auth needed, which is helpful. However, it does not disclose rate limits, error handling, or response structure beyond 'normalized'. This is adequate but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loading the purpose and including the key usage instruction. No extraneous information; every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, and the description only vaguely says 'metadata and scorecard data'. For a data retrieval tool, more detail on return fields or structure would improve completeness. However, sibling tools and common expectations partly compensate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for 'path' and 'url'. The description adds the constraint 'Pass exactly one of `path` or `url`', which is not in the schema, providing additional semantic value beyond the basic parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns 'Rotten Tomatoes TV series metadata and scorecard data', specifying the resource (series) and action (returns detail). It distinguishes from sibling tools like rottentomatoes_movie, rottentomatoes_episode, and rottentomatoes_season by focusing on series-level data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly instructs to 'Pass exactly one of `path` or `url`', which is a clear usage guideline. However, it does not provide when-to-use vs. alternatives or when-not-to-use, though sibling names imply context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the burden of behavioral disclosure. It explicitly reveals the JS-executing browser backend, the required per-visit access token, and the bot-management challenge, with the result that responses may take longer. This is meaningful behavioral context beyond the schema. It could be stronger by specifying failure behavior or explicitly confirming read-only, but the disclosed latency and mechanism are already advanced information.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: the first front-loads the purpose and output fields; the second explains the non-obvious latency behavior. Both sentences earn their place, though the second sentence is dense with technical background. This is appropriately sized for a tool with such a notable execution path.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema, the description still mentions key returns: address, hours, BOPIS/curbside/same-day flags. The required coordinate parameters are covered by schema, and the latency caveat adds context important for planning. Some details like exact output structure or failure modes are missing, but the tool is simple and the provided inversion is enough for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers all four parameters in documentation: latitude, longitude, radius, and limit with bounds and defaults. The description adds only 'near a coordinate', which is more of a purpose statement than new parameter semantics. With 100% schema description coverage, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The first sentence clearly states the tool's role: it is a 'Sephora store locator' that returns physical store locations near a coordinate. It then names the returned data categories, which differentiates it from sephora_search and other product-level Sephora endpoints. The description is specific and non-tautological.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use this tool: when a caller wants Sephora physical stores near a latitude/longitude. It does not explicitly name an alternative tool or state when not to use it, but the store-locator framing and required coordinates establish a clear usage context. A 5 would require explicit exclusion guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description is the sole source of behavioral info since no annotations are provided. It discloses that the tool fetches anonymous Spotify credentials at request time and does not require caller-supplied tokens, which is valuable. It does not mention rate limits or result structure, but the authentication detail is significant.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences. The first sentence states the purpose, and the second adds a key behavioral trait. No unnecessary words, front-loaded with essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema and annotations, the description is somewhat incomplete. It covers purpose and authentication but does not explain the return format, pagination, error handling, or any other behaviors beyond auth. It is adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for all 9 parameters, so baseline is 3. The tool description does not add any parameter-specific meaning beyond what is in the schema, so it stays at baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches Spotify albums and returns normalized results. The verb 'Search' and resource 'albums' are explicit, and it distinguishes itself from other search tools like spotify_search or spotify_tracks_search by specifying albums.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context that this tool is for searching albums, which implies its usage. However, it does not explicitly mention when not to use it or provide alternatives, but the context is sufficiently clear for an agent to decide.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description does well by disclosing data source (Pathfinder), fallback mechanisms (episode page, embed, oEmbed), and that metadata is public. It is implicitly read-only. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with the core purpose, no fluff. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool, it covers purpose, parameters, and fallbacks. However, it does not describe the returned metadata fields or handling of invalid inputs, which could be helpful given no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds context: optionality, exclusivity (either uri or id), and default behavior. This goes beyond the schema's field descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves Spotify podcast episode details, specifies the data source (Pathfinder) and fallbacks, and the name matches. It is distinct from sibling tools like search or show listing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It tells how to use parameters (uri or id) and mentions default behavior, but does not contrast with alternatives like spotify_episodes_search or spotify_podcasts_show_episodes, nor when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the core behavior (returns all filter groups/options, context-aware options with filter_ids) and the mutual exclusivity constraint. However, it does not explain edge cases (e.g., what happens if neither q nor category_id is provided), error conditions, or return format details, which are important given the absence of annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long, front-loaded with the main purpose, and every sentence earns its place by adding functional detail. There is no fluff, redundancy, or irrelevant information, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and no annotations, so the description must be complete on its own. It covers the main behavior and parameter usage for q, category_id, and filter_ids, but notably omits store_id from the narrative (though schema covers it). More critically, the description says 'Provide exactly one' while the schema lists no required parameters, creating ambiguity about the behavior when no parameters or both parameters are provided. This gap in edge-case handling makes the description somewhat incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, setting a baseline of 3. The description adds value by clarifying the mutual exclusivity of q and category_id beyond the schema descriptions, and by explaining the purpose of filter_ids as a way to obtain 'remaining context-aware options,' which is more semantic than the schema's bare field description. store_id is not elaborated, but the schema already explains it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List Target filter options' and further elaborates with 'Returns every dynamic filter group and option for either a product query or category.' This specific verb+resource pairing distinguishes it from sibling tools like target_search (searches products) and target_categories (lists categories), making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage rules: 'Provide exactly one of q or category_id' and 'Pass currently selected option ids through filter_ids to obtain the remaining context-aware options.' This gives clear when-to-use guidance, though it does not explicitly name alternative tools or state when not to use this tool, leaving a small gap for full sibling differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden, and it does well by stating the ranking basis, the returned fields, and that the data is public and sourced from Twitch's GraphQL API. It stops short of mentioning pagination, rate limits, or invalid-category behavior, so not a 5.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with the core action and result shape. It has only slight redundancy between 'top live streams' and 'top currently-live streams', but no meaningful fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter read-only tool, the description provides sufficient context: the input scenario, output fields, ranking order, and data source. It lacks exact response-shape or edge-case details, but these are not critical for basic invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% coverage: 'game' includes slug-format guidance, and 'limit' includes its default and maximum. The description adds no parameter-specific meaning beyond that, so the baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb/resource—'Get the top live streams for a Twitch game/category'—and enumerates the returned fields. It is clearly distinct from sibling tools like twitch_top_games (top games) and twitch_search (search-based discovery).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives clear context for when to use this tool: when you need currently-live, viewer-ranked streams for a given Twitch game/category. However, it does not explicitly name alternative tools or state when-not-to-use conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full behavioral burden. It discloses pagination semantics ('one page'), output normalization, the presence of a rating summary, and the empty-response-rather-than-error behavior for zero reviews or unrecognized product IDs — non-obvious traits that materially affect agent expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, with the main verb and resource first and supporting details following, so it is well front-loaded. There is minor redundancy: the product_id source phrase partially repeats what the schema already documents. All other sentences earn their place, particularly the edge-case behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, so the description must convey return values; it does so by enumerating the rating summary components (rating count, average rating, recommended ratio, rating histogram) and identifying the page-based review payload. Given only two simple parameters, this is sufficient for a caller to use the tool correctly, though page size or more concrete review fields would help.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% so the baseline is 3. The description adds a meaningful non-schema fact: product_id can be sourced from a product page's URL in addition to the schema's 'search result's product_id field', which meaningfully enriches the parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb-resource pair ('Get an Ulta Beauty product's customer reviews') and names two distinct outputs: normalized review pages and the retailer's site-wide rating summary. This clearly distinguishes it from sibling tools such as ulta_product, ulta_product_questions, and other retailers' review tools without ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides operational context, explaining that product_id comes from a search result field or a product page URL and that empty/unknown IDs yield a normal empty result. However, it never explicitly states when to choose this tool over the closely related siblings (e.g., ulta_product_questions versus ulta_product_reviews), leaving the routing logic mostly implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description is the sole source. It discloses that the data is public and sourced from Vinted's server-rendered brands page, setting expectations for access and origin. It also notes the directory is curated and not exhaustive, which manages expectations about content coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loads the main purpose, and each clause adds distinct value (scope, ID usage, public data sourcing). No fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a no-parameter, no-output-schema read tool, the description covers the essential context: what it returns, scope limitations, and how results can be used downstream. It could specify entry fields beyond `id`, but that's a minor gap given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema is empty with zero parameters, so there is nothing to document. The description appropriately avoids unnecessary parameter detail, and the mention of entry `id` usage is relevant to the return value rather than input parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as returning Vinted's curated 'Popular brands' directory, with a specific verb ('Returns') and resource impact. It distinguishes itself from an exhaustive catalog by explicitly stating it's a curated subset, though it does not name an alternative sibling tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It states this is Vinted's own curated list, implying it should be used when a user needs popular brands rather than the full catalog. It also provides specific downstream guidance that each entry's `id` can be used as the `id` query parameter to /vinted/brand, which helps an agent decide when to call this vs. related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden, and it does a good job: it reveals the data source ('Wayfair's own published sitemap'), notes that 'name is derived from the category's own URL slug' and is 'not an authoritative site-provided label,' and clarifies the 'q' filter is case-insensitive. It could go further by outlining output fields or pagination behavior, but the safety profile of a list endpoint is already self-evident.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is moderately sized and starts with the clear lead 'List Wayfair categories.' Subsequent sentences, like the discovery-gap rationale and the URL-slug caveat, are relevant and informative. The second sentence is slightly conversational, but no sentence is wasted or redundant.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (3 optional params, no required inputs, no output schema), the description covers the essential facts: source, purpose, companion endpoint, naming caveat, and filtering behavior. It would be more complete with an explicit note about the default page size, but the schema provides that default, so nothing critical is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already explains q, page, and page_size. The description adds a small nuance about q (matching against derived name or department) and states the name's non-authoritative derivation, but it does not substantially extend the parameter meanings. This meets the baseline 3 for full schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'List Wayfair categories' – a specific verb and resource – and immediately differentiates the tool from its sibling wayfair_category by saying 'Pair a returned id with GET /wayfair/category to browse that category's product grid.' This unambiguously identifies what the tool returns and how it fits into the broader workflow.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states the tool's niche: discovering category ids from Wayfair's sitemap and closing the discovery gap when ids would otherwise have to be found elsewhere. It also implicitly defines the alternative – wayfair_category – by telling the user to pair a returned id with that endpoint. It does not formally list 'use X instead when...', but the companion-tool relationship is clear enough for an agent to route.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the entire burden of behavioral disclosure. It accurately describes what the tool returns and what input it accepts, making the read-only nature reasonably inferable. However, it does not state whether the operation is purely a read, what happens on invalid URLs, whether any auth is needed, or how errors are handled. Given zero annotation support, it is missing some behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and uses the first sentence to orient the reader, then provides a useful enumeration of the article fields, then the input constraint. There is a slight redundancy in the opening phrase 'Yahoo Life article content' and the sentence that follows, but it is short and immediately scopes the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter retrieval tool, the description is largely complete: it lists the returned content fields, which compensates for not having an output schema, and it clearly restricts inputs to canonical lifestyles URLs. Missing details like expected error behavior or null-return semantics are minor, given how narrow the tool is.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers the parameter with high specificity, so the baseline is 3. The description adds a valuable semantic clue by mentioning the URL type ('such as one returned by the home story stream'), which tells the agent where to source a valid URL from the sibling home stream tool. This workflow hint goes beyond what the schema says, even if the phrase is a mild repetition of 'canonical www.yahoo.com/lifestyle article URL.'
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a clear identification of the resource ('Yahoo Life article content') and then states with a precise verb and object: 'Returns a single Yahoo Life article's full content.' It enumerates the exact article fields (title, author, publish time, etc.), which distinguishes it from the many sibling article tools like yahoo_news_article or yahoo_tech_article. No ambiguity about which resource is targeted.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says to pass a canonical www.yahoo.com/lifestyle article URL, and it points to a concrete upstream source: 'such as one returned by the home story stream.' That implies a clear workflow coupling with yahoo_life_home. It provides useful context for when to invoke this tool, though it does not explicitly mention alternatives or when to use other article tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the transparency burden. It discloses that this is a read-style feed retrieval, lists exactly what each result contains, and explains that the data is sourced from Yahoo News's own server-rendered section pages. It does not mention pagination, rate limits, or auth, but it provides notably more behavioral context than a one-line description would.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded. It names the resource, describes the return payload, and notes the underlying source in only two sentences, with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter feed tool, the description is largely sufficient: it explains the resource and the return fields even without an output schema. The main gap is that it never provides example category values or clarifies how to determine valid Yahoo News section names.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description mostly repeats the 'Yahoo News section' concept in prose and does not add meaningful detail beyond the schema, such as valid category names or formatting expectations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear, specific operation: it returns a Yahoo News section's story stream and enumerates the expected output fields (title, destination URL, summary, source, publish time, comment count, thumbnails). This clearly distinguishes it from sibling tools like yahoo_news_home, yahoo_news_article, and yahoo_news_comments.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is clear: access the story stream for a Yahoo News section/category. It does not explicitly name when not to use it or alternative tools, but the section-level framing is distinctive enough that an agent can infer the right context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden, and it does so reasonably: it declares a read operation ('Returns...'), lists the exact response fields, and explicitly names the source ('Sourced from Yahoo News's own server-rendered homepage'), telling the agent this reflects live homepage content rather than a search or API layer. It omits ordering/size nuances but for a zero-parameter read tool that gap is minor.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences with no filler: purpose, field payload, then source provenance. Every clause earns its place. Minor deduction because the first sentence partially restates the tool name and the 'need to know' phrasing is stylistic rather than informative, but the structure is front-loaded and compact.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters, no output schema, and no annotations, the description carries a heavy burden and mostly meets it: it discloses the return values (seven named fields), the scope (homepage 'need to know' stream), and the provenance (server-rendered homepage). It stops just short of full completeness by omitting ordering, cap on story count, and freshness behavior, which a caller might reasonably expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, and the rubric sets a baseline of 4 in this case. The description correctly avoids inventing adjustable inputs; there is nothing to document beyond what the empty schema confirms.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific predicate-resource combination: 'homepage story stream' backed by a concrete field list (title, destination URL, summary, source, publish time, comment count, thumbnail images). It distinguishes itself from siblings like yahoo_news_article, yahoo_news_category, and the other Yahoo *_home tools by anchoring on the homepage, so an agent can select it without opening the schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage context is implied rather than stated. An agent can tell this is for retrieving the Yahoo News front-page feed, but the description never names alternatives or conditions ('use yahoo_news_category for vertical category stories'; 'use yahoo_news_article for a single story'), and with zero parameters the usage shape is simple. Since the when/when-not guidance is absent, this is at the minimum viable level.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It notes the data is 'sourced from the list page's own product cards,' indicating an opportunistic/scraped retrieval rather than a canonical database, and it lists the exact exported fields. It could add caveats about missing cards or pagination, but the source disclosure adds meaningful insight.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the operation, output fields, and source. The opening phrase 'Yahoo Shopping curated list items' is a fragment that largely repeats the tool's purpose, but every other sentence adds necessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Even though there is no output schema, the description documents the returned fields and explains where the slug comes from, which is sufficient for an agent to call the tool correctly with a single parameter. It could be slightly more explicit about the overall response shape or empty-list behavior, but it is otherwise complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the parameter description already explains that `list` is the list slug from GET /yahoo-shopping/shopping-lists. The description repeats this dependency but does not add meaningful new semantic detail beyond the schema, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Returns one curated Yahoo Shopping list's items' and enumerates the exact per-item fields. It clearly distinguishes this tool from related list/category/home endpoints by focusing on a single list's product cards.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells the agent to use GET /yahoo-shopping/shopping-lists first to obtain the required slug, giving a clear prerequisite and sequence. It doesn't discuss excluded alternatives, but the context is specific enough to guide correct invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral burden. It discloses the output contract (a slug, title, and image for each themed list) and situates the call as a read-only return of a curated directory. However, it does not disclose whether the directory is paginated or truncated, how many lists to expect, or any ordering/content constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three short, information-dense sentences, with the return value front-loaded and the routing tip kept last. The only flaw is redundancy — "Yahoo Shopping curated shopping-lists directory" appears verbatim in the first two sentences — which slightly wastes a slot.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, no-output-schema tool, the description fills in the important gaps: it names the shape of each list entry and tells the agent the next step to read items. The main open question is scale/pagination, and the description provides a usable, if not exhaustive, picture of behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so per the rubric the baseline is 4; the input schema is an empty object and there is nothing for the description to elaborate. The description consistently implies no filtering or inputs, which matches the schema, adding no contradictions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific resource — Yahoo Shopping's curated shopping-lists directory — and the exact return shape (slug, title, image per themed list), with concrete examples like "Cooling Essentials" and "Back to School". It also differentiates itself from the singular shopping-list endpoint by explicitly pointing the agent to GET /yahoo-shopping/shopping-list for reading a list's items, so it does not get confused with its sibling.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
"Use a list's slug with GET /yahoo-shopping/shopping-list to read its items" clearly routes the agent to the alternative tool and implies the directory is the discovery step. It qualifies as clear context for when to use this tool vs. the item-fetching sibling, though it stops short of explicitly naming the sibling or stating exclusions like "do not use this to read items."
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden and largely handles it: it states the returned data shape, handles omitted/invalid colorId, and specifies that an unrecognized productId returns 404. It does not mention rate limits or auth, but for a read operation this is a minor gap rather than a misleading one.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense and front-loaded, with each section covering output, parameter source, optionality, and error behavior. There is minor redundancy in the repeated 'full detail' phrasing, but overall no sentence is filler and the structure supports quick agent scanning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and no annotations, so the description is the primary source of behavioral information. It fully accounts for the return fields, the optional parameter behavior, and the failure mode. An agent has what it needs to call this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents the parameters. The description adds real semantic value by explaining where productId comes from and by clarifying that an omitted or invalid colorId still resolves to a valid base product variant instead of failing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as one that returns a single Zappos product's complete detail, with a specific list of what is included. It is easy to distinguish from zappos_search or zappos_suggest, but it never explicitly names a sibling or states 'use this instead of X.'
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear invocation context: productId should come from a search result's product_id field or a product page URL, and colorId is optional. It stops short of explicitly routing the agent between zappos_search, zappos_brands, and zappos_product, but the provided context is enough for correct selection in most cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite having no annotations, the description discloses key behavioral traits: 'Credential-free public data' and 'from Agoda's own flight content service'. This tells the agent no authentication is required and identifies the data source. It also mentions 'real-content amenities', implying live data. It does not detail error behaviors or rate limits, but the provided context is meaningful.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, each contributing essential information: what the tool does, what it returns, and how to obtain the input. It is front-loaded with the verb 'Get' and contains no redundant language.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one nested parameter, no output schema) and absence of annotations, the description covers the essential aspects: purpose, return content, input source, and auth requirements. It does not outline the return structure or pagination, but for a straightforward amenities lookup, it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with only a generic 'body' parameter described as 'One or more flight segments to fetch amenities for.' The description adds value by instructing to 'copy the segments straight from a flight search response's own segment fields,' which clarifies the source and format of the input. However, it still does not specify the exact nested structure or how multiple segments are represented, so it only modestly supplements the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Get Agoda flight segment amenities' and enumerates the returned content (aircraft type, seat layout, meals, entertainment, wifi). This distinguishes it from sibling tools like agoda_flights_search, which searches for flights rather than fetching amenities for existing segments.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides practical usage context: 'Copy the segments straight from a flight search response's own segment fields.' This implies the tool is used after a flight search and tells the agent exactly where to obtain the input. It does not explicitly name alternatives or exclusion cases, but the guidance is clear and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosure. It adds useful context: 'Credential-free public data from Agoda's own flight search' and mentions 'bookable' itineraries. However, it does not disclose rate limits, pagination behavior, or error/empty-result handling, which are important for a search endpoint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences with no redundancy. It front-loads the core function, then provides output details, a prerequisite, and auth context—each sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers core usage: what it searches, expected inputs (IATA codes, date), output fields, and auth requirements. It omits pagination details, result limits, and round-trip handling, but for a one-way search tool with a self-explanatory schema, it is fairly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds value by emphasizing that origin/destination are IATA codes and instructing to resolve free-text names first, which clarifies parameter usage beyond the schema descriptions. It doesn't detail every parameter, but the schema already does.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Search Agoda one-way flights' and lists specific output fields (per-segment flight number, airline, times, layovers, aircraft type, price). It distinguishes from sibling tools like agoda_flights_search_locations by explicitly focusing on one-way itineraries and referencing IATA codes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear prerequisite: 'Resolve free-text city/airport names to codes first via the flight destination search endpoint,' which directs the agent to a specific sibling tool. It also implies the tool is for direct IATA-code queries, but does not explicitly discuss alternatives like round-trip searches or other flight providers.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the tool uses 'Credential-free public data', which communicates a safe, read-only operation, and describes the output behavior ('each city's direct and nearby airports'). However, it does not mention limitations like rate limits, ambiguity handling, or error conditions, which would have made it even more transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, each earning its place: the first states the main action, the second elaborates on the input and output, and the third notes the access requirement. No filler or repetition, and it is front-loaded with the primary purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema or annotations, the description covers the essential aspects: input format, output type, purpose, and data source. It lacks details on error cases or result formatting, but these are not critical for such a straightforward lookup tool, making it nearly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes 'keyword' as 'Free-text city or airport name' (100% coverage). The description adds context by explaining that this keyword is resolved into IATA codes, but it does not provide new parameter-level meaning beyond the schema. Therefore, baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Search Agoda flight destinations/airports' and explains it 'Resolves a free-text city or airport name into IATA airport codes for flight search'. This distinguishes it from sibling tools like agoda_flights_search, which searches actual flights, and provides specific output details (IATA codes, direct and nearby airports).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool by stating it resolves locations 'for flight search', signaling it is a prerequisite lookup step before performing a flight search. It does not explicitly name alternatives or exclusions, but the context is clear enough for an agent to determine appropriate use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly states that this is 'credential-free public data' from Agoda's own hotel search, indicating no authentication is needed and clarifying the data source. It also discloses the return contents (matching property ids and direct links). It omits details like pagination behavior or rate limits, but for a search tool, the key safety and access traits are well covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the core action and resource, then efficient elaboration on inputs and data source. Every sentence earns its place with no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has four parameters, no output schema, and no annotations, the description is reasonably complete. It covers purpose, return shape, parameter flexibility, and authentication requirements. It could add more detail about the structure of the returned result set (e.g., pagination metadata), but for a search tool this is a solid level of contextual completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all four parameters thoroughly. The description adds marginal semantic value by restating the precedence rule for city_id over city and noting that at least one is required. This is helpful but largely redundant with the schema descriptions, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches Agoda hotels by city and specifies the exact output: matching property ids and direct listing-page links. It distinguishes itself from sibling tools like agoda_hotel_detail (single hotel details) and agoda_homes_search (different property type) by focusing on hotel search scoped to a city.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on how to use the tool: callers can supply either a numeric city id or a free-text city name, with city_id taking precedence. It does not explicitly name alternative tools or exclusions (e.g., 'use agoda_hotel_detail for a specific property'), so it falls short of a 5, but the intended use case is unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully cover behavioral traits. It states the tool returns a normalized character profile (read operation) and that it's credential-free public data, indicating no authentication or destructive actions. This is sufficient for a simple lookup tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no wasted words. The first sentence states the purpose and output fields, the second adds credential information. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a single parameter, no output schema, and a clear list of return fields, the description is fairly complete. It lacks details on error handling or rate limits, but for a simple get-by-ID tool, it adequately informs the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter 'id' with description 'AniList character id' and 100% schema coverage. The description adds that it's an AniList ID and that the tool gets a character, but does not provide additional format details or constraints beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get an anime/manga character' and lists the specific fields returned (names, image, description, etc.). It distinguishes itself from sibling tools like 'anime_character_search' which is for searching, while this tool retrieves a specific character by ID.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description specifies the required input ('by AniList id') and notes that it's credential-free public data. It implies usage when you have an AniList ID, but does not explicitly mention when not to use it or suggest alternatives like search for query-by-name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses return fields (narrator, duration, audio preview) and the conditional cross-link to the ebook edition. It also notes 'from Apple Books' public catalog page' and 'normalized', implying read-only behavior. It lacks error-condition details but adds meaningful context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the main verb, and each sentence adds value. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description adequately itemizes expected return data and the conditional cross-link. It could mention how to obtain the ID or link to search, but for an ID-based detail tool it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameters id, lang, and country are already fully documented. The description adds no parameter-specific semantics, leaving it at the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description uses specific verb 'Retrieve' and resource 'Apple Books audiobook details', clearly distinguishing from siblings like apple_books_audiobook_search or apple_books_book. The mention of 'normalized audiobook metadata' adds further specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies use when audiobook metadata is needed, but does not explicitly name alternatives or state when not to use. This is a clear context without exclusions, appropriate for a simple retrieval tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It usefully discloses the pagination mechanism (catalog page for first page, Apple review API for deeper pages, up to 20 per page), but does not describe the return shape, error behavior, or any rate-limiting considerations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary action, and every sentence adds value. There is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is a focused reviews retrieval endpoint with a well-documented schema. The description covers the core behavior and pagination nuances; what's missing (return fields, sorting) is not explicitly required given the simplicity and existing schema coverage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds meaningful semantics beyond the schema by explaining that page >1 or larger limits route through Apple's review API and that the max is 20 per page, which helps the agent understand parameter interactions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Retrieve') and clear resource ('Apple Books audiobook customer reviews'), stating it returns a page of reviews. It distinctly focuses on audiobook reviews, separating it from related siblings like apple_books_book_reviews or apple_books_audiobook_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Clear context is provided: this tool is for retrieving audiobook reviews, with pagination details explaining how pages beyond the first are fetched. However, it does not explicitly mention when to prefer this over alternatives like apple_books_audiobook_similar or apple_books_book_reviews.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It transparently explains the data source (catalog page vs API) and the pagination limit, which are key behavioral traits. However, it does not disclose error conditions, rate limits, or the exact structure of returned reviews, leaving some gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no waste. It front-loads the purpose in the first sentence and provides critical pagination details in the second. The structure is efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description adequately covers pagination behavior and data sources for a moderately complex tool, but it omits information about the content of the reviews (e.g., rating, text, author, date). Since there is no output schema, describing the return structure would improve completeness. Still, the core functionality is well-covered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents all five parameters (100% coverage), but the description adds value by clarifying the interplay between 'page' and 'limit' and the two different data sources. This contextual information goes beyond the schema's individual field descriptions, helping the agent understand how to paginate effectively.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Retrieve Apple Books customer reviews.' It clearly states the tool returns a page of a book's customer reviews, distinguishing it from sibling tools like audiobook reviews or book details. The purpose is unambiguous and precisely scoped.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides useful usage context about pagination (first page vs deeper pages, limit up to 20), but it does not explicitly mention when to use this tool versus alternatives like apple_books_audiobook_reviews or goodreads_book_reviews. The use case is implied rather than explicitly contrasted, so guidance is partial.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It adds valuable context about category_id being a dynamic, device-specific ID rather than a static enum, and lists device enum values. However, it does not disclose potential error behavior, rate limits, or data completeness, leaving some behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded: first sentence states the purpose, second clarifies the pivotal category_id, and third lists device enums. Every sentence contributes essential information with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the non-obvious workflow and parameter semantics well, especially the discovery of category_id via appstore_editorial. It mentions the return type (curated editorial shelves) but lacks details on output structure or failure modes. Overall, it is sufficient for a tool with a well-explained prerequisite but not exhaustive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description significantly enhances understanding of the key parameter category_id by explaining its numeric, device-specific nature and how to discover it from appstore_editorial. It also enumerates device values, which the schema does not. Other parameters (lang, country) rely on schema descriptions but are standard.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves an App Store category-scoped editorial page, with a concrete example ("Entertainment Apps for Vision"). It distinguishes itself from sibling appstore_editorial by specifying 'category-scoped' and the device-specific nature of the page.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It explains that category_id must be discovered from an appstore_editorial response for the same device, giving a clear prerequisite and usage context. It does not explicitly state when not to use this tool, but the implied workflow (first call appstore_editorial, then this tool) provides guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses locale defaults (country=us, lang=en-us), source (public Bing endpoint), and trimming to requested count. With no annotations, the description adequately conveys read-only behavior and constraints, though it could mention no side effects explicitly.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three efficient sentences: first states purpose, second describes output, third covers defaults and source. No unnecessary words, well-structured for quick parsing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, behavior, and parameters adequately for a simple suggestion tool. Lacks description of return format, which is mitigated by the schema's 100% coverage and the implicit nature of suggestions. Output schema absence is noted but not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds context about defaults for country and lang and explains trimming for count, which is helpful but not extensive. Does not compensate for missing output schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Suggest Bing search queries' and 'Returns Bing autosuggest query completions for a query prefix', identifying the verb and resource. Distinguishes from sibling suggest tools by specifying Bing as the source and from other Bing tools by focusing on query completion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description implies usage for generating autocomplete suggestions, but does not explicitly state when not to use or compare to alternatives like bing_search. However, the purpose is clear enough for selecting this tool over siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral burden. It adds useful context: 'public' indicates no auth, and 'normalized release rows' describes the output transformation. However, it does not disclose pagination behavior, default sort, error handling, or what happens if multiple/zero identifiers are passed. The description is reasonable but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences. The first sentence states the purpose and output; the second provides the key usage constraint. Every word earns its place, and it is front-loaded with the core function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with no output schema, the description adequately explains the return type ('normalized release rows') and the required identifier. It doesn't elaborate on sort/offset semantics, but those are documented in the input schema. It is complete enough for an agent to select and invoke correctly, though it could mention default behavior or what 'normalized' entails.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds critical semantics by mandating 'exactly one of id, path, or url,' which clarifies the mutual exclusivity and required-ness beyond the schema's empty required array. It also implies that sort/offset/sortDir are optional modifiers. This adds meaningful guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns normalized release rows from a Box Office Mojo brand page, using a specific verb ('Returns') and resource ('brand page'). It distinguishes from siblings like boxofficemojo_brands (plural, likely a list) and other boxofficemojo detail tools by explicitly calling out 'brand detail' and the output shape.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a clear usage constraint: 'Pass exactly one of id, path, or url.' This tells the agent which identifier to provide. It does not explicitly name alternatives or when-not-to-use scenarios, but the context is clear enough for a single-entity retrieval tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that data is 'credential-free public' and 'rendered from the reviews page through proxied browser renderers', hinting at web scraping behavior and potential latency. However, it does not detail rate limits, error handling, or pagination behavior beyond the page parameter.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose in the first sentence, and concise additional details in the second. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, but the description clearly indicates the return values (author, headline, rating, aggregate rating). It does not specify page size or ordering, but for a simple paginated tool, this is sufficient. Slightly incomplete because the exact structure of the output is not fully described.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining how to find the product_id ('the numeric id in a /p/{id}/{slug}/ URL'), which is not in the schema description. It also clarifies the page parameter by stating the default is 1 and that each page returns a page of reviews.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Get Capterra product reviews' and specifies the return content: normalized reviews (author, headline, rating) plus aggregate rating. It distinguishes from siblings like capterra_search and capterra_product by focusing on reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description notes 'Credential-free public Capterra data' implying no authentication required. While it lacks explicit when-to-use or when-not statements, the purpose is clear and distinct from sibling tools (e.g., capterra_product for product details, capterra_search for product search).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Discloses credential-free access, proxied browser rendering, and the fallback behavior (no empty-results page). Lacks details on rate limits or failure modes, but the key behavioral quirk is well-explained.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences plus a note, each serving a distinct purpose: purpose/returns, data source, and critical behavioral note. No fluff, front-loaded with most important information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description covers purpose, return fields, data source, and a notable behavioral characteristic. Could mention response ordering or pagination but not essential given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only one parameter 'q' with schema description 'Search query'. Schema coverage is 100%, so description adds no additional semantics beyond what the schema already provides. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the verb 'search Capterra products' and lists returned fields (id, name, url, description, rating). Differentiates from capterra_product and capterra_reviews by focusing on search results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides crucial guidance on interpreting fallback results for no-match queries, but does not explicitly contrast with sibling tools for when to use search vs. product/reviews. Sibling names imply context, but explicit alternatives would be clearer.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description takes responsibility for behavioral disclosure. It reveals that the tool is credential-free, sources data from CarMax's mobile-app API, and is typo-tolerant by default, which adds meaningful context beyond the schema. It does not cover rate limits or return format, but for a simple autocomplete endpoint this is acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with purpose, then adds critical behavioral and source details. There is no redundant or extraneous text — every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two parameters and no output schema, the description covers purpose, behavior, credential requirements, and data source. It does not describe the return format, but for an autocomplete tool this is likely obvious. It is adequately complete for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds some context by mentioning 'make/model/trim' and 'typo-tolerant by default,' but these are also largely implied by the schema's own descriptions. It does not significantly enrich parameter understanding beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb ('Get') and resource ('CarMax search autocomplete suggestions'), and adds scope details ('partial search term, make/model/trim'). This distinguishes it from sibling tools like carmax_search, which performs full searches rather than autocomplete.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool: when a user needs autocomplete suggestions for a partial term, especially since it highlights typo-tolerance. However, it does not explicitly mention alternatives or when not to use it, though the 'autocomplete' wording naturally differentiates from carmax_search.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses the data source ('CarMax's own mobile-app store-locator API'), credential-free access, and the specific fields returned (address, phone numbers, hours, driving distance for ZIP). This is strong transparency for a search tool, though it lacks info on error behavior or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with purpose, and each sentence adds distinct value (what it does, what it returns, data source). No fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description covers the key return fields and search behavior, and it clarifies distance applies only to ZIP-based searches. It doesn't describe the exact response structure or edge cases, but for a simple store-finder it's largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents all three parameters with full descriptions, including zip precedence and geo-sort. The description adds no new parameter-level semantics beyond restating ZIP or keyword search, so it only meets the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Search CarMax store (physical location) locations,' using a specific verb and resource, and immediately distinguishes from vehicle-focused siblings like carmax_search by emphasizing physical store locations. It lists concrete output fields, making the tool's function unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states searches are by ZIP or free-text keyword, and mentions the ZIP-based geo-distance feature, giving clear context for when to use the tool. However, it does not explicitly name alternative tools (e.g., carmax_search for vehicles) or provide when-not-to-use guidance, so it earns a 4 rather than 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description shoulders the full transparency burden. It discloses that the tool is credential-free, uses public data, and sources results from Cars.com's public search API, which conveys the read-only nature. It also details the normalized output shape, adding value beyond the tool name and schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences: the first states the core purpose, the second adds return details, and the third adds source/access context. Every sentence contributes essential information without repetition, and the opening is immediately clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description adequately explains what is returned (normalized vehicle summaries with listed fields and total count) and provides source context. It does not mention whether parameters are all optional, but the schema indicates no required fields, and the description covers the key functional aspects for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% coverage with clear descriptions for all four parameters, including allowed stock_type values and page default. The description adds no additional parameter-level meaning beyond what the schema already documents, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches Cars.com vehicle listings and specifies the types of listings (new and used) plus the exact returned fields. It distinguishes itself by naming the specific source (Cars.com) and the credential-free public API, separating it from sibling search tools for other automotive sites.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: whenever the agent needs to search Cars.com for new or used vehicle listings. It does not offer explicit alternatives or exclusions, but the purpose is unambiguous enough that the agent can select it appropriately among sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that the tool returns 'item cards' and lists defaults, but does not describe the return format (e.g., fields in each card), pagination behavior, or that it is a read-only operation. More context on the response structure would improve transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences plus a defaults list. It is front-loaded with the core purpose and every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (listing with optional filters) and lack of output schema, the description covers the core functionality and defaults. However, it does not specify what fields the returned 'item cards' contain, which would be helpful for an agent to interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by specifying exact accepted values for the 'chart' parameter (trending, popular, notable) and providing defaults for all parameters, which is not in the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List a Chrome Web Store top chart', specifying the verb 'List', resource 'Chrome Web Store top chart', and distinguishing from siblings like chromewebstore_search (which searches). The accepted chart values (trending, popular, notable) add specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides defaults for all parameters and acceptable chart values, giving clear context for usage. However, it does not explicitly mention when to use this tool versus alternatives like chromewebstore_search or chromewebstore_category, which could be helpful.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that trader details are only present for EU traders and specifies default values for optional parameters (num=50, country=us, lang=en). However, it does not explicitly state that the operation is read-only or mention any authentication requirements or potential errors.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the main purpose, followed by trader detail clarification, and ending with default parameter values. Every sentence adds unique information without redundancy, making it both concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately describes the return: publisher details with conditional trader fields and listed items. It covers the conditional nature of trader data and provides defaults. However, it does not describe possible errors (e.g., invalid id) or the structure of the returned items, which limits completeness slightly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema describes all 4 parameters. The description adds value by stating default values for num, country, and lang, which are not in the schema descriptions. The id parameter's format is repeated from the schema, so minimal additional value there.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a Chrome Web Store publisher and their items, including specific details like trader information and listed items. It explicitly mentions the verb 'Retrieve' and the resource 'Chrome Web Store publisher and their items', distinguishing it from sibling tools like chromewebstore_item or chromewebstore_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains what the tool does but does not explicitly state when to use it versus alternatives like chromewebstore_item for individual items or chromewebstore_search for finding publishers. The usage context is implied by the tool name and description, but no explicit guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full burden. It describes what is returned but does not mention authorization needs, rate limits, or that it is a read-only operation. The lack of behavioral context is a minor gap, but the description is honest and not misleading.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences efficiently convey purpose, returned fields, use case, and defaults. No redundant information; every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description lists returned fields comprehensively. It covers the essential context for a permissions retrieval tool. Minor omission: no example output or structure, but the list of fields is sufficient for the tool's narrow scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by noting defaults for country and lang (country=us, lang=en) and specifying that id is a 32-character extension id, which aids proper usage beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves declared permissions for a Chrome Web Store item and lists the specific fields returned. It distinguishes from siblings like chromewebstore_item (general info) and chromewebstore_privacy (privacy data) by focusing on permissions exclusively.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states the use case 'security and supply-chain review,' which guides when to use it. It does not explicitly exclude alternatives, but the narrow focus and specificity imply appropriate contexts. Sibling differentiation is implicit through the tool's purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool returns suggestions and lists defaults, but does not disclose potential error conditions, rate limits, or behavior for invalid inputs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no redundancy. The first sentence states the purpose, the second adds source and defaults. Highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple suggestion tool with 4 parameters and no output schema, the description covers the essential behavior, source, and defaults. It could mention the return format but is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% coverage with descriptions, but the description adds value by specifying default values for num, country, and lang, which are not in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it suggests search terms for autocomplete, returning item-name suggestions for a prefix. This distinguishes it from full-text search tools like chromewebstore_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies it's for autocomplete suggestions, and given the sibling chromewebstore_search, the usage context is clear. However, it does not explicitly exclude when not to use or mention alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses output fields (name, address, distance), sorting behavior (by distance), and that the data is public and sourced from Costco's backend. This goes beyond a simple purpose statement, though it omits details like distance units, result limits, or error behavior, preventing a perfect score.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise sentences with no fluff. Each sentence adds value: purpose, return details, and data source. There is minor redundancy (repeating 'near a latitude/longitude') but it is not distracting and the overall structure is efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 parameters, no output schema, no nested objects), the description is largely complete. It explains what the tool does, the inputs, and the return fields. The lack of distance unit specification is a minor gap but not critical for a straightforward lookup tool. A perfect score would require more explicit output structure or edge-case handling.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides descriptions for both parameters ('Latitude' and 'Longitude'), giving 100% schema coverage. The description adds the context that these coordinates are used for a nearby search, but does not add extra detail such as decimal degrees format, valid ranges, or coordinate system. This matches the baseline score of 3 when schema coverage is high.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Find nearby Costco warehouses,' which is a specific verb+resource statement. It further clarifies the tool's scope by specifying it returns warehouses near a latitude/longitude, sorted by distance, with name, address, and distance fields. This clearly distinguishes it from sibling tools like costco_search or costco_product_availability, which serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use the tool: when a user needs Costco warehouse locations near a given coordinate. It explicitly states the input is a latitude/longitude pair, which indicates the required context. However, it does not name alternative tools or provide explicit exclusion criteria, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the disclosure burden. It conveys read-only behavior via 'Get' and 'Returns one', and adds useful context that the record is 'crawled' and tied to the dataset enum `apple-podcasts-shows`. It does not discuss error behavior or data staleness in depth, but for a simple by-id retrieval this is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences, front-loaded with the action and source, with no redundant details. Every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is very simple: one required parameter, no output schema, and no nested objects. The description names the dataset enum, the record type, and the retrieval key, which is enough for an agent to invoke it correctly. It could optionally mention return fields, but that is not strictly necessary given the simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the `id` parameter already has a clear type description with an example: 'Apple Podcasts numeric show id (e.g. 173001861)'. The description only reiterates lookup 'by id' and adds no meaningful parameter semantics beyond what the schema already provides, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Get' with the resource 'Apple Podcasts show' and explains it returns one crawled record by id from the dataset enum `apple-podcasts-shows`. This clearly distinguishes it from siblings like `datasets_apple_podcasts_shows_search` or `apple_podcasts_show`.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It clearly implies when to use: when you already have an Apple Podcasts show id and need the crawled dataset record ('Returns one... by id'). However, it does not explicitly name alternatives such as search tools for finding ids, so it lacks an explicit when-not-to-use statement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full disclosure burden. It discloses the dataset discovery method, coverage limitation, and the sort enum, which adds behavioral context beyond the tool name. It doesn't mention pagination limits or rate limits, but those are partially in the schema and the core limitation is well disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (four sentences) and front-loaded with the purpose. Each sentence earns its place: dataset scope, search index, row granularity, provenance/limitation, and sort options. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description could explain return fields more explicitly, but it provides essential context about dataset coverage and sort options. The 100% schema coverage handles parameter semantics, making the description adequate for a search tool despite not detailing result fields.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 10 parameters. The description lists the sort enum values, but this duplicates schema content and does not add new meaning. It does not explain parameter interactions beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Search') and the resource ('Apple Podcasts shows dataset'), and distinguishes from siblings by describing the dataset as crawled from a chart grid and search-term sweep, not a full catalog. It also notes 'One row per show,' which clarifies the granularity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context about dataset provenance and its limitation ('not a full catalog of every Apple Podcasts show'), implicitly indicating this tool is for searching the crawled dataset rather than live Apple Podcasts search. However, it does not explicitly name alternatives or state when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description effectively communicates the tool's behavior: it searches a search index, returns normalized financial data and insider activity, and supports sorting and open filters. No contradictions or missing critical behavioral details like destructiveness or authentication.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with the core purpose, and each sentence adds meaningful detail without redundancy or fluff. It efficiently conveys complex filtering behavior in a single paragraph.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the high parameter count and absence of output schema, the description adequately explains the overall search behavior, included data, and filter idiosyncrasies. It could mention pagination trade-offs or response format to be fully complete, but it covers the essentials well.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds value by explaining that certain filters (entity_type, sic, etc.) are open filters discoverable via facets, and by enumerating sort options. This enriches understanding beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches the SEC companies dataset, detailing the included data types (filing history, financial rollups, insider activity) and sorting options. It distinguishes from sibling tools by mentioning facets for filter discovery, implying a complementary relationship with facets tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly states the tool's purpose for searching SEC companies, but does not provide direct guidance on when to use this tool versus alternatives like `datasets_sec_companies_item` or `sec_company_search`. The mention of using facets for filter values offers some contextual guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It clearly states the tool returns distribution counts and that it uses the same filters as search. Additional details like pagination or rate limits are absent but not critical for a facet endpoint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, directly stating the purpose, how it works, and listing facet values. No extraneous information; it is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the large parameter set (18) and no output schema, the description adequately explains the tool's function and relationship to search filters. It could mention result structure or limits, but overall it is sufficient for an agent to understand usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are well-documented in the schema. The description adds minimal value beyond emphasizing the facet parameter and its enum values, which is already listed in the schema description of the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool facets the website tech-stack dataset and returns distribution counts. It lists the specific facet enum values and notes it honors the same filters as search, distinguishing it from other dataset tools like datasets_techstack_search and datasets_techstack_item.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates this tool is for obtaining distribution counts ('market-share view') using search filters, implying it is for aggregated data. It lacks explicit 'when not to use' guidance but the context of sibling tools makes it clear that search or item tools are for raw data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the 404 behavior for missing domains and enumerates the returned fields (technologies, rollups). For a read-only dataset lookup, this is transparent enough, though it doesn't mention rate limits or authentication.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one long sentence that front-loads the purpose. It lists details efficiently but could be slightly more concise. Overall, it's well-structured and informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so the description must describe return values. It thoroughly explains the returned data: each detected technology (name, categories, confidence, version, evidence) and rollup categories (CMS, e-commerce, CDN, web-server, server-language). This is complete for a single-domain lookup.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by providing an example domain (shopify.com) and noting that scheme and 'www.' are stripped, which clarifies input formatting beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a site from the 'techstack' dataset by domain, listing specific data fields (technologies with details, rollups). It distinguishes from siblings like datasets_techstack_search (search) and datasets_techstack_facets (facets).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you have a specific domain to look up, but does not explicitly state when to use this tool vs. alternatives such as datasets_techstack_search for broader queries. No exclusion criteria or alternative tool names are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses chronological order, daily accrual, and the behavior of returning a short/empty series for new startups rather than 404. It could mention rate limits or authentication, but covers key behavioral aspects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no fluff: first sentence states purpose and lists returned metrics, second sentence clarifies a key behavioral nuance (accrual and empty series). Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description explains the return type (time-series), fields, and order. It lacks explicit structure (e.g., 'returns array of objects'), but the metric list and 'one point per day' give sufficient context. It does not cover error cases beyond empty series.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond the schema's parameter descriptions (e.g., inclusive dates, limit default/max). It does not provide context like format examples or parameter interactions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'a startup's daily history', listing specific metrics (MRR, revenue, traffic, etc.). It effectively distinguishes from siblings like datasets_trustmrr_item (current data) and datasets_trustmrr_search (search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly indicates usage for historical time-series data, contrasting with current-data tools. However, it does not explicitly state when not to use it or name alternatives like trustmrr_startup for a single point-in-time snapshot.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite having no annotations, the description discloses the key behavioral trait: it is a dedicated aggregates API returning only count breakdowns, not embedded listing data, and the data is public. This prevents an agent from expecting search results or treating it as part of depop_search bulk output.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Every sentence earns its place: initial summary, return details, API source, and public-data qualification. It is three short sentences and front-loaded with the main purpose. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter public tool with no output schema, the description adequately covers what is returned and how via the API. A bit more detail about the shape of the breakdown would help, but given the simplicity of the tool, this is nearly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully describes 'query' as 'Free-text keyword search' at 100% coverage. The description adds only 'for a search query,' which repeats the schema without introducing format examples, limitations, or query-construction tips. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a precise verb and resource: 'Returns result-count breakdowns per department/category/subcategory for a search query.' It also distinguishes itself by explaining that it uses a dedicated aggregates API, separate from search responses, which differentiates the tool from siblings like depop_search and depop_search_sellers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to call this tool: when an agent needs aggregate result-count breakdowns rather than search listings. It adds helpful context that this is a distinct upstream call, but it doesn't explicitly name alternatives or exclude when to choose other Depop tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It states that the data is public and sourced from Depop's own API, implying safe read-only access. However, it does not disclose the response structure, whether the list is paginated, or how large the taxonomy may be, which leaves a moderate gap for an un-annotated tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences contain all relevant information without filler. The description front-loads the action ('Get Depop's size taxonomy'), then adds specific details about scope and usage in the second, compact sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema and no annotations, but the description communicates the return conceptualization, data source, and downstream use in enough detail to support correct invocation. A concrete example of the composite ID format or response shape would make it fully complete, but for a zero-parameter public reference lookup it is largely sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so the baseline for parameter semantics is 4. The description adds no parameter explanations but does add semantic value by stating the purpose of the returned IDs (for use in depop search/shop size filters).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description names the exact resource ('Depop's size taxonomy') and gives a specific verb ('Get'), clearly distinguishing it from taxonomy siblings like depop_brands and depop_categories. It also specifies the outputs are composite IDs usable with /depop/search and /depop/shop filters, leaving no doubt about what the tool provides.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes it clear the returned IDs are intended for the sizes filter in specific Depop endpoints, giving an agent strong context for when to fetch this taxonomy. It does not explicitly state when not to use it or name alternatives, but the pointed reference to the filter serves as a useful usage cue.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the full behavioral burden. It discloses that results are public data from Depop's own API and that category mapping is included where relevant. However, it doesn't mention whether suggestions are limited, rate-limited, or shaped differently from the native Depop UI, leaving some behavioral ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact, front-loaded with the purpose, and provides the additional API source detail in a second sentence. There is no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter autocomplete tool, the description covers the core use case and clarifies the output type (suggestions) with optional category mapping. It doesn't describe exact output shape or limits, but that is less critical given the absence of an output schema is common for lightweight suggestion tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers the single 'query' parameter with a clear description. The tool description also clarifies the parameter's role as a partial query, which supports the schema without contradicting. With 100% schema coverage and a single parameter, the description adds enough context to move slightly above baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool is Depop's search-box autocomplete, returning suggestions for a partial query. It also includes the relevant detail that category mapping is returned where applicable, which differentiates it as a lightweight autocomplete rather than a full search tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly indicates when to use it (for partial query autocomplete) and specifies the input is 'partial'. It doesn't explicitly contrast with sibling tools like depop_search or amazonsuggest, but the context is sufficient for an agent to select the right operation for typeahead behavior.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the transparency burden. It discloses the key auth requirement (none required) and the Android mobile guest experience context. It does not mention result format or pagination, but for a read-only search this is acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences, front-loaded with the core purpose, and every clause adds value (scope, context, auth). There is no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 3-param search tool with no output schema, the description covers purpose, scope, and authentication. It lacks only explicit details about return value structure, but the tool's simplicity and the schema's clarity make it largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and each parameter has a clear one-line description, so the baseline is 3. The description adds that lat/long correspond to 'nearby merchants', but it does not elaborate on units or query syntax beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the verb 'Search' and the resource 'DoorDash dishes and items', and adds the scope 'across nearby merchants from the Android mobile guest experience', distinguishing it from sibling search tools. It also notes that no account/token is required, making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use this tool: to find specific dishes/items near a location without authentication. However, it does not explicitly exclude alternatives or name sibling tools, so it stops short of full usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that no DoorDash account or caller-supplied token is required, and that data comes from the Android mobile guest experience. This adds value beyond a simple 'get details' statement, though it doesn't cover rate limits or error behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no filler. The first sentence states the core action and return types, and the second adds context about the source and auth requirements—every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a three-parameter, no-output-schema tool, the description provides sufficient context: what data is returned, where it comes from, and auth requirements. It is not exhaustive (no mention of error cases or relationship to other doordash tools), but it is adequate for a read-only lookup.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with descriptions for all three parameters (store_id, latitude, longitude). The description doesn't add additional meaning beyond the schema, so it meets the baseline but doesn't exceed it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves store fulfillment details and specifies the output: fulfillment methods, delivery fee info, and scheduling details. It also identifies the source as the Android mobile guest experience, which distinguishes it from siblings like doordash_store_info, store_menu, and store_reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes the tool's purpose explicit by enumerating the returned data, so an agent can infer when to use it. However, it does not explicitly name alternative tools or state when not to use this one, which would be helpful given the large number of DoorDash sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does well: it identifies the data source (Android mobile guest experience), the nature of the response (lightweight card with specific fields), reliability (reliably includes address/coordinates), and the auth requirement (none). It could add more about error cases or the role of the delivery coordinates, but the disclosed traits are useful and go beyond a generic 'get store info'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, no filler. The first sentence states the core purpose, the second details the response content and source, and the third differentiates from the full endpoint and covers auth. Every sentence earns its place and the information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with no output schema or annotations, the description covers what the tool returns (map coordinates, address, phone), its source, and auth requirements, which is largely sufficient. The main gap is that it does not explain why delivery latitude/longitude are required and how they influence the lookup, nor does it describe the output structure beyond a 'card'. Given the low complexity, this is a minor omission.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% coverage with basic descriptions for store_id, latitude, and longitude (e.g., 'Delivery latitude'). The tool description mentions returned coordinates, address, and phone, but does not explain the relationship between the delivery latitude/longitude inputs and the returned store coordinates, nor does it add any additional semantic nuance beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets DoorDash store contact info and returns a lightweight info card with map coordinates, address, and phone number. It differentiates itself from the full store endpoint by noting it is a 'distinct upstream contract' and reliably includes address/coordinates, which also distinguishes it from siblings like doordash_store_menu or doordash_store_reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use this tool: when you need lightweight contact info and reliable address/coordinates, and explicitly notes it is a distinct contract from the full store endpoint (implying use this instead of a heavier endpoint). It also removes a potential barrier by stating no account or token is required. However, it does not explicitly name alternative sibling tools or state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the transparency burden. It discloses that no authentication is required, that the menu is location-aware, and describes the response structure. It lacks details on errors or rate limits, but covers the key behavioral aspects for a read-only fetch.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the primary purpose, and no filler. Every clause adds useful information about output or authentication.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple menu-fetching tool with no output schema, the description explains the return content (sections, item names, descriptions, prices) and the auth context. It could mention failure modes or whether item IDs are included for follow-up calls, but overall it is sufficiently complete for typical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with each parameter described (store_id, latitude, longitude). The description adds context that the menu is location-aware, tying latitude/longitude to behavior, but does not add further format or constraint details beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Get a DoorDash store menu.' It clearly states what is returned (menu grouped into sections with item names, descriptions, and displayed prices), distinguishing it from sibling tools like doordash_store or doordash_store_item.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: this returns a location-aware menu and requires no DoorDash account or token. It does not explicitly name alternatives or exclusions, but the purpose is specific enough for an agent to choose it for menu retrieval.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that results are 'normalized', lists exactly what fields are returned, mentions page-based pagination, and notes the underlying data source (DuckDuckGo's own image JSON API). It does not cover rate limits or error behavior, but for a read-only search tool this is reasonably transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the primary action, and every phrase earns its place. The output fields and pagination are summarized without fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 params, no output schema, no annotations), the description covers the essential aspects: purpose, return values, pagination, and data source. It omits details like per-page result limits and error cases, but the provided information is sufficient for most use cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% parameter description coverage, so the baseline is 3. The description adds context for 'q' (query string) and 'page' (page-based pagination) but does not meaningfully elaborate on 'region'. It mostly echoes the schema, so no additional semantic value beyond the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Search DuckDuckGo image results' – a specific verb and resource. It then enumerates the normalized fields returned (title, source page URL, image URL, thumbnail, dimensions, hostname) and mentions pagination, clearly distinguishing it from sibling tools like duckduckgo_video, duckduckgo_news, and duckduckgo_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: this is for image search on DuckDuckGo, and it even notes the pagination model. However, it does not explicitly state when to prefer this over alternatives (e.g., bing_images or brave_images) or when not to use it. The context is sufficient for basic selection but lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses the return format (title, destination URL, description, duration, thumbnail, publisher, published time, view count), pagination behavior, and the data source (DuckDuckGo's own video JSON API). This goes beyond minimal details, though it does not mention rate limits or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the main action, and every sentence adds value. It lists return fields compactly without unnecessary fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is no output schema, the description compensates by listing the returned fields and explaining pagination and data source. It is complete enough for an agent to understand what the tool does and what to expect, though it could optionally mention potential limitations like default region behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents q, page, and region. The description adds minimal extra meaning: it implies q is a query string and that 'page-based pagination' relates to the page parameter, but it does not enhance understanding of the parameters beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb+resource construction: 'Search DuckDuckGo video results.' It clearly distinguishes this tool from sibling tools like duckduckgo_image, duckduckgo_news, and google_videos by specifying video results. The expected output fields (title, URL, duration, etc.) further clarify the tool's purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states the primary use case ('Search DuckDuckGo video results') and clarifies that results are normalized video data, implying when this tool is appropriate. However, it does not explicitly mention exclusions or alternatives (e.g., 'for web search use duckduckgo_search'), so it lacks the explicit alternative guidance that would merit a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the full burden. It states the tool is credential-free and read-only, which is good, but it does not disclose potential error behavior, rate limits, or what happens with invalid event IDs. The description is adequate but lacks deeper behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loading the purpose in the first sentence, and provides essential information in a few sentences without unnecessary details. Every sentence serves a clear purpose (purpose, data source, parameter guidance, event ID source).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema, the description explains the return content (matchup, betting odds, boxscore stat totals). It also explains how to obtain the required event ID. While it could be more explicit about the output structure, it provides sufficient context for a tool with three straightforward parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% description coverage for all three parameters. The description adds meaningful context beyond the schema by listing the enum values for sport and league and noting that league must be valid for the chosen sport and that event ID comes from the scoreboard endpoint. This extra guidance helps the agent select correct values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a single game's summary including matchup, betting odds, and boxscore stat totals. It specifies the data source and effectively distinguishes itself from sibling tools like espn_scoreboard (which returns multiple games) by focusing on one game.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on how to get the event ID (from scoreboard endpoint) and explains the enum constraints for sport and league. It implicitly suggests when to use this tool versus the scoreboard or other endpoints, though it does not explicitly list when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly states that it 'Fetches public data,' indicating a read-only operation, and notes the source ('About tab') for contact details. It does not discuss rate limits or error cases, but for a simple public-data lookup this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, consisting of two sentences. The primary action is front-loaded in the first word, and every subsequent clause adds valuable detail about input or returned fields, with no redundant wording.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter tool with no output schema, the description adequately covers the returned data and input formats. It enumerates the data fields and indicates the data source, but does not mention potential edge cases (e.g., missing fields or invalid IDs), which is a minor gap for an otherwise complete description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% coverage for the single parameter, describing the accepted forms (vanity name, handle, profile.php id, or full URL). The description restates the same input options without adding new semantic meaning, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get Facebook page details.' It uses a specific verb with a specific resource, and enumerates the data fields returned (name, follower counts, category, contact details), making it easy to distinguish from sibling tools like facebook_group or facebook_marketplace.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context about when to use this tool—whenever a Facebook Page's public details are needed. It explains the accepted input formats (page ID, vanity name, or URL), though it does not explicitly mention alternatives or exclusions, which keeps it just short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations were provided, so the description carries the full burden. It discloses that the data is public, sourced from server-rendered search pages via a real browser-rendering backend, which signals potential latency or scraping-based behavior. It also lists the exact fields returned in normalized summaries, providing transparency about response content, though it does not mention rate limits or failure modes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: the first states the action, the second details the return fields and data source. It is front-loaded and every sentence adds value without redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool with two parameters and no output schema, the description is largely complete: it covers purpose, parameters (implicitly), return content, and data source. It could be slightly more explicit about pagination behavior or browser-rendering caveats, but the schema already documents the page parameter. Overall, it covers the essentials.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes both parameters with 100% coverage (q as free-text keyword, page as 1-based result page defaulting to 1). The description's 'free-text keyword' matches the schema, adding no new semantic detail beyond what the schema provides. Per baseline, 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description opens with 'Search Fiverr gigs' – a specific verb + resource. It further specifies free-text keyword search, public listings, and a list of returned fields, clearly distinguishing it from the fiverr_gig and fiverr_seller tools in the sibling set.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description conveys a clear use case: search Fiverr's public gig listings by keyword, returning summary data. It does not explicitly compare to alternatives like fiverr_gig or fiverr_seller, but the context is evident from the tool name and description. No exclusions or when-not-to-use guidance is given, so it's clear but incomplete on alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses sorting by like count, returned fields, and credential-free access. It does not mention pagination or error behavior, but covers key behavioral traits beyond minimal info.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two efficient sentences: first states purpose, second adds details on fields and sorting. No wasted words, front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and full parameter schema coverage, the description adequately explains what the tool returns and its behavior. Lacks error handling or rate limit info, but sufficient for a simple read tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description restates parameter details (id, limit with default/max). It adds no new parameter meaning beyond schema, but the mention of returned fields helps understand output context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get a Goodreads book's featured reviews' with specific details on returned fields and sorting. It distinguishes from sibling tools (e.g., goodreads_book, goodreads_author_books) by focusing on featured reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (for a specific book's featured reviews) and mentions 'Credential-free' which contrasts with tools that may require auth. However, it does not explicitly state when not to use or list alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the data source ('Parsed from careers.google.com's server-rendered job detail page') and implies a read-only operation via 'Returns.' However, it does not mention potential issues like scraping limitations, latency, or failure modes. For a simple read tool this is adequate but not rich, earning a mid-range score.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise sentences, front-loaded with the primary purpose. Each sentence adds necessary detail: what it does, how to identify the posting, and the source page. No wasted words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one parameter and no output schema, the description is mostly complete. It states the return (a posting), the identifier, and the source. It does not detail the fields in the returned posting, but given the simplicity and the absence of an output schema, this is a minor gap. The description adequately covers the essential context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes `id` as 'Numeric Google job id' (100% coverage), so the baseline is 3. The description adds value by linking the parameter to the search result (`the `id` field returned by search`), clarifying which ID to use and reinforcing the parameter's origin. This semantic enrichment justifies a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states what the tool does: 'Returns one Google Careers posting by its numeric job id.' It specifies the resource (Google Careers posting), the verb (returns), and the identifier (id from search), which distinguishes it from search tools like google_jobs_search. The source ('Parsed from careers.google.com's server-rendered job detail page') adds further specificity, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context on when to use this tool: it takes the `id` field returned by a search, implying it should be used after google_jobs_search. However, it does not explicitly state when not to use it or name alternative tools, so it stops short of a full 5. The mention of 'single posting' and the id origin provides usable guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It reveals that the tool scrapes server-rendered search page data and notes that page size is fixed at 20 results, which adds context beyond the basic 'search' operation. It does not mention rate limits or error behavior, but for a search tool this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, each serving a purpose: identifying the tool, explaining the data source, and stating result contents and pagination. There is no wasted wording, and it is appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description provides a solid overview of what the tool does and what results contain (description, responsibilities, qualifications). It does not fully describe return structure (e.g., metadata, total results) or the effect of the location filter, but given the absence of an output schema and the low-to-moderate complexity, this is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents all three parameters with 100% coverage. The description adds value by specifying that page size is fixed at 20, which clarifies how the 'page' parameter works. It does not elaborate on 'q' or 'location' beyond schema definitions, but the extra detail on pagination semantics earns a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a search tool for Google's public careers site, with a specific verb ('Searches') and resource ('careers.google.com'). It also distinguishes itself from job detail tools by noting that each result includes description, responsibilities, and qualifications inline.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for searching Google careers jobs but does not explicitly state when to use this tool versus alternatives like google_jobs or google_jobs_job. No exclusions or alternative recommendations are provided, so guidance is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, but the description covers behavior: it returns normalized results parsed from the public page, has default locale, and can return 503 for challenge pages. This gives useful insight beyond structured fields.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each serving a clear purpose: purpose, defaults, error handling. No redundant words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description specifies return fields and an error scenario, but could mention other error types or rate limits for a scraping-based tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds default values (country=us, lang=en) and mentions clamping for count (1-50), which adds meaning beyond schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search Google News' and specifies the returned fields (title, source, link, age), distinguishing it from siblings like bing_news or google_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions locale defaults and a potential 503 error, but provides no explicit guidance on when to use this tool versus alternatives such as bing_news or brave_news.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It clearly states what the tool returns (ratings-and-reviews breakdown by device) and the default parameters. However, it does not explicitly confirm it is a read-only operation or describe any potential quirks, such as behavior for unavailable devices or locale-specific variations. The description is adequate but not deeply transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core action ('Get Google Play ratings by device'), followed by the return shape and defaults. Every sentence contributes information without redundancy or unnecessary detail. It is highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description explains the return value shape (one entry each for phone, tablet, and Chromebook) and states default parameters. For a simple read-only tool with three well-documented parameters, this is sufficient. It does not specify exact fields within each entry (e.g., rating values, counts), but the description covers the essential context for invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with all parameters having basic descriptions (e.g., 'Two-letter language code'), so the baseline is 3. The description adds meaningful value by specifying default values for country and lang (`country=us`, `lang=en`) and clarifying that app_id refers to the Google Play package name, which is not fully clear from the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource ('Get Google Play ratings by device') and clearly distinguishes the tool from siblings like googleplay_reviews by explaining it returns the ratings-and-reviews breakdown under device tabs (phone, tablet, Chromebook). It is unambiguous and action-oriented.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies appropriate usage context by stating it returns the device-specific ratings breakdown and provides defaults for country and language. It does not explicitly name alternatives or exclusions, but the clarity of purpose makes it clear when this tool should be selected over the many other Google Play sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full disclosure responsibility. It describes a read operation (returns data) with no side effects, but omits information about authentication, rate limits, or potential errors. The description is adequate but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two short, information-dense sentences. It is front-loaded with the tool's purpose and contains no redundant or irrelevant content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and absence of an output schema, the description covers the essential aspects: input constraints and expected output type. However, it could briefly mention the output structure or common use cases to enhance completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (both parameters have descriptions). The description adds a critical constraint not in the schema: 'Pass exactly one of `id` or `url`,' which clarifies mutual exclusivity and improves usability.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns 'normalized public IMDb company-credit sections for a title,' specifying the verb ('returns'), resource ('company-credit sections'), and scope ('for a title'). This distinguishes it from siblings like 'imdb_title_credits' (broader credits) and 'imdb_title' (general info).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly instructs to 'pass exactly one of `id` or `url`,' providing clear usage direction. However, it does not mention when to choose this tool over siblings or exclude other scenarios, so it lacks explicit when/not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It indicates a read operation but lacks details on side effects, auth requirements, or rate limits. Still, it adequately conveys the basic behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff. First sentence states purpose, second gives usage instruction. Perfectly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description mentions returns 'normalized public IMDb keyword rows', giving a sense of output. Could benefit from slightly more detail on what keyword rows contain, but sufficient for a simple retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with basic descriptions. The description adds value by explicitly stating the mutual exclusivity constraint ('exactly one'), which is not in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool returns normalized public IMDb keyword rows for a title, which is a specific and distinct functionality among the many IMDb sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states the constraint 'Pass exactly one of `id` or `url`', providing clear usage guidance. However, no comparison with alternative tools or when-not-to-use scenarios is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries the burden. It mentions normalization, limit defaults and clamping, but lacks details on pagination, rate limits, or auth requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences: purpose, output description, usage rule. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequately covers key aspects for a simple review list tool given no output schema, but could mention return fields or ordering.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameters, but description adds the crucial constraint 'Pass exactly one of id or url', which is not reflected in schema's optional fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it returns IMDb title user reviews as normalized rows. Distinguishes from sibling tools like imdb_title or imdb_title_credits by focusing on reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit instruction to pass exactly one of id or url, but does not contrast with sibling tools or specify when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states it returns 'normalized public IMDb technical specifications', implying read-only and public access, but does not disclose rate limits, authentication needs, or error behavior. Adequate for a simple retrieval tool but could be more transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose and followed by usage instruction. Every sentence is necessary and no filler. Excellent conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with two parameters and no output schema, the description covers the key aspects: what it returns (list of specs), how to call it (pass one identifier), and the data source (IMDb title). It could mention that the output is a JSON object to increase completeness, but overall sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with 'id' and 'url' already described. The description adds value by clarifying that exactly one parameter must be passed, which is not obvious from the schema (neither is required). This guidance enhances usability.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns IMDb technical specifications such as runtime, sound mix, color, and aspect ratio. It distinguishes itself from sibling tools like imdb_title or imdb_title_awards by focusing on technical specs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Pass exactly one of `id` or `url`', providing a clear usage constraint. However, it does not elaborate on when to use this tool versus alternatives beyond the implicit purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It meaningfully states the tool is metadata-only, does not return products, and that the data is public from Instacart's storefront navigation. This goes beyond a simple 'get' by setting clear expectations, though it does not address authentication, rate limits, or error behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured in four sentences, each contributing unique value: the action, the return structure, exclusions, and data source. It is front-loaded with the verb phrase and contains no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple taxonomy tool with no output schema, the description adequately covers the return value (two-level taxonomy), the scope (metadata only), and the source (public Instacart storefront). It is complete enough for an agent to understand what it will receive, though a more explicit description of the response format (e.g., array of departments) would make it fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% coverage with descriptive parameter explanations (e.g., shop_id is 'Store's opaque shop id, from GET /instacart/stores'). The description does not add additional parameter-level detail beyond what the schema already contains, so it meets the baseline without enhancing it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets the Instacart store department taxonomy, specifies it returns a two-level taxonomy (department and subcategory), and provides examples like Produce and Dairy & Eggs. It explicitly differentiates from sibling tools by noting it is 'Metadata only, does not return products,' distinguishing it from instacart_search and instacart_item.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a store's departmental structure is needed and effectively excludes product-related use cases with 'does not return products.' However, it does not explicitly name alternative tools such as instacart_search or instacart_item, so it provides strong context but stops short of explicit when-not/alternative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that unknown orgs return an empty board (not a 404), that it is credential-free and public ATS JSON, and that inline detail includes description and compensation when requested. These are key behaviors beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: the first states the main purpose, the second elaborates on details, parameter behavior, and edge case (unknown org). No unnecessary words, all information is relevant and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but the description explains that output includes inline detail (description, compensation) and is JSON. It covers input behavior and edge cases. For a simple two-parameter tool, this is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds value by explaining that 'org' is the Ashby slug from the careers URL, and that 'include_compensation=true' enables compensation details. This clarifies the parameters beyond the bare schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List an organization's Ashby job board' with verb 'list' and resource 'job board'. It specifies inline detail and optional compensation inclusion. The org parameter is explicitly defined as 'Ashby slug from its careers URL', distinguishing it from sibling tools like jobs_greenhouse_board.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates this is for Ashby job boards and mentions credential-free access, but does not explicitly state when to use this tool versus other job board tools in the sibling list (e.g., jobs_greenhouse_board, jobs_lever_posting). No when-not guidance or alternatives provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It usefully notes fallback behavior ('Tries the newer PCSX detail first, falling back to the legacy SmartApply detail generation') and that it's 'Credential-free public ATS JSON'. However, does not detail rate limits, response size, or any potential side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences: purpose, parameter guidance, behavioral notes. No fluff, front-loaded with the key action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, parameter sources, fallback behavior, and auth status. Lacks details on error handling or response format, but the tool is simple and the description is reasonable for its complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds context: 'id is the position id from a board listing; tenant/domain as in the board endpoint' clarifies the source and usage of each parameter, going beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get a single Eightfold position' and specifies it returns 'full HTML/text description'. Among siblings like 'jobs_eightfold_board' (listing) and other job-specific tools, this tool is uniquely for retrieving a single position detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explains that 'id is the position id from a board listing; tenant/domain as in the board endpoint', implying prior knowledge from a board listing. However, does not explicitly state when to use this tool versus alternatives like 'jobs_eightfold_board' or other job detail tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that the tool is credential-free, public, returns JSON with full descriptions, paginated via page/limit, and clarifies the domain distinction. This is comprehensive behavioral information.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, no redundant information. Every sentence adds value: purpose, domain clarification, pagination, and public credential-free nature.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a listing tool with 5 parameters and no output schema, the description covers purpose, parameters, pagination, and return format (jobs with full description inline). It could mention error handling or rate limits, but the schema's max 50 limit is sufficient. Overall, very complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds context for domain (careers domain vs employee portal) and implies pagination behavior, but does not add significant new semantics beyond the schema's parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List an iCIMS tenant's job board' and elaborates with specifics about the public nature, domain format, pagination, and inline descriptions. It distinguishes itself from sibling tools like jobs_icims_job by focusing on listing multiple jobs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description tells when to use this tool (to list public iCIMS jobs) and clarifies the domain parameter's meaning. It contrasts with the employee portal subdomain. However, it does not explicitly say when not to use it or mention alternatives among the many job board siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses the feed is public and credential-free, but does not mention rate limits, pagination, or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with purpose, no wasted words. Efficiently conveys key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers main points: purpose, parameters, credential-free nature. Lacks mention of output shape details or error scenarios, but sufficient for a simple listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. Description adds value by explaining company subdomain format and that parameters are filters, exceeding the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists a company's Personio job board, with specifics about normalization and filters. It uniquely identifies the resource among sibling job board tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains it's for Personio's public ATS feed and implies credential-free access, but lacks explicit comparison to other job board tools in the sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description discloses key behaviors: credential-free access, paging via limit/offset, and that job postings contain only brief descriptions (full details are HTML). No hidden behaviors or contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four sentences, front-loaded with the main action, and every sentence provides necessary information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and 5 parameters, the description covers the main purpose, parameter source, paging, and a key limitation (brief descriptions). It lacks output format details but is sufficient for a listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, baseline is 3. The description adds value by explaining that tenant and board come from the careers URL, providing concrete construction guidance beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists a UKG Pro Recruiting tenant's job board, specifying it returns public opportunities. It distinguishes from sibling tools by naming the specific platform (UKG/UltiPro) and provides the URL structure.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for UKG job boards and mentions credential-free public access, but does not explicitly compare to alternatives or state when not to use this tool among numerous job board siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the tool is credential-free and returns public ATS JSON with full HTML/text description. For a simple read operation, this provides sufficient behavioral insight without contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of three concise sentences that front-load the core purpose. Every sentence provides necessary information without redundancy or fluff, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 parameters, no output schema, no annotations), the description covers the essential aspects: what it does, what it returns, how to identify the target posting, and authentication requirements. It leaves little ambiguity for a typical use case.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema coverage is 100%, so the baseline is 3. The description adds value by clarifying that the 'id' parameter is a posting shortcode obtained from a listing, which is not explicit in the schema's brief description. This enhances understanding beyond the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Get a single Workable posting' and distinguishes it from sibling 'jobs_workable_postings' (plural) by focusing on a single posting. It specifies the return format (full HTML/text description) and resource, making the purpose crystal clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by noting that the id is a posting shortcode from a listing, suggesting it should be used after obtaining a listing from a sibling tool like jobs_workable_postings. However, it does not explicitly state when to use this tool versus alternatives or when not to use it, leaving room for ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses key behavioral traits: normalization to a shared shape, fetching detail per job via a single-posting endpoint, and being credential-free. It does not mention pagination, rate limits, or potential destructive actions, but given no annotations, it provides useful behavioral context beyond the bare minimum.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at 4 sentences, front-loading the core purpose, then explaining normalization, filters, company parameter, and detail fetching. Every sentence adds value without redundancy or unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description covers key aspects: input parameters, normalization, detail fetching, and credential-free access. However, it lacks mention of pagination or explicit differentiation from the singular 'jobs_workable_posting' sibling, which would improve completeness for a listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage (baseline 3), the description adds meaningful context, especially for the 'company' parameter by explaining it is the Workable account slug from the careers URL. It also clarifies that filters are optional and groups them, adding value beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list' and the resource 'Workable postings', specifies normalization to a shared Job shape, and mentions optional filters. It effectively distinguishes this tool from siblings by targeting Workable specifically, which is evident from the sibling list containing other job board tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for Workable postings but does not explicitly guide when to use this tool over alternatives like 'jobs_workable_posting' (singular) or other job board tools. There is no mention of when not to use it or specific scenarios that favor other tools, leaving the agent with implied rather than explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It reveals the tool is credential-free and returns public ATS JSON, but does not disclose rate limits, error handling, or empty result behavior. Adequate but limited.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Four compact sentences with no wasted words. The main purpose is stated first, followed by essential details about paging and parameter sources.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, paging, parameter sourcing, and public nature. Lacks description of the return format beyond 'public ATS JSON', which could be improved. Without an output schema, the agent would benefit from knowing the structure of a job posting item.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds meaningful context by explaining how tenant, datacenter, and site map to the careers URL and providing an example. This goes beyond the schema's individual parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it lists a Workday tenant's job board, specifies public Workday (CXS) postings, and mentions paging via limit/offset. Distinguishes itself from sibling tools like jobs_workday_job by focusing on board-level listing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context: the tool lists public postings and requires tenant, datacenter, and site from the careers URL. Does not explicitly state when not to use it or list alternatives, but the purpose is sufficiently specific.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description is the sole source of behavioral info. It states 'Credential-free public ATS JSON' which is helpful, but does not mention error handling, rate limits, or idempotency. The 'Get' verb implies read-only, but more transparency would be better.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with the core purpose in the first sentence and additional clarifications afterward. No unnecessary words; each phrase adds meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description mentions key return fields. It explains the source of all parameters and notes credential-free access. Missing details on error responses or potential limitations, but adequate for the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds extra meaning by explaining the source of path (externalPath from board listing) and that tenant/datacenter/site mirror the board endpoint, which adds value beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it 'Get a single Workday job' and specifies the return fields (description, location, req id). It distinguishes from sibling tools like jobs_workday_board by indicating this is for full detail of a single posting.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains that path comes from a board listing and tenant/datacenter/site are as in the board endpoint, providing context for parameter values. It implicitly suggests using after a board listing, but does not explicitly list when not to use or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description explains it returns popular titles filtered by parameters and lists accepted values for type and monetization_types. It does not disclose rate limits, pagination, or caching behavior, leaving a moderate gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: one stating purpose and filters, and one providing a practical example. No filler, every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 10 parameters and no output schema, the description covers the main functionality and a use case. It lacks details on return format or how 'popular' is determined, but the example helps compensate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers all 10 parameters with descriptions (100% coverage). The description adds value by explaining the combine use case for providers and production_countries, and explicitly listing accepted values for type and monetization_types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it discovers JustWatch titles, returning popular movies and shows filtered by optional criteria. It specifies the resource and action, and distinguishes from siblings like justwatch_search or justwatch_popular by emphasizing filtering and popularity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides a concrete example of combining providers with production_countries to build charts. However, it does not explicitly state when not to use this tool versus siblings like justwatch_search, which might be better for direct title lookups.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, but description discloses it returns 'public exchange standard hours and maintenance windows' from 'Kalshi market-data JSON'. Adequate transparency for a read-only, no-param tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff. Front-loaded with name and purpose. Highly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description specifies what data is returned (hours and maintenance windows). Sufficient for a simple lookup tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters. Baseline 4 applies as description adds no parameter info, but none needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it returns Kalshi exchange schedule (standard hours and maintenance windows). Distinguishes from sibling kalshi_exchange_status by specifying 'schedule' vs 'status'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs siblings like kalshi_exchange_status. Implied by purpose but not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral disclosure burden. It explicitly documents the returned fields (address, phone, weekly hours, distance, store badges/services) and discloses the no-results edge case as a 'genuine empty list rather than an error,' which prevents an agent from misinterpreting a valid empty response as failure. It does not cover rate limits, geocoding failure behavior, or distance unit, but those are minor for a read-only search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no waste: the action and input format come first, followed by the return fields and an edge-case note. Every sentence earns its place and the most critical information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter search tool with no output schema, the description covers the input format, output fields, and the degenerate no-result case, which is enough for an agent to call and interpret this tool correctly. Minor gaps — what the badge/service values are and what distance units get returned — keep it from a perfect score.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already has 100% description coverage, defining 'search' as a free-text location (city/state, zip code, or address). The description adds only the 'nearby' qualifier, which is a marginal increment over the schema baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description leads with a specific verb and resource, 'Find nearby Kohl's store locations,' which unambiguously states what the tool does. It differentiates the tool from kohls_category, kohls_product_reviews, and kohls_suggest by clarifying the resource is physical store locations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly establishes the usage scenario: search for physical Kohl's locations near a free-text city/state, zip code, or address. It does not explicitly name exclusions or alternatives, but the 'Find nearby ... physical store locations' framing gives a clear context for when to using a.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full disclosure burden. It goes beyond the obvious by stating there is no product data, clarifying the response shape, and warning that a nonsense query generates a genuine empty list rather than an error — which prevents an agent from misreading an empty result as a failure. It omits details like limits on suggestion count, but for a small one-parameter tool the core behavioral contract is well covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences, front-loaded with purpose, followed by output shape and an edge-case note; every sentence earns its place. A minor redundancy (the phrase 'search/search-box typeahead' appears in two places) keeps it from a 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter tool with no output schema, this description explains everything the agent needs: what input to supply, what the result contains, what it does not contain, and what happens on a degenerate input. Nothing essential is missing for selecting and correctly invoking the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: the query parameter is documented as 'Partial search text'. The prose description adds little beyond the same keyword, 'partial', and does not add constraints such as maximum length, encoding, or examples. Baseline 3 applies because the schema already carries the parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: returns Kohl's own search-box typeahead result for a partial query, and describes the output shape (flat list of suggested search phrases, no product data). It is self-distinguishing from kohls_category, kohls_product_reviews, and kohls_stores without needing to inspect any other definition.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Clear context is provided: use it when you have a partial query and want typeahead suggestions, and the explicit 'no product data' constraint tells the agent when not to use it. However, no alternative sibling tool is named, so the when-not guidance is implicit rather than an explicit pointer to a replacement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that the tool is credential-free and public, and specifies the output includes counts and percentages for each half-star bucket. Without annotations, it covers key behavioral aspects for a read operation, though it omits details like error handling or data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three short sentences, each providing essential information: purpose, output format, and access context. No redundant or unnecessary content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with one parameter and no output schema, the description explains the output structure well (star-range buckets, counts, percentages). It could be more complete by mentioning how to obtain the slug or potential error responses, but overall it sufficiently covers the tool's functionality.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'slug' is described in the schema as 'Letterboxd film slug', and the description's phrase 'Get a Letterboxd film's rating distribution' implies the slug identifies the film. With 100% schema coverage, the description adds no additional semantic value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Get' and identifies the resource as 'rating distribution', detailing the star-rating buckets and output structure (counts and percentages). This clearly distinguishes it from sibling tools that provide film details, reviews, or similar films.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states the tool retrieves rating distribution, implying usage when that specific data is needed. It mentions 'Credential-free public Letterboxd data', indicating no auth is required. However, it does not explicitly advise when not to use it or name alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses that the data is public, requires no credentials, and returns stats like films watched and follower counts. This is sufficient for a simple read operation, though it does not mention error handling or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences: the first states the purpose and return data, the second clarifies privacy and credential requirements. Every sentence adds value, is front-loaded, and contains no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has a single parameter, no output schema, and no annotations, the description adequately explains what the tool returns (specific stats) and its public nature. It is complete enough for an agent to decide when to use this tool, though it lacks details on potential pagination or data limits.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage (the 'username' parameter is described as 'Letterboxd username'). The description adds some context by implying the username is for a member, but does not significantly enhance the parameter's meaning beyond what the schema already provides. According to guidelines, baseline is 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get a Letterboxd member's public profile stats.' It specifies the resource (Letterboxd member), the verb (Get), and lists the data returned (films watched, lists, following/followers). This distinguishes it from siblings like letterboxd_film or letterboxd_person, which target different entities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides usage context by stating that data is public and credential-free, indicating when to use (for public profile stats). It does not explicitly exclude scenarios or name alternative tools, but the sibling context makes the distinction clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It explicitly describes a read-only retrieval operation ('Get', 'Returns') and gives a detailed inventory of the returned attributes, including sale detection and per-color variant pricing. It does not cover potential limitations like rate limiting or data freshness, but for a read-style lookup tool the behavioral surface is well exposed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core action, then a compact list of return fields, then a parameter note. Every element earns its place; the phrasing is direct and avoids filler. The repetition of 'full detail' is minor and does not detract from the clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, so the description compensates by listing all major return data categories. It also explains the origin of the required productId. The description is sufficient for an agent to decide when to call the tool and how to supply the parameter, though it could optionally mention response structure or error behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes productId as a 'Numeric Macy's product id, from a product page's ?ID= query parameter,' which is 100% schema description coverage. The description repeats this same guidance, so it adds little beyond the schema, but it is consistent and confirms the source of the identifier. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Get a Macy's product's full detail,' and then enumerates the exact data fields returned (name, brand, description, pricing with sale detection, availability, images, rating, color variants). This makes the tool's purpose immediately distinguishable from sibling tools like macys_product_reviews and macys_suggest, even without explicitly naming them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes clear this is the tool to use when complete product details are needed, and that the caller must already have a Macy's product ID from a product page. It does not explicitly state when not to use it or name alternatives, but the product-detail context is sufficiently unambiguous given the sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full behavioral burden and does valuable work: it discloses the output shape (flat list of phrases), bounds the result ('no product data'), and pre-empts a common failure interpretation by stating unmatched partial queries return a normal empty result rather than an error. It stops short of richer context like rate limits, result count, or auth requirements, so a perfect score isn't warranted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three tightly written sentences, each earning its place: purpose, output shape and boundary, then a valuable edge-case note. No fluff, no repetition, and the key scoping terms ('partial query', 'flat list', 'no product data') are front-loaded into the first sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter, no-output-schema tool, the description is complete: it states what is returned, what is NOT returned, and how the tool behaves in the edge case of no matches. The only minor addition would be a concrete example of input/output, which isn't necessary for this simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% – the 'query' parameter is documented with the type string and description 'Partial search query', so the baseline is 3. The tool description reinforces that the query is partial/typeahead input but adds no new semantic detail beyond what the schema already communicates.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb and resource ('Get Macy's search-box suggestions'), and specifies the exact scope: typeahead suggestions for a partial query, returned as a flat list of phrases. The explicit statement 'no product data' distinguishes it from sibling product tools like macys_product and other retailers' suggest tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Clear usage context: this is for partial-query typeahead suggestions, not for retrieving product details, and the 'no product data' note implies it should not be chosen when product data is required. It gives a natural condition for selection (partial query) and even describes expected behavior for unmatched queries, though it names no explicit alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the transparency burden. It discloses credential-free public data, an anonymous login-free session, and the Mercari mobile-app API source, plus a normalized output shape. It does not mention failure modes or rate limits, but for a simple read operation this is strong coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no filler. The first sentence states the action and enumerates useful output fields; the second adds essential access context. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-id read tool with no output schema, this description is quite complete: it lists the main return fields, notes normalization, and explains access requirements. It omits details like error behavior and data freshness, but these are not critical for tool selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%: the single 'id' parameter is already described as 'Mercari item id, e.g. from a search result's id field.' The tool description adds no new parameter-level meaning beyond this, so it meets the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a specific verb and resource: 'Get Mercari item detail.' It then enumerates the exact returned content (description, photos, price, condition, category, hashtags, shipping origin state, similar items), making it clearly distinct from sibling search tools like mercari_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage after obtaining an item id, and the schema's 'e.g. from a search result's id field' reinforces that context. However, it does not explicitly name alternatives or state when not to use this tool, so it stops short of fully explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses that the tool returns paginated data, lists the fields returned, and states it is credential-free public data. It does not mention rate limits or potential destructive effects, but the read-only nature is implied. The transparency is good but could be improved with rate limits or data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences: the first states the purpose and return fields, the second notes the credential-free nature. It is front-loaded, no wasted words, and efficiently conveys essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool with 4 parameters all documented in the schema, the description covers the purpose, return fields, and auth requirements. It does not explain the return format (e.g., array) but that is typical. The completeness is adequate for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with all parameters described (page, slug, sort, per_page). The description adds overall context (critic reviews, paginated, returned fields) but does not elaborate on individual parameters beyond what the schema already provides. The baseline is 3 for high schema coverage, and the description adds marginal value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists Metacritic game critic reviews, specifying it returns paginated professional/publication reviews with fields like publication, score, quote, author, platform, and source URL. It distinguishes from the sibling tool 'metacritic_game_user_reviews' implicitly by focusing on critic reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description specifies the tool is for critic reviews and that it is credential-free, implying it can be used without authentication. However, it does not explicitly contrast with alternatives like metacritic_game_user_reviews or metacritic_game, but the sibling tool names provide context. No explicit when-not-to-use guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description notes it is credential-free and returns normalized rows, indicating a read-only, public operation. It does not mention the max limit or any pagination details, which would enhance transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences: the first explains the tool's purpose, and the second lists the allowed slugs. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains the resource and action adequately given low complexity. It lacks details on return format (no output schema), but 'normalized rows' gives some context. The list of slugs is a strong hint for parameter selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both 'limit' and 'slug'. The description adds value by listing the possible slug values, which is not in the schema. This helps the agent select valid inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized Metaculus question rows from a public category feed. It lists allowed category slugs, making the resource and action specific. This distinguishes it from sibling tools like metaculus_question or metaculus_questions, which have different scopes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by listing allowed slugs and stating it's from a public feed. However, it does not explicitly mention when to use this tool over alternatives (e.g., metaculus_questions for all questions) or exclude cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the transparency burden. It discloses the return grouping and the accepted type enum values, which is helpful. However, it doesn't detail response format, error handling, or edge cases like invalid season values. This is acceptable for a simple read tool but not richly transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loaded with the purpose, and contains no filler. Every sentence adds value: the first states the function, the second details the return grouping and type options.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with only two optional parameters and no output schema. The description explains the core output (standings grouped by division) and type options, which is sufficient for an agent to select and invoke it. It could mention whether standings include win-loss records, but this is not critical for basic use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for both parameters, but the description adds the enum values for the 'type' parameter, which is crucial for correct invocation. This goes beyond the schema's generic 'Standings type' and earns a score above the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb and resource: 'Get MLB standings.' It also specifies the return structure (AL and NL standings grouped by division), distinguishing it from sibling tools like espn_standings or sofascore_standings by its MLB-specific scope and grouping detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: when you need MLB standings. It provides clear context about what the tool returns but does not explicitly mention alternatives or when not to use it. This aligns with 'clear context, no exclusions,' so a 4 is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of explaining behavior. It discloses that the tool returns a flat list of suggested search phrases, not product data, and that suggestions mirror Nike's own Top Suggestions. This is meaningful behavioral context. It does not mention rate limits, authentication, or empty-result behavior, but for a read-only, simple suggestion tool this is a reasonable disclosure level.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with zero filler. It front-loads the exact action and resource, then provides the crucial scoping behavior—same Top Suggestions list, no product data. Every phrase contributes to helping the agent understand what the tool does and what it returns.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one parameter, no annotations, and no output schema, the description is nearly complete: it explains what the return looks like ('a flat list of suggested search phrases'), how the suggestions relate to Nike's UI, and what is absent ('no product data'). It lacks an explicit return-item format or example, but this is a simple suggestion tool and the description provides enough to call it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes the only parameter, 'query,' with 'Partial search query' at 100% coverage. The description reinforces this by saying 'for a partial query' and phrases the tool as typeahead, but it does not add extra meaning such as minimum length, formatting, or examples. This matches the baseline score for full schema-documentation coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Get Nike search-box suggestions,' and further specifies it returns typeahead suggestions for a partial query—the same 'Top Suggestions' list as Nike's search box. It explicitly states 'no product data,' which clearly distinguishes it from nike_search and other product-focused tools without needing to inspect sibling schemas.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context on when to use this tool: when you need Nike's search-box suggestions/typeahead for a partial query rather than full search results or product data. It does not explicitly name alternative tools like nike_search or say 'use nike_search for product results,' but the 'no product data' exclusion strongly implies the boundary. This is clear context without explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It discloses the 'Credential-free' nature, the real-time aspect of availability, and specifies the returned data categories. It does not discuss error behaviors or side effects, but for a read-only retrieval tool, this is reasonably transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three short, front-loaded sentences. The first states the primary purpose, the second details the return contents, and the third adds the credential-free trait. No wasteful words; every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description properly explains the return values (profile fields and timeslots). It provides enough context for an AI agent to select and invoke the tool, including defaults and required restaurant_id. Minor gaps like error handling do not undermine its completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description mentions 'given date/time and party size' but adds no format or semantic details beyond the schema's RFC3339 and default values. The restaurant_id is only referenced implicitly via the resource name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Get an OpenTable restaurant's profile and live availability', which is a specific verb+resource statement. It enumerates the returned profile fields (location, cuisines, hours, price band, review summary) and distinguishes itself from sibling tools like opentable_restaurant_menus and opentable_restaurant_reviews by its availability focus.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use this tool: when you need a restaurant's profile and real-time booking slots. It does not explicitly name alternative tools for menus or reviews, but the content makes the use case evident. There are no exclusion criteria stated, so it earns a 4 rather than 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden. It discloses that no credentials are needed and states the return content (sections, items, prices). It does not mention potential failure modes or that it is a read-only operation, but 'Get' makes that apparent. Adequate for a simple retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary purpose, and every phrase adds value. No redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter read tool with no output schema and no annotations, the description is nearly complete. It tells what is returned and that it's credential-free. It could mention how to obtain the restaurant_id, but that is likely discoverable elsewhere, so minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already has 100% coverage with 'OpenTable restaurant id'. The description adds no further parameter details (e.g., where to find the ID or its format). Baseline 3 is appropriate because the schema fully documents the single parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and the specific resource ('OpenTable restaurant's menus'), and enumerates returns ('sections, items, prices'). It distinguishes itself from sibling tools like opentable_restaurant (restaurant details) and opentable_restaurant_reviews (reviews).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use it: whenever you need an OpenTable restaurant's menus. It also notes 'Credential-free', which is a useful access guideline. It does not explicitly name alternatives, but the scope is clear enough that an agent can infer this is for menu data only.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the transparency burden. It discloses that the data is public and sourced from Pinterest's own board pages, and it describes the return shape (metadata plus a page of pins), implying a read-only operation. It does not cover rate limits or error behavior, preventing a higher score.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary purpose, and contains no filler. Every sentence adds useful information: what is returned and that the data is public from Pinterest's board pages.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description reasonably covers the main output: board metadata fields plus a page of pins. It is sufficient for a low-complexity tool, though the phrase 'a page of pins' could be more explicit about pagination limits or pin field details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: both username and slug are documented in the input schema with clear descriptions. The tool description itself does not add parameter-level detail, but this is acceptable because the schema already provides full meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a specific verb and resource: 'Get a Pinterest board's detail.' It enumerates the returned metadata (name, description, cover image, pin/follower counts, owner) and pins, making the tool's scope clear and distinguishing it from sibling tools like pinterest_user_boards or pinterest_pin.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly signals use for retrieving a single board's metadata and pins. It does not explicitly name alternatives or exclusion cases, but the context is unambiguous enough for an agent to select this tool when a board's detail is needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the data is public, sourced from Pinterest's own web search, and enumerates the result fields. This is solid transparency for a read-only search tool, though it omits pagination and result limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences that front-load the verb and resource, list the return payload, and cite the data source. There is zero filler and no repetition of schema details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter search tool with no output schema, the description covers purpose, return fields, and data source adequately. It lacks detail on pagination or result limits, but this is a minor gap for a public web search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully documents the single 'query' parameter with 100% coverage and a 'Search text' description. The description's phrase 'text query' adds only minor reinforcement and does not explain query syntax or formatting, so it stays at the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with the specific verb-resource pair 'Search Pinterest pins' and lists exactly what is returned (title, description, image, board, pinner) for a text query. It clearly distinguishes this generic search tool from sibling tools like pinterest_user_pins or pinterest_pin.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies this is for text-query searches for public Pinterest pins, which is clear context. It does not explicitly name alternatives or state exclusions, but the scope is unambiguous for a simple search tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It explicitly notes that only public data is returned and that it is sourced from Pinterest's own profile pages, which conveys the read-only, non-sensitive nature of the operation. However, it does not discuss error scenarios, rate limits, or response format, which is a minor gap for a simple profile retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exceptionally concise: two sentences. The first sentence front-loads the purpose, and the second succinctly enumerates the return fields. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema), the description is largely complete. It states the purpose, the data returned, and the data source. It could be enhanced by mentioning what happens if a username is invalid or if data is unavailable, but for a public profile getter, this is a minor omission.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully describes the single parameter 'username' with 'Pinterest username', achieving 100% schema coverage. The tool description does not add further meaning or detail about the parameter itself, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb ('Get') and resource ('Pinterest user's public profile'), and enumerates the returned fields (display name, bio, website, avatar, counts). This distinguishes it from sibling tools like pinterest_user_pins or pinterest_user_boards, which focus on pins or boards rather than profile details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly indicates when to use this tool: whenever a Pinterest user's public profile data is needed. It provides clear context about what the tool returns, but does not explicitly mention alternatives or exclusion criteria. Since the purpose is unambiguous and effectively guides the agent, this earns a 4 rather than a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the behavioral disclosure burden. It does well by stating that the data is credential-free and public, that results are paginated, that next_page appears when more results exist, and that cc controls both region and currency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and information-dense with no filler. Every sentence contributes: the core operation, result content, pagination behavior, localization parameters, and the no-credential requirement are all covered efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main things an agent needs for a simple search call: required term concept, output content, pagination, localization, and that no credentials are needed. It is not missing critical behavioral details, though it could optionally state default behavior for cc and l when omitted.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description still adds meaning beyond the bare parameter definitions. It explains the relationship between page and next_page, clarifies that cc selects region and price currency, and says l selects text language.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies a specific verb-resource pair: searching the PlayStation Store by term, returning search result pages of concepts and products. It is easily distinguished from browsing, category, deal, and product-detail sibling tools without needing to open their schemas.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use it: when a term-based PlayStation Store search is needed. It gives practical usage context through pagination and region/language parameters, but it does not explicitly state when-not to use it or name alternatives such as playstation_browse or playstation_product.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for safety and behavioral disclosure. It transparently states the tool is credential-free, uses public data, sources from both server-rendered brand pages and a JSON pagination API, and explains the pagination mechanism (pass next_max_id back as max_id). It does not mention rate limits or error conditions, but for a browse-only tool this is a solid disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized at three sentences, each earning its place: the first states the core purpose, the second explains pagination, and the third details the data source and authentication-free nature. It is front-loaded with the most important information and contains no redundant filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with a simple browse-by-brand dataset, the description is reasonably complete. It covers purpose, pagination, credential-free access, and the two API sources. However, there is no output schema, and the description does not enumerate what 'normalized listings' include (e.g., price, title, image, etc.), which would help an agent set expectations about return shape. This leaves a small completeness gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with both `name` and `max_id` already well-described in the schema. The description adds only marginal value beyond this (e.g., the 'Nike' example, the 'browsing view' framing, and a restatement of the cursor behavior). It does not introduce any new parameter semantics not already present in the schema, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Browse Poshmark listings by brand'), the resource ('Poshmark listings'), and the specific scope ('by brand'), which distinguishes it from sibling tools like poshmark_search (search all listings), poshmark_category (browse by category), and poshmark_closet (browse a user's closet). The example 'Nike' and the explicit mention of 'the same browsing view as Poshmark's own brand pages' firmly anchor its purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context on when to use the tool (to browse brand-specific listings in Poshmark's own brand-page view). It also implicitly excludes auth-heavy scenarios by noting 'Credential-free public data'. However, it does not explicitly name alternative tools (e.g., use poshmark_search for keyword-based search) or provide when-not-to-use guidance, so it falls short of a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses that the data is public, credential-free, sourced from Poshmark's server-rendered page, and normalized. This is strong for a read-only tool, though it stops short of mentioning potential scraping limitations or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the core purpose, and every sentence adds value: what the tool returns, the composition of the response, and the data source/authentication context. No fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema, the description does well to enumerate the return content: full listing details, seller profile, public comments, and similar listings. It would be slightly stronger with explicit mention of error behavior or the exact response shape, but for a single-parameter detail fetcher it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema fully documents the single parameter 'id' with an explicit extraction rule from listing URLs. The description adds no further parameter detail, but since schema coverage is 100%, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Get Poshmark listing detail,' which clearly names the verb and resource. It further distinguishes this from sibling Poshmark tools by specifying the full page-level content returned, such as listing data, seller profile, comments, and similar listings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes the use case clear: retrieve detail for a specific Poshmark listing. It adds context that this is credential-free public data, implying no auth setup is needed, though it does not explicitly name alternatives like poshmark_search or poshmark_closet.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does well: it discloses that the tool is credential-free, sources data from Poshmark's server-rendered page and JSON API, and explains pagination behavior with next_max_id. This goes beyond typical read-only descriptions, though it doesn't cover rate limits or error behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: the first sentence states the core action, the second gives an example and aligns with Poshmark's own browsing experience, and the third covers pagination and data sourcing. Every sentence adds value, and it is appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (two params, no output schema), the description covers the essential context: purpose, return type, pagination, and authentication. It could be improved by detailing what the normalized listings contain, but it is sufficiently complete for an agent to understand and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%: both 'id' and 'max_id' have clear descriptions, including how to derive the id from a /trend/{slug}-{id} URL and that max_id is an opaque cursor. The description adds a small reinforcement of the max_id mechanism but does not provide substantial semantic value beyond the schema, so it lands at the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Browse') and resource ('Poshmark trend/showroom collection'), and immediately explains what it returns: a page of normalized listings. It distinguishes itself from sibling tools by referencing Poshmark's own trend pages and giving an example collection, which sets it apart from search, closet, listing, and category tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use the tool: to browse a curated trend/showroom collection, mirroring Poshmark's trend page view. It also explains pagination usage with max_id. However, it does not explicitly mention alternatives or provide when-not-to-use guidance, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden and discloses useful behavioral traits: output is 'normalized', and a specific throttling behavior (503 with Retry-After) with remediation guidance is provided. It does not mention authentication or mutation safety, but 'List' strongly implies read-only.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, with the core purpose in the first sentence and actionable error handling in the second. No wasted words, perfectly front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters (fully schema-documented) and no output schema, the description adequately covers purpose, output normalization, and error handling. It does not describe return structure, but that is acceptable without an output schema and with such a focused listing use case.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for all 5 parameters, so the baseline is 3. The description adds no extra parameter-specific semantics beyond 'from a linked domain', which is already reflected in the schema's domain description. No additional value to parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List') plus resource ('Reddit domain posts') and scoping ('from a linked domain'). This clearly distinguishes it from sibling tools like reddit_subreddit_posts and reddit_user_posts, which operate on different dimensions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies clear usage context: use this when you need posts originating from a specific domain. It does not explicitly name alternatives or exclusions, but the domain-specific scope is evident and sufficient for selection among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden for behavioral disclosure. It explicitly reveals that the upstream source returns generic fallback shelves for unrecognized ids rather than errors, and it states the output shape (normalized products with pricing, rating, image). This is highly useful for managing agent expectations beyond what a schema shows.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, well-structured, and information-dense. Each sentence contributes: what the tool returns, output content, input format, and upstream behavior. It is front-loaded with the core purpose and avoids redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter read tool with a clearly documented parameter and no output schema, the description is nearly complete. It covers the input source, the response structure, and the non-error fallback behavior. A minor omission is explicit guidance on what to do when a product truly does not exist or whether id should be treated as string vs number, though the schema covers type.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents the id parameter clearly. The description adds value by reinforcing the /ip/ URL context and noting that unrecognized ids still return fallback shelves. It does not add new syntax or formatting details, so a 3 is appropriate per the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Get a Sam's Club product's related items.' It clearly describes the output as related-item carousels from the product page, naming example shelves and the normalized product fields. This distinguishes it from sibling tools like samsclub_product, samsclub_category, and samsclub_content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description tells the agent when the tool is appropriate: when you need the related-item carousels from a Sam's Club product page. It also explains the required input format (numeric product id from /ip/ URL). It does not name sibling alternatives explicitly, but the purpose and input constraints imply the right usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description transparently states the data source (official company_tickers map), output fields (CIK, ticker, name), and that it requires no credentials. It does not cover rate limits or error behavior, but for a simple lookup, this is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, each earning its place: first states the core purpose, second adds source and credential-free nature. No unnecessary words, well front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple lookup tool with 2 parameters and no output schema, the description covers the essential: input format (ticker or name), output fields, data source, and access. Very slightly lacking in return format details, but largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining the tool uses an 'official company_tickers map' and outputs specific fields, beyond the schema's parameter descriptions. It clarifies the purpose of the query parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool resolves a ticker or company name to EDGAR companies, specifying output includes CIK, ticker, and name. It distinguishes itself from sibling SEC tools (e.g., sec_company_intelligence, sec_company_submissions) by focusing solely on basic mapping.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions 'credential-free public SEC data,' implying no authentication is needed, but does not explicitly compare or contrast with sibling tools like sec_full_text_search or sec_company_intelligence. It lacks guidance on when to use this vs. alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the disclosure burden and does a solid job: it states pagination ('Returns one page'), tells the user an unrecognized slug returns 404, and clarifies slug formatting. Combined with the schema's parameter descriptions, this gives a clear security and behavior model. It stops short of describing the response shape, but that is a minor omission for a listing tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three tightly scoped sentences: purpose, filter parity, and slug format. It front-loads the primary action and every sentence earns its place without redundant filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a category-browse tool with nine parameters, the description plus 100%-coverage schema is sufficient for invoking the tool correctly. The 404 behavior and slug construction are the most important context outside the schema, and both are present. Detailed response fields are not covered, but the no-output-schema case is handled well given the listing's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, which sets a baseline of 3. The description adds meaningful value by explaining that slug is 'the path segment after sephora.com/shop/' with the example 'makeup-cosmetics', which helps an agent construct valid input. The rest of the parameters are already well-documented in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action and resource: 'Returns one page of a Sephora category/browse listing' with concrete examples like Makeup and Skincare. It also distinguishes this browse tool from related tools like sephora_search by noting it uses the same sort and facet filters but operates on category slugs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies its use case via 'category/browse listing' and explains how to construct the required slug, but it does not explicitly state when to prefer this over /sephora/search or when not to use it. The mention of parity with sephora/search filters provides context but not explicit routing guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It reveals the fallback mechanism from vanity domain to a *.myshopify.com domain, and notes that it returns normalized metadata. This is valuable behavioral context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. The main action and key behavior are front-loaded. Every sentence adds important context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no output schema, the description provides sufficient information about input, behavior, and fallback. It could include return format details, but without an output schema, the description is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single 'url' parameter, baseline 3. The description adds meaning by explaining that the URL is a public storefront, that it resolves to normalized metadata, and describes fallback behavior. This adds value over the schema's simple 'Shopify storefront URL' description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Shopify store metadata, specifies it resolves a public storefront URL, and returns normalized metadata from credential-free storefront JSON. It also describes a fallback mechanism, making the purpose very specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions 'credential-free' and a fallback behavior, implying it is for basic store info without authentication. However, it does not explicitly state when to use this tool versus other Shopify tools (e.g., shopify_product, shopify_products), leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the transparency burden. It discloses that the data is public, sourced from SoundCloud's JSON API, sorted newest first, and includes the specific counts returned. It could additionally mention rate limits, error cases, or authentication, but 'public data' sufficiently signals the read-only and access profile.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. The main action and scope come first, followed by return fields and data source. Every sentence earns its place and the description is easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and that the input schema documents the two params, the description covers the core needed information: what is fetched, the ordering, the returned fields, and the public data source. With no output schema, it might have briefly noted the overall response shape, but it already tells an agent enough to call and interpret the result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema itself already documents the url and limit parameters well. The description adds ordering and output fields but not new parameter-level meaning, keeping this at the baseline for well-covered schemas.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: get a SoundCloud user's own uploaded tracks, ordered most recent first. It clearly differentiates this from sibling tools like soundcloud_search, soundcloud_profile, and soundcloud_track by emphasizing 'own uploaded tracks' and naming the exact returned fields.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use it: when an agent needs an artist's original uploads rather than playlists, profiles, or generic search results. It gives clear contextual guidance, though it does not explicitly name alternative tools or state when-not-to-use conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It mentions validation of chart and region parameters and category chart limitations, but lacks details on response format, data freshness, or any side effects. It's adequate but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with the main action. Every sentence adds necessary detail without redundancy. Highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description explains what is returned (chart rankings) and includes validation and region constraints. It is mostly complete, though could mention that rankings are normalized.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. The description adds that chart and region are validated against supported values and that category charts are restricted to specific regions, adding semantic value beyond the allowed lists.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Spotify podcast charts from a specific source (podcastcharts.byspotify.com). It distinguishes from siblings like apple_podcasts_charts or spotify_podcasts_search by specifying the source and type of data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides context on when to use this tool (to retrieve podcast charts) and includes region constraints for category charts. However, it does not explicitly compare to alternative tools or indicate when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explicitly states it is 'Credential-free public Steam storefront JSON', disclosing authentication requirements and output format. No annotations exist, so this is sufficient for a read-only tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with the main action, no extraneous information. Every sentence serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers return fields and parameter usage. Without an output schema, explaining the returned metadata fields is helpful. It lacks error handling details, but overall is adequate for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds meaningful context: cc selects region/currency, l selects language, filters shrinks payload with comma-separated fields. This adds value beyond the schema's minimal descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves Steam store details for a single app, listing specific metadata fields (title, type, price, etc.). This distinguishes it from sibling tools like steam_reviews or steam_achievements by focusing on store metadata.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining store metadata but does not explicitly provide when-to-use guidance or contrast with alternatives like steam_steamspy or steam_search. The agent must infer from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses credential-free access and data enrichment toggle, which is helpful given no annotations. However, missing potential limitations like rate limits, pagination, or data refresh frequency. Transparency is good but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences covering purpose, output details, and key parameter. No extraneous information, well front-loaded. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with 3 optional parameters and no output schema, the description is largely complete. Could mention if results are paginated or have a fixed size, but the core behavior is well covered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds value by explaining the enrichment behavior (default enriching, enrich=false for raw) and the role of l and cc parameters for name localization. Goes beyond schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states it retrieves Steam's live games-by-concurrent-players leaderboard, listing returned fields (rank, appid, current concurrent, peak). This clearly distinguishes it from sibling tools like steam_charts_most_played and steam_charts_top_releases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or alternatives guidance. The description implies use for live concurrent player data, but does not contrast with sibling chart tools. Suitable for an informed agent but lacks direct usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It mentions credential-free public access, which is useful, but lacks details on rate limits, error handling, or what happens if the package does not exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no waste. The first sentence establishes purpose and output fields; the second adds parameter context and authentication info. Efficiently structured and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple fetch tool with 3 parameters and no output schema, the description covers the core purpose, parameter semantics, and authentication. It lacks behavioral details like caching or error responses, but remains adequate for typical usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds value by explaining that 'cc' controls region/currency and that 'packageid' is numeric. This enriches the parameter understanding beyond the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it gets Steam store details for a package and lists the specific returned fields (name, apps, price, platforms, release date). The phrase 'a purchasable bundle' effectively distinguishes it from sibling tools like steam_app which handles individual games.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description explains that 'cc' selects store region and price currency, and notes it is credential-free. While it implies use for packages versus apps, it does not explicitly contrast with adjacent tools like steam_app or steam_items.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does well: it discloses the data source (StockX GraphQL API), that it is credential-free, the ordering (release date ascending), and the filtering ('on or after the given date'). It adds useful context about output contents, though it omits any caveats about empty results or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the action, and every phrase adds value—details on ordering, product content, and data source are all relevant. No filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description explains return contents (product summaries, pricing, release dates) and ordering. It covers the core behavior well. Minor omissions like explicit pagination behavior or timezone notes are mostly covered by the schema, so the context is sufficiently complete for a moderate tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents all parameters with clear descriptions (from, page, limit), and the description does not add significant meaning beyond referencing 'the given date'. This is a baseline 3 because schema coverage is 100% and the description adds minimal extra semantic value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb and resource: 'Get StockX upcoming release calendar.' It distinguishes itself from sibling tools like stockx_product and stockx_search by focusing specifically on releases and describing the output (date-ordered, new/restocked products, pricing).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes the usage context clear: it retrieves upcoming release calendar data, implying use when release schedule info is needed. However, it does not explicitly state when not to use this tool or name alternatives, though the name and context strongly suggest appropriate use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the transparency burden. It adds meaningful behavioral context by stating 'Credential-free public data' and describing the output as 'normalized product summaries with headline pricing plus the total matching count'. It lacks explicit read-only/side-effect statements or rate-limit notes, but the public-data disclosure is valuable context beyond the name and schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the primary action ('Search/browse StockX products'), then precise details about inputs, outputs, and data source. Every phrase earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 14 parameters and no output schema, the description covers input scope, output nature, and access requirements effectively. It could mention pagination or defaults, but the schema already documents page/limit defaults, so the description is sufficiently complete for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds a high-level framing by grouping filters as 'facet filters (gender, brand, color, shoe height, activity, availability)' and mentioning free-text keyword search, but it does not enrich individual parameter meanings beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Search/browse StockX products' with clear scoping to the product catalog, listing optional keyword search and facet filters. It distinguishes from sibling tools like stockx_product (product detail) and stockx_categories (category list) by describing what this tool returns: normalized summaries, headline pricing, and total count.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly indicates when to use this tool: to browse or search StockX's catalog by category with optional filters. It does not explicitly name alternatives or say 'use stockx_product for full details', so it stops short of a 5, but the context is unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description discharges transparency by enumerating what fields are included, what is excluded (discussion, leaderboard, etc.), and noting the data source (Strava's server-rendered page). This gives the agent a solid mental model of the tool's access limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each adding distinct value: purpose, limitations, and source. No redundant phrasing or irrelevant details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter public profile lookup, the description covers return fields, exclusions, and data provenance. It lacks only explicit error/edge-case behavior, which is not critical for this simple retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The sole parameter id is described in the schema as 'Strava club ID' (100% coverage). The description adds no further format or constraints, but none are needed. Baseline 3 applies given full schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Returns a Strava club's public profile' and enumerates specific fields (name, flags, location, description, member count, images). It clearly differentiates by stating what is not returned (discussion, leaderboard, etc.), making the tool's scope unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly frames usage as fetching base public club data and explicitly excludes data requiring a logged-in Strava session, which sets expectations. However, it doesn't name alternative tools or state explicit 'when to use' conditions beyond the inherent purpose. It's clear enough for a single-purpose lookup.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the disclosure burden. It states 'Public data, sourced from Strava's own server-rendered route pages,' which adds context about data source and accessibility. However, it doesn't detail behaviors like rate limits, pagination, or error conditions, leaving some gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the tool's primary purpose, and every sentence contributes meaningful information. No redundant or verbose content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter detail endpoint with no output schema or annotations, the description covers the key aspects: what data is returned, how to obtain the required path, and the data source. It could mention potential failure modes or response format, but overall it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds value by explaining the path parameter's origin, providing a concrete example, and clarifying the expected format. This goes beyond the schema's generic field description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool returns a single Strava route's detail with a specific list of fields (type, difficulty, distance, elevation gain, estimated time, summary). This clearly distinguishes it from sibling tools like strava_routes, which would list multiple routes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description tells the user that the path parameter is the relative route path returned by /strava/routes, implying a sequential workflow. It provides clear context on when to use this tool after obtaining a route from strava_routes, though it doesn't explicitly mention alternatives or exclusion scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It discloses that the tool uses public data sourced from Strava's server-rendered route pages, implying a read-only operation with no authentication required. While it does not mention rate limits or exact pagination behavior, the public-data note gives essential context for a read-only listing tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences plus a short enumeration of sport values. It is front-loaded with the purpose and contains no redundant information, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (4 flat parameters, no output schema) and the absence of annotations, the description covers the main retrieval dimensions: sport, country, region, and pagination via 'page'. The return description ('a page of recommendations') is somewhat high-level but sufficient for a listing tool, though it could mention output structure or edge cases to be truly comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: every parameter (page, sport, region, country) already has a description in the schema. The tool description adds no new parameter-level information beyond repeating the sport values and region format already present in the schema, so it earns the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'route-index listing' that returns a page of public route recommendations for a sport, country, and region. It uses specific verbs ('Returns', 'listing') and identifies the resource (Strava's public route recommendations), distinguishing it from the sibling tool 'strava_route_detail' which would handle individual routes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use the tool: when you need a paginated list of Strava public routes filtered by sport, country, and region. It also enumerates valid sport values. However, it does not explicitly mention alternatives or exclusions (e.g., when to use strava_route_detail instead), so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the type of output ('normalized product details') and enumerates key data categories (content, images, price, rating, category, availability flags). It does not mention potential side effects or error conditions, but as a read-only 'get' operation, the lack of side effects is apparent. The ambiguity around 'selected store' when store_id is optionally provided is a minor gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that immediately identifies the tool's purpose ('Get a Target product') and then supplies the key output highlights. No redundant information or filler. Every word contributes to understanding the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple lookup tool with two parameters and no output schema, the description provides sufficient context about what will be returned. It lists the major data categories, which covers the typical use case. Missing details like default store behavior or error handling are minor given the simplicity of the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema describes both parameters thoroughly (tcin as numeric Target item id, store_id as Target store id for pricing/availability). The description adds marginal context by mentioning 'selected store' and 'availability flags,' but this largely mirrors the schema. Since schema coverage is 100%, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action: 'Get a Target product' and specifies that it returns 'normalized product details for one Target item.' This clearly distinguishes it from sibling tools like target_search, which searches for products, and target_reviews, which retrieves reviews. The verb+resource structure is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies this tool is for fetching a single product's details using an identifier, contrasting with search tools. However, it does not explicitly mention when to use this versus target_search or other product tools, nor does it name alternatives or exclusions. The context is clear but lacks explicit alternative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries the transparency burden. It usefully discloses that data is parsed from Tesla's own job detail JSON endpoint, implying a direct scrape of Tesla's site, but it does not describe the response structure, fields, or any potential limitations such as rate limits or authentication needs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three short, front-loaded sentences with no wasted words. Each sentence adds relevant information: what it does, how the id is obtained, and where the data comes from.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter fetch tool, the description covers the essential context: target resource, id source, and data origin. The lack of an output schema is partially mitigated by the clear statement that it returns 'one Tesla Careers posting', though a bit more detail about the returned fields would make it fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents the `id` parameter with 100% coverage, so the baseline is 3. The description adds meaningful detail by clarifying that the id is numeric and comes from the list endpoint, which helps the agent understand the expected value beyond the minimal schema description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns one Tesla Careers posting by its numeric job id, making the purpose specific and unambiguous. It also distinguishes this tool from the list/search job tools by referencing the `id` field from the list endpoint.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the intended workflow: first use the list endpoint to obtain an `id`, then call this tool. It does not explicitly name alternatives or state when not to use, but the context is clear enough for an agent to select it appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses an important behavioral trait: the response may indicate additional replies but without a usable continuation cursor. This is valuable context beyond the basic retrieval purpose, though it omits details like response format or pagination behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loaded with the primary action, and every sentence adds useful information. No waste or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with two straightforward parameters and no output schema, the description provides enough context about what is returned and a key limitation. It lacks detailed response structure, but that is not critical for invoking the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% coverage with descriptions for 'username' and 'code'. The tool description adds no additional meaning beyond the schema, so it meets the baseline without enhancing parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action and resource: 'Retrieve public replies to a Threads post.' This distinguishes it from sibling tools like threads_post, threads_profile, and threads_search, which serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context by noting this returns only 'public replies... exposed to logged-out visitors' and mentions a limitation about continuation cursors. However, it doesn't explicitly mention alternatives or when not to use the tool, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full transparency burden. It discloses that the tool returns a zero-based paginated event feed, which is a key behavioral trait. It also constrains category_id to those from the categories tool. However, it omits details about error handling, rate limits, or response structure, which limits full transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two short sentences, with the primary action front-loaded. There is no redundant wording, and each sentence adds value — the first states the action, the second explains the pagination and category source.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 2-parameter tool with no annotations and no output schema, the description covers the essentials: purpose, pagination scheme, and valid category source. It lacks details like default page size or error behavior, but given the tool's simplicity, it is reasonably complete for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds meaningful context by specifying that category_id should come from ticketmaster-discover-categories, which is not in the schema. The page parameter is reinforced as zero-based, though already stated in the schema. This enhancement justifies a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List events in a Ticketmaster discover category' — a specific verb+resource+qualifier. It distinguishes this from sibling tools like ticketmaster_discover_city_events and ticketmaster_venue_events by focusing on discover categories. The mention of 'zero-based paginated event feed' also clarifies the output nature.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear prerequisite: 'for any category returned by ticketmaster-discover-categories', which implies a workflow where one first fetches categories. This gives context for when to use the tool. It does not explicitly list exclusions or alternative tools, but the category linkage is evident and sufficient for an agent to select it appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the transparency burden. It adds valuable behavioral context by stating that a zero total with an empty events list is a valid no-results response, preventing misinterpretation. It also clarifies the accepted sort enum values, which is not covered by annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and mostly front-loaded, but the first sentence 'Search Ticketmaster events' is redundant with the second sentence, which already states the same action. Removing or merging the first sentence would make it tighter and more efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 3-parameter search tool with no output schema, the description is reasonably complete. It explains the no-results edge case and sort options, and the schema covers parameter details. It does not describe the full return structure, but the mention of an 'events list' gives enough context for basic use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds meaningful value by explicitly listing the sort enum values (`relevance` and `date`), which the schema leaves unspecified. It also reinforces the `q` parameter semantics with different wording, though the schema already covers it adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches Ticketmaster events by artist, event, team, or venue, which is specific and actionable. This distinguishes it from sibling tools like ticketmaster_event or ticketmaster_discover_city_events, which focus on details or discovery rather than keyword search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies clear usage context: use this tool when you want to find Ticketmaster events via a text query. It does not explicitly mention alternatives or when not to use it, but the query types (artist, event, team, venue) provide enough guidance for an agent to decide when invocation is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It clearly states the tool returns the category list exposed by the Explore page, which is straightforward. No side effects are expected, and the behavior is transparent for a simple list retrieval.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, zero waste. Every word is necessary and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple parameterless tool, the description is reasonably complete. It states the output is a list of categories, though it does not specify the format (e.g., strings or objects). Given the lack of output schema, a bit more detail would be helpful, but still adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no parameters, so the description does not need to explain parameter semantics. Baseline for 0 params is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The verb 'List' and resource 'TikTok explore categories' are specific and clear. It distinguishes from sibling tools like 'tiktok_explore' (which likely returns content) by stating it returns the category list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (when you need the list of explore categories) but does not explicitly state when not to use or mention alternatives. There is no guidance on prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses a non-obvious behavior: unscoped queries interleave results across types rather than returning the top-ranked single type. It also states 'Credential-free public TMDB data', which clarifies authentication expectations. This is more than baseline, though it does not cover rate limits or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three tight sentences: the first adds the verb, the second defines scope, the third explains a key behavior. No redundant filler, every sentence contributes, and it is front-loaded with the purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers purpose, scope, cross-type behavior, and auth requirements. It is sufficient for a straightforward search tool with a simple schema, though it omits an explicit return format description and alternative-tool references. Overall, it provides solid contextual grounding for an agent to select and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all four parameters (query, type, page, limit). The description does not add extra parameter-level meaning beyond what the schema provides, which is the baseline case for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Searches TMDB movies, TV shows, and people.' It also explicitly distinguishes from more specific sibling tools (e.g., tmdb_movie, tmdb_tv, tmdb_person) by covering all three types. The interleaving note further clarifies that this is a cross-type search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the core use case: an unscoped query that interleaves results across all three types. This implies when to prefer this tool over type-specific siblings, but it does not explicitly name alternatives or state when not to use it. The context is clear, but explicit exclusion/alternative guidance is missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It adds the credential-free auth context ('Credential-free public TMDB data') and states it returns a chart, indicating a read-only retrieval. It doesn't mention rate limits or response format, but for a data-fetch chart tool this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, 23 words, front-loaded with the core action. Every phrase adds value: the verb, resource, chart categories, and the credential-free note. No redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 14 optional parameters, all well-documented in the schema, the description need not repeat them. It provides the essential context (what data is returned, credential requirements). The lack of an output schema means the response format is not described, but for a chart-list tool the intent is clear.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, providing baseline 3. The description adds meaningful context for the 'category' parameter by listing the four chart types (popular, top rated, airing today, on the air), which the schema does not. This enriches the parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get a TMDB TV chart' with specific chart categories enumerated (popular, top rated, airing today, on the air). This distinguishes it from sibling tools like tmdb_tv (likely show details) and tmdb_search (search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for chart-style TV data ('Returns a TMDB TV chart') but does not explicitly mention when to use it versus alternative TMDB tools or list exclusions. No alternatives or exclusions are named, so usage guidance is inferred rather than direct.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full disclosure burden. It reveals the data is 'credential-free public data sourced from Trip.com's own server-rendered hotel-detail page' and explicitly calls out that pricing is absent, which helps set expectations. It also mentions 'normalized' output, adding a behavioral trait beyond just the return fields.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core action and then uses a structured list of return sections. Every sentence carries information, from the data source to the pricing limitation, without repetition or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema, the description extensively enumerates the response sections (identity, location, rating, images, policies, etc.) and explicitly states what is not included (pricing). It could be more complete by addressing error behavior or locale/language of data, but it covers the main expectations well.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters (id and slug) are fully described in the schema, so schema coverage is 100%. The description does not add parameter-level semantics beyond the schema; it only mentions the search endpoint as a source for id indirectly, which is already in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Get Trip.com hotel detail' – a specific verb and resource – and then enumerates the returned data sections. It clearly positions this as the Trip.com hotel-detail tool, distinct from the sibling tripcom_hotels_search and other providers' hotel detail tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It states pricing is not included and directs users to 'use the search endpoint for a city's current display prices,' providing an explicit alternative for a specific use case. It also implies this is the correct tool when hotel identity, location, ratings, images, and policies are needed, though it lacks a broader when-to-use/when-not-to-use statement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the credential-free nature and specifies the returned fields, giving a clear behavioral picture. It does not detail pagination behavior or rate limits, but the schema already documents limit/offset clamping, so the description adds meaningful context beyond the structured data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary action, and every phrase adds value. It avoids redundancy with the schema and includes essential context (credential-free, returned fields) without verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a feed-browsing tool with no output schema or annotations, the description covers purpose, return fields, and auth status. It could ideally mention potential limitations such as geographic coverage or result ordering, but the existing detail is sufficient for an agent to select and invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds minimal parameter semantics beyond the schema: it mentions 'specific location' aligning with latitude/longitude, but the schema already explains 'Delivery search center latitude/longitude.' No new meaning is added for limit/offset.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Browse UberEats location feed' and enumerates the returned data fields (name, rating, review count, delivery estimate, cuisine tags, cover image). This distinguishes it from sibling tools like ubereats_search and ubereats_store by focusing on the feed concept.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context: a location feed requiring latitude/longitude to find delivering restaurants. It also notes 'Credential-free public UberEats data,' clarifying that no authentication is needed. However, it does not explicitly name alternatives or state when not to use this tool, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that this is credential-free public data, states the return fields, and describes the two behavioral modes. This is transparent for a read-only search tool. It doesn't cover rate limits or error behavior, but those aren't critical for the described functionality, and the description provides substantial context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loads the purpose, and includes return fields and usage notes without unnecessary words. Every sentence contributes value, and it is appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is quite complete for a search tool without an output schema: it lists the return fields, explains the two invocation modes, and notes credential-free access. It doesn't explicitly discuss pagination or limits, but those are already captured in the parameter schema. This is strong coverage for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so all parameters are documented structurally. The description adds extra semantics by explaining the query parameter's dual role (keyword or omitted for feed) and the offset usage nuance, but it doesn't go beyond what the schema already communicates for most parameters. Baseline 3 is appropriate given the high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches UberEats restaurants and returns specific fields (name, rating, review count, delivery estimate, cuisine tags, image). It also explains the two modes (keyword search vs. browsing the general feed) and distinguishes from related tools like ubereats_feed by emphasizing location-based delivery and optional keyword. This is a specific verb+resource with strong scoping.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use the tool: to find restaurants delivering to a location, with or without a keyword. It clarifies the difference between keyword search and browsing the general feed. While it doesn't explicitly mention alternatives like ubereats_store for details, the context is clear and there are no misleading exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden and does well: it discloses the operation is credential-free (no auth needed) and lists the exact payload fields, signaling a safe read-only fetch. It lacks details on error handling or rate limits, but for a simple menu retrieval it provides meaningful behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the action and resource. Every sentence adds value: the first states purpose, the second enumerates return contents and access mode. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a single parameter and no output schema, the description adequately explains what the tool returns and that it is public data. It doesn't discuss relationships to sibling ubereats tools, but it is complete enough for an agent to decide when a store menu is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the store_id parameter is already well described in the schema as the UUID from search's storeUuid field. The description does not add any parameter information, but since the schema fully covers semantics, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets an UberEats store menu, with a specific verb ('Get') and resource ('store menu'). It enumerates the exact content returned (sections, items, descriptions, prices, availability), which distinguishes it from sibling tools like ubereats_store and ubereats_store_reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context by noting it is credential-free public data, which implies it is appropriate for public store menus without authentication. However, it does not explicitly mention alternatives or when not to use this tool, so it stops short of full usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the behavioral disclosure burden. It does well by explaining the empty vs. populated meaning of group, the duplicate cross-listing behavior, and that the returned URL is directly usable as a parameter. A small gap is that it does not describe the full list response shape or any pagination/limits, but the core behavior is well covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is detailed but slightly redundant: "List Ulta Beauty storefront categories" and "Lists Ulta Beauty's own storefront category navigation" repeat the same idea. However, the most important operational details about group, duplicates, and the URL parameter are clearly stated and the content is well ordered.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single optional parameter with no output schema, this description is substantially complete: it states what is returned, how the returned URL should be used, what group means, when department filters, and how duplicates may legitimately occur. There are no significant gaps that would prevent an agent from selecting and invoking this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers the single optional parameter with "Filter to one department," and the description adds only that the department filter "filters to just that department's entries." This is useful but only a marginal extension of the existing schema documentation, putting it at the baseline for fully described parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: "List Ulta Beauty storefront categories." It also clarifies the output (department, group, name, URL) and explicitly ties the URL to GET /ulta/category, which distinguishes it from ull_ category-specific sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear usage context: this tool "closes the discovery gap" when the caller does not already know a category path. It does not explicitly name alternatives or state when not to use it, but its role relative to the category endpoint is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral disclosure burden. It explains that an invalid or omitted sku still resolves to the base product's default variant and that an unrecognized productId returns 404; this is valuable beyond the semantic basics. It does not mention authentication, rate limiting, or additional error types, but for a simple detail-retrieval call these are not critical.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core operation and return field list, then moves to parameter provenance, variant behavior, and error handling. Every sentence is informative and contains no filler, even though the phrase 'full detail' appears twice.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter read tool with no output schema and no annotations, this description is sufficient: it lists the return contents, explains both parameters including optional sku behavior, gives an example id, and states the 404 error case. Nothing essential for calling the tool correctly is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents both parameters, so the baseline is 3, but the description adds meaningful context beyond the schema. It specifies the exact source of productId, gives an example value, and explains the optional behavior and fallback semantics for sku.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a single Ulta Beauty product's full detail and enumerates the fields included. It differentiates the tool from search/review/category siblings by the phrase 'full detail' plus the field list, but it does not explicitly name or contrast it with sibling tools like ulta_search or ulta_product_reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives concrete guidance on where to obtain productId, namely from a search result's product_id field or a product page URL, which implies use alongside search tools. It provides a real-world example and explains sku's optional role, but it does not explicitly state when not to use this tool or point to alternative tools such as ulta_product_reviews.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden and does so well: it discloses the composed return shape (suggested terms, product matches, featured top result) and the important edge-case behavior that a no-match query returns an empty result rather than an error. It does not cover auth or rate limits, but for a simple read-only suggest tool this is reasonable disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
It is front-loaded with the core action and every subsequent sentence adds distinct information: what the response contains, the featured-result behavior, and the no-match behavior. There is no filler or repetition of the parameter schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter suggest tool with no output schema, the description adequately sets expectations about both the payload shape and the empty-match result. It is complete enough for correct selection and invocation; detailed field-level return typing is not necessary at this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and the single 'query' parameter is already described as a 'Partial search term'. The description restates and reinforces that meaning but adds no syntax, format, or length details beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') with a resource ('Ulta Beauty search suggestions') and details the result structure: suggested search terms, top product matches, and a featured result. It clearly distinguishes this from general search tools like ulta_search and from dozens of other retailers' suggest tools by anchoring it to Ulta Beauty's own typeahead behavior.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states the input is a partial search term, which makes the intended autocomplete use case clear. It does not explicitly name alternatives such as ulta_search, but the partial-term context plus the 'typeahead' framing gives enough context that an agent would not use this for full product searches.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that request metrics exclude certain endpoints (console, billing, usage, user-management), which is good. However, it does not explicitly state that this is a read-only operation with no side effects, though it is implied.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, consisting of two sentences with no extraneous information. The main purpose is front-loaded in the first sentence, and the second sentence adds a key detail about request limits.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is no output schema, the description provides a reasonable sense of what is returned (billing snapshot, request and credit metrics). It could be more specific about the default time range and the recency of metrics, but overall it is sufficient for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with each parameter described (from, to, range). The description does not add additional semantic information beyond the schema, such as stating that range defaults to current billing period. Baseline 3 is appropriate as schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the verb (Get) and the specific resource (current user's usage overview). It distinguishes from sibling tools like usage_timeseries and usage_endpoints by specifying it returns a billing snapshot plus request and credit metrics, limited to product API traffic.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description implies usage for obtaining a holistic overview of the authenticated user's usage, but does not explicitly state when to use this tool over siblings like usage_timeseries or usage_endpoints. It provides clear context on what it returns, but lacks exclusions or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It thoroughly discloses included fields, deliberately excludes online-presence and activity data (last-seen timestamps, upload-frequency badges), and describes the data source as Vinted's server-rendered member page. This goes beyond basic read/write hints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: first states the resource and return fields, second notes exclusions and data source. Every sentence adds value with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema, the description covers the return content, deliberate exclusions, and data provenance. It omits error handling or rate-limit behavior, which would add completeness but is not essential for a straightforward profile lookup.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% coverage for the single parameter 'id' with a clear explanation ('Numeric Vinted member ID, from a /vinted/item result's seller link'). The description itself adds no additional parameter semantics, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Returns a Vinted seller's public storefront profile' and enumerates the specific fields (username, location, rating, follower/following counts). This uses a specific verb+resource and distinguishes the member profile from sibling vinted_* item/brand/category tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage is present: the id is sourced 'from a /vinted/item result's seller link', which suggests when to use it (follow-up on an item's seller). However, there is no explicit statement of when to use this versus alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states that it returns both live and upcoming shows, lists the specific data fields, and notes that the data is public and sourced from Whatnot's GraphQL API, which reassures the agent about access requirements and data origin. It could add details on pagination or ordering, but for a simple browse tool this is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the purpose, then immediately listing return fields and data source. Every sentence contributes valuable information without redundancy, making it concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter read-only browsing tool, this description is nearly complete: it specifies input category, output fields, the statuses included, and the data source. Without an output schema, listing the return fields is especially helpful. Minor gaps like ordering or pagination prevent a perfect score, but the description gives enough to use the tool confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of the parameter descriptions, so the baseline is 3. The description adds no additional meaning beyond the schema's 'Whatnot category slug' definition, except for implying that the category is used for filtering in the browse operation. Since the schema already fully documents the sole parameter, the description provides no extra semantic value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a specific verb and resource: 'Browse Whatnot live shows by category.' It clearly distinguishes this from sibling tools like whatnot_live (likely a general live shows feed) and whatnot_categories (which lists categories) by scoping to category-based browsing. It also enumerates the returned fields, making the purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly guides usage by stating the tool operates 'by category' and references 'GET /whatnot/categories' for the full list of category slugs, which is a clear prerequisite. It does not explicitly name an alternative tool or state when not to use it, but the category-slug dependency and the mention of categories endpoint provide adequate context for choosing this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden, and it does disclose the readable resource and enumerates the returned fields. However, it does not mention failure behavior for invalid URLs, potential missing fields, response format, rate limits, or any other runtime traits, leaving room for agent uncertainty.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences that front-load the core purpose, then detail the output fields and input requirement. Every sentence adds necessary information and no filler is present.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter read tool, the description provides enough output-field detail and input source context, especially given the small input schema. The absence of an output schema means the field enumeration is useful, though exact response structure and error behavior are not described.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents the URL parameter with 100% coverage, and the description augments it by prescribing a canonical www.yahoo.com/entertainment/ article URL and connecting it to the home or category story streams. This added guidance goes beyond the schema's minimal description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a single Yahoo Entertainment article's full content, with the verb 'Returns' and the resource scope 'Yahoo Entertainment article.' It further enumerates the exact fields returned, and the reference to a 'canonical www.yahoo.com/entertainment/ article URL' distinguishes it from sibling Yahoo article tools in other sections.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates the tool should be used with a canonical article URL, especially one produced by the home or category story streams, giving a clear workflow context. It does not explicitly name sibling alternatives or state when not to use it, but the domain-specific URL pattern makes the selection reasonably obvious.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden. It clearly communicates that the operation is a read returning content and fully lists what is returned; however, it doesn't discuss failure modes, authentication requirements, rate limits, or explicitly confirm absence of side effects beyond the semantically implied 'Returns.' This is a moderate but not severe gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two succinct sentences, front-loaded with the primary purpose and return content list, followed by the single input requirement. Every sentence adds use and clarity, with no repetition of the schema or waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter reader with no output schema and no annotations, the description covers the essential body content, return fields, URL domain, canonical-ness, and even URL sourcing from the sibling stream tools. It is complete enough to ground an agent's invocation, although it doesn't spell out a semantics for invalid or non-canonical URLs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers the parameter completely ('Canonical health.yahoo.com article URL'), so the baseline is 3. The description goes further by explaining where canonical URLs can be obtained (home/category story streams) and implicitly tying the URL to the exact article to fetch, which adds value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Returns a single Yahoo Health article's full content.' It names the exact resource (single article) and enumerates the fields (title, description, author, publish/update time, section, image, keywords, original publisher, body paragraphs), making it crisp and distinguishable from home/category stream tools and other Yahoo article tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly says the input must be a canonical health.yahoo.com article URL and even tells the agent where such URLs can be found: 'one returned by the home or category story streams.' This gives enough context to decide when to use the tool, although it doesn't formally list alternatives or exclusions, such as 'use yahoo_health_home for the stream instead.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full behavioral burden. It does disclose meaningful behavior beyond the schema: the result is a flat list (not nested/structured), it is sourced specifically from Yahoo News's search box, and it contains completed news search terms. It doesn't address edge cases like empty matches or short-query behavior, but for a simple read-only suggest tool this is a reasonable disclosure level.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences totaling about 24 words, with the core purpose front-loaded in the first sentence and the output shape glossed in the second. There is zero filler, and no sentence repeats schema content or annotation data.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 2-parameter tool with no nested objects and a fully covered schema, the only missing piece is the return value description, and the description supplies that: 'a flat list of suggested news search terms.' Minor omissions such as unspecified behavior for extremely short inputs or locale assumptions do not prevent correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% — the schema already documents q as 'Partial search query to autocomplete' and count with default and clamping behavior. The description's phrase 'for a partial query' merely echoes the schema's wording and adds no extra meaning. Baseline of 3 applies because the description doesn't need to compensate for any schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb-resource pair: 'Returns Yahoo News's own search-box autocomplete suggestions for a partial query.' The qualifier 'Yahoo News's own' explicitly contrasts with sibling general autocomplete tools like yahoo_search_suggest or bing_suggest, and the output shape ('a flat list of suggested news search terms') pins down exactly what the agent receives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'Yahoo News's own search-box' gives implicit routing context — this is distinct from general Yahoo web suggest (yahoo_search_suggest) or other domain suggest tools. It does not explicitly name alternatives or when-not-to-use conditions, so it falls short of the highest rating, but the context is clear enough for an agent to select it for news-scoped autocomplete.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations were provided, so the description carries full behavioral burden, and it delivers: it states the output normalization (decoded destination URL, never the raw click-tracking redirect) and the source ('server-rendered search page'). This URL-decoding guarantee is exactly the kind of non-obvious behavior an agent needs to set correct expectations. It omits minor details like rate limits or empty-result behavior, but covers the most important quirks.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each earning its place: purpose plus return fields, the URL-decoding caveat, and the data source. The most important scoping sentence is front-loaded, and there is no extraneous or boilerplate text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description correctly carries the return value information (title, destination URL, description, hostname, pagination), which it covers. Given that this is a straightforward 3-parameter search tool, it is near-complete; the only gap is leaving time_range's accepted values undocumented in both schema and description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds 'page-based pagination', which reinforces the page parameter, and implicitly ties the query string to the result shape. It does not add meaningful detail about time_range value formats or any other parameter beyond what the schema already documents.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource — 'Search Yahoo web results' — and precisely enumerates the output fields (title, destination URL, description, hostname, page-based pagination). This clearly sets it apart from sibling tools like yahoo_search_images, yahoo_search_news, yahoo_search_videos, and yahoo_search_local, which are all Yahoo-specific but different modalities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The strong focus on 'Yahoo web results' plus the detail that results come from Yahoo's 'own server-rendered search page' make the intended use case — general Yahoo web search — clear. However, it does not explicitly state when not to use it (e.g., images/news/videos variants) or name alternatives, leaving some routing inference to the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Even though there are no annotations, the description discloses informative behavioral traits: paginated feed output, the exact visible fields, and a source caveat (server-rendered section pages). It implies a read-only story-fetching operation without stating side effects. This goes beyond a flat schema by describing return shape and pagination behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two dense, front-loaded sentences. The first sentence establishes the core purpose and resource, and the second adds pagination and source context. Every clause contributes to the agent's ability to invoke the tool correctly; there is no wasted or redundant language.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 2-parameter, no-output-schema tool, the description carries sufficient context: the return fields are enumerated, pagination is mentioned, and the source is clarified. It does not describe a response envelope or error cases, but given the simplicity of the tool, those are not critical for successful invocation. This is not worse than an average similarly-scoped tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Since schema description coverage is 100%, the description doesn't need to restate what the parameters mean, but it also doesn't add much beyond them. It says 'page-based pagination' in prose, which mirrors the schema's '1-based page number', and it uses 'section' for category, matching 'Yahoo Shopping section'. No additional identifier mechanics or value examples are given, so the description delivers no meaningful token beyond what the schema already states.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'returns a Yahoo Shopping section's editorial story feed' and goes on to define the exact story fields (title, destination URL, category, thumbnail). This clearly distinguishes the tool from sibling tools like yahoo_shopping_home or yahoo_shopping_article by focusing on the section's story stream.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: to retrieve a Yahoo Shopping section's editorial story feed with pagination. It does not explicitly call out alternatives or when-to-not-use, but the wording is sufficient for an agent to infer the appropriate scenario without ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry behavioral disclosure. It does note that data comes from sports.yahoo.com's server-rendered game page and spells out the returned content, making the read-only nature apparent. However, it does not mention limitations like live-data availability, historical coverage, or potential html scraping fragility.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description puts purpose first, then lists the full league set, and closes with the game-slug derivation example. The league list is long but necessary given the bare schema, and every sentence carries useful information without filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With two string parameters and no output schema, it covers what the tool returns (matchup, period line score, team stat totals), how to source the game slug, and all league keys. Missing edge-case behaviors like error handling on invalid slugs or legacy data are not addressed, but the core usage needs are fully covered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only labels 'league' as 'League', but the description enumerates every accepted league value, effectively compensating for the missing enum. It also explains exactly how to derive the 'game' parameter from another response's url and gives a concrete example slug, giving an agent a complete invocation recipe.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states what the tool does: returns one game's boxscore (matchup, line score by period, and team stat totals) from a server-rendered Yahoo Sports page. It distinguishes itself from scoreboard/schedule tools by specifying a single game and by referencing scoreboard/team-schedule responses as its inputs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives clear context for when to use this tool: after obtaining a game slug from a scoreboard or team-schedule response's game url. It doesn't list any exclusions or alternative game-summary tools, but the entry-point relationship is explicit and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden for behavioral disclosure. It explains the underlying source (Yahoo's server-rendered MMA schedule page) and the output shape (calendar events with name, date, and status), which is helpful context. However, it leaves unaddressed staleness/caching behavior, meaning of the returned status values, response format details, and implications of the word 'known' (potential incompleteness).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences and front-loads the core purpose immediately, then adds the return shape, source, and then the scope and no-parameter information. Each sentence earns its place with minimal redundancy; the repeated mention of 'Yahoo's page' is a minor stylistic cost, not an informational waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, no-output-schema tool, the description is substantially complete: it names the output fields (name, date, status), identifies the source page, and prefaces the no-param scope. The only gap is that it does not detail what status values might look like or how frequently the schedule refreshes, but given the simple tool shape the core usage need is fully met.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters and the schema description coverage is 100%, so the baseline is 4. The description reinforces this by explicitly stating the endpoint 'takes no parameters' and provides an explanation (Yahoo's own page exposes nothing more from this URL).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource — "Returns the known UFC event calendar (name, date, status)" — and explicitly scopes the tool as UFC-only, distinguishing it from other promotion/schedule endpoints. The specification that Yahoo's page does not expose Bellator, PFL, or ONE Championship further clarifies what this particular tool is and is not.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context — this tool only covers the UFC schedule exposed by Yahoo's page, with no parameters. It claims implied alternatives: anything outside the UFC calendar (e.g., other promotions) is out-of-scope, so an agent knows what not to use it for. However, it never points to an explicit sibling or filter condition.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral disclosure burden. It does disclose the data source, the scope of returned data, and hints at parity with the scoreboard response. However, it does not address rate limits, pagination, auth needs, or data gaps like upcoming-playoff-game availability, which could be relevant for an agent making a production call.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The opening phrase 'Yahoo Sports team schedule' is a bit redundant with the tool name, but everything after it earns its place. The detailed league enum list is necessary because the schema lacks an enum, and the sentence teaching the agent how to fetch a team slug is high-value. Overall it is dense and readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no schema output, the description provides enough expectations by saying the schedule will have 'the same per-game fields as the scoreboard', which ties the return format to an existing sibling tool. Covering both required parameters and the data origin makes the tool usable, though it could be more explicit about the return structure or any pagination behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema's property descriptions are generic ('League key', 'Yahoo Sports team slug'), but the description adds concrete value: it enumerates all 26 accepted league values (with proper hyphenation) and goes beyond saying 'team' by explaining that the slug comes from scoreboard or standings, with examples like 'green-bay' and 'la-lakers'. This is exactly the non-obvious information an agent needs to invoke the tool correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb 'Returns' and a specific resource: a team's full schedule, including its scope (regular season plus any already-played/scheduled playoff games) and its source (sports.yahoo.com's server-rendered team schedule page). This clearly distinguishes it from siblings like yahoo_sports_scoreboard, yahoo_sports_standings, and yahoo_sports_team.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when the tool should be used — when you want a specific team's full schedule — and instructs the agent to get the required team slug from the scoreboard or standings response. It does not explicitly say when not to use it or name an alternative, but the context is sufficient to route correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It meaningfully discloses the credential-free access and the underlying Android app backend, adding valuable context beyond the schema. It doesn't cover error cases or return format, but the simple read-only nature is evident.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences, front-loaded with the main purpose. Each sentence adds a distinct useful detail: single business, backend source, and credential requirements. No waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter and no output schema. The description adequately covers the purpose, parameter, and auth expectations, enough for an agent to select and invoke it. It could optionally mention how to obtain the id via yelp_search, but this is not essential.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the only parameter 'id' already has a description. The tool description reinforces that the id can be an alias or encoded id but adds no new format details or examples beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('looks up') and clearly identifies the resource ('single Yelp business by alias or encoded id'). It distinguishes this tool from siblings like yelp_search and yelp_business_reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides clear context that this tool is for retrieving business detail, which implies when to use it. It doesn't explicitly mention exclusions or alternatives, but the scope is obvious from the description and sibling tool names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full transparency burden. It discloses the backend ('Yelp's real Android app backend') and credential-free operation ('no login, no API key, no cookie required'), which addresses common auth concerns. It stops short of covering rate limits or failure modes, but it goes beyond minimal expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the primary action, no filler. Every phrase adds value: what it fetches, the output format, the backend, and authentication requirements.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no output schema and no annotations, the description explains the return value (thematic snippets with supporting quotes), the access method (Android backend), and the lack of credentials. This covers the essentials, though it omits details about error cases or data volume.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the schema already describes `id` as 'Yelp business alias or encoded id.' The description adds no additional parameter semantics, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Begins with a specific verb+resource: 'Get Yelp business review highlights.' It then defines what highlights are ('thematic review snippets (extracted talking points with a supporting quote)'), clearly distinguishing this from sibling tools like yelp_business_reviews (likely full reviews) or yelp_business_reviews_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context on what the tool returns (thematic snippets with quotes), which implies when to use it. It does not explicitly name alternatives or state when not to use this tool, so it falls short of a 5 but offers more guidance than a bare statement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden. It transparently discloses the unconventional backend ('via Yelp's real Android app backend'), the auth requirements (credential-free), and the return format (highlighted excerpt per match). It does not cover rate limits or error handling, but it adds significant transparency for a read-only search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise sentences, front-loaded with the main action, and contains no fluff. Every sentence adds value: purpose, method, and credential requirements.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (2 params) and no output schema, the description adequately covers the return value (highlighted excerpt) and access requirements. It could mention behavior when no matches are found, but for a simple search tool, it is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, providing clear descriptions for both 'id' and 'term'. The description adds only marginal context (like returning a highlighted excerpt) but does not significantly enhance parameter understanding beyond the schema, so the baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Search Yelp business reviews by keyword' and specifies the exact resource (a Yelp business's reviews). It differentiates from sibling tools like yelp_business_reviews by focusing on keyword search and highlighting per match, making it distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly indicates when to use the tool—when you need to search reviews by a keyword—but does not explicitly state alternatives or exclusions. Sibling tools like yelp_business_reviews would be used for unfiltered listings, but this is not called out, so it lacks explicit when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses return structure (metadata, items, continuation token) and pagination, but does not mention access restrictions (e.g., private playlists) or authentication needs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with verb, zero waste. Efficiently communicates purpose and output.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so description must explain return values. It achieves this by stating returns metadata, normalized video items, and continuation token. Adequate for a playlist tool, though more detail on item structure could help.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds no additional meaning beyond what the input schema already provides for both parameters. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Retrieve playlist metadata and items', clearly identifying the verb and resource. It distinguishes itself from sibling tools like youtube_video and youtube_search by focusing on playlists.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving a specific playlist's content, but does not explicitly state when to use it versus alternatives like youtube_channel_playlists. It provides clear context but lacks exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It adds useful context: the tool browses by slug, requires market (no default), returns normalized result cards plus total_count, and slugs are market-specific. However, it does not disclose potential failure modes (e.g., invalid slug), rate limits, or authorization requirements. This is moderate but not comprehensive disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long and front-loaded with a clear purpose statement ('Browse a Zalando category or brand'). Each subsequent sentence adds distinct and essential information (return format, slug sourcing, market requirement) without repetition or filler. It is appropriately dense and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with only two parameters and no output schema, the description is quite complete. It explains the return type by referencing zalando-search's normalized result cards and the added total_count, provides guidance on obtaining valid slugs, and points to zalando-markets for the country list. Minor gaps remain, such as pagination behavior and error handling, but the description covers the essential context needed for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes both parameters ('Zalando country storefront' and 'Zalando category or brand URL slug, in the target market's own language'). The description adds value beyond the schema by providing concrete slug examples, explaining that slugs are market-specific with cross-market examples (shoes/chaussures/scarpe), and directing users to zalando-markets for the full storefront list. It also emphasizes that market is required, which is already in the schema but reinforced with rationale.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Browse' and identifies the resource as 'Zalando category or brand listing'. It clearly distinguishes itself from sibling tools by explicitly comparing its output to zalando-search ('returns the same normalized result cards as zalando-search, plus the category's upstream total_count') and by defining the input as a URL slug. Examples of slugs (shoes, womens-dresses) further clarify the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context on when to use this tool: when you have a category or brand slug, with guidance that slugs are market-specific and should be taken from the market's own site navigation or a product's url field. It references the alternative zalando-search and points to zalando-markets for the storefront list. However, it stops short of explicitly stating when NOT to use it (e.g., when performing a free-text search), so it lacks the full when/when-not contrast.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the data source (Zappos's published sitemap), that names are derived from URLs rather than authoritative labels, and that q is case-insensitive. It doesn't mention rate limits or pagination edge cases, but for a read-only list endpoint that is a minor gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Each of the four sentences has a distinct informational role: purpose, data source and discovery gap, next-step pairing, and naming caveat/filter semantics. No sentence is wasted and the main purpose is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description tells the agent what the tool returns (a page of brands with ids/URLs), how to use those in the next step, and data quality caveats. With no output schema, it provides enough context about returned ids and names, though a structured description of the response payload would be even more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameters q/page/page_size are already fully documented in the input schema. The description restates q's filtering behavior without adding meaningful new semantics beyond the schema coverage. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'List Zappos brands,' which states the exact action and resource. It also distinguishes the tool's role from zappos_brand by explaining that this endpoint closes the discovery gap when a brand id isn't known, and that one should 'Pair a returned id or url with GET /zappos/brand' for browsing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly signals when to use this discovery tool vs. the specific brand retrieval endpoint. It frames the gap ('otherwise has to be found elsewhere') and routes the user onward to the brand detail tool. It doesn't provide an explicit 'do not use when...' list, so it falls just shy of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and reveals that data is parsed from a stable server-rendered page and that no separate JSON endpoint exists. This adds meaningful context about the data source and reliability, though it does not describe error handling or output structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, two sentences, with no redundant or extraneous information. It front-loads the core purpose and then gives the key parameter source and technical context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and no annotations, so the agent must rely on the description to understand return details. While the description says it returns 'one Amazon.jobs posting', it does not enumerate fields or outline error behavior, leaving some ambiguity for a simple one-parameter tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides a description for the id parameter, but the tool description adds that it is the field returned by search, giving the agent a clear origin and expected value. This adds value beyond the schema's minimal 'Numeric Amazon job id'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns one specific Amazon.jobs posting by numeric job id, using the specific verb 'Returns' and identifying the resource. It distinguishes itself from the sibling search tool by emphasizing 'single posting' and by noting the id comes from search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a workflow by saying the id is 'the `id` field returned by search', which clarifies when to use this tool. However, it does not explicitly name the search sibling tool or state when not to use this tool, leaving some room for ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries some burden. It discloses that the data is 'Parsed from jobs.apple.com's server-rendered job detail page' and shows example ID formats, which is useful behavioral context. However, it does not mention error handling, rate limits, or what happens for invalid IDs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences with no fluff. It front-loads the core purpose, follows with concrete examples, and ends with the source. Every sentence contributes value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter fetch tool with no output schema, the description is mostly complete: it states the purpose, identifies how to obtain the ID, and notes the data source. It could be more complete by describing the returned posting structure or failure behavior, but the tool is simple enough that these gaps are minor.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Even though the schema covers the 'id' parameter 100%, the description adds significant meaning by explaining that the ID comes from search results, and gives two distinct example formats (requisition ID vs. evergreen/PIPE ID). This goes well beyond the schema's minimal 'Apple job id'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it 'Returns one Apple Careers posting by its job id', using a specific verb and resource. It distinguishes itself from search tools by specifying it returns a single posting, and the sibling apple_jobs_search exists for discovering IDs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description tells the agent to use the 'id' field 'returned by search', giving concrete examples of valid IDs. It clearly implies the correct workflow (search first, then fetch detail), though it does not explicitly name the sibling search tool or state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden. It discloses the source ('homepage's own Best Selling section') and the nested/fine-grained nature of the data, and it reveals that each ID can be used downstream in bestbuy_category. Lacking a description of the exact return structure or count, but for a zero-parameter tool the description is informative.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded and packed with meaningful context, but the phrase 'fine-grained' appears multiple times and could be tightened slightly. Overall each sentence serves a purpose: what it does, what the results look like, how it differs from a sibling, and how to use the IDs.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with no parameters, no output schema, and no annotations, the description is adequately complete: it tells the agent the source, suggests the granularity, names the sibling, and gives usage linkage to bestbuy_category. It could explicitly say the return is a list of objects with id/name, but the description already sets enough expectations for this type of category-listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so the baseline of 4 is appropriate. The description does not need to explain parameters, and it stays consistent with the empty schema by not pretending parameters exist.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the purpose: retrieving Best Buy's fine-grained trending product-type categories. It differentiates from the sibling bestbuy_categories by specifying that it is much more specific than those ~25 top-level departments, supported by concrete examples like 'Windows Laptops' and 'PS5 Consoles'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives actionable context for when to use the tool; it points to bestbuy_categories as the top-level alternative and even tells the agent that each returned ID is directly usable as bestbuy_category's category_id. It does not explicitly state a when-not-to-use condition, but the contrast with bestbuy_categories is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, this description carries the behavioral burden itself. It states that the tool returns normalized product data sourced specifically from the product page's schema.org Product structured-data block, which is a meaningful and non-obvious behavioral disclosure. It doesn't cover failure or missing-data cases, but for a simple read-style lookup this is substantially transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two tight sentences with no waste. The action and returned content are front-loaded, the source explanation earns its place, and the SKU clarification is placed last where contextual detail belongs.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, so the description correctly compensates by enumerating the normalized return fields. With exactly one required parameter, a named product source, and clear output expectations, the description is complete enough for an agent to select and call the tool with minimal risk of confusion.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully documents the single parameter with the text 'Numeric Best Buy SKU', so the baseline is strong. The description adds value by explaining where to find the SKU on bestbuy.com product pages and URLs, which helps an agent correctly source and format the identifier.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Uses a specific verb and object ('Get a Best Buy product's detail') and explicitly lists the returned normalized fields such as name, brand, color, price, availability, rating, images, and breadcrumbs. This makes it easy to distinguish from siblings like bestbuy_product_reviews, bestbuy_product_questions, and bestbuy_product_related.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is implied: provide a known Best Buy SKU to fetch one product's detail, with the SKU located on bestbuy.com pages/URLs. However, it never explicitly says when not to use it or points the agent to alternatives such as bestbuy_search for finding SKUs or bestbuy_product_reviews for ratings content.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the responsibility for behavioral disclosure. It adds useful behavioral detail by saying the store data comes from Best Buy's own SEO store directory, that city matching is case-insensitive, and that state codes are limited to the 50 states plus dc and pr. It does not mention edge cases like missing cities or pagination, but the tool appears to be a read-only lookup, which the description supports.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The first sentence is front-loaded with the tool's purpose and the required parameters are described immediately after. It is somewhat verbose due to the full list of state codes, but that list is useful and non-redundant because the schema has no enum. There is a slight redundancy between the first and second sentences, but overall the structure is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter lookup with no output schema, the description gives enough context to call the tool correctly: it states the input rules, the source of the data, and the fields the response contains. It does not define the exact output envelope or behavior when no stores match, but the missing detail is unlikely to prevent a successful call.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only describes 'City name' and 'Two-letter state/territory code', so the description adds meaningful value by enumerating all valid state/territory codes and explaining that city is free text matched case-insensitively against the state's directory. This materially helps the agent construct a valid request without extra guessing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Get Best Buy's physical stores in one city.' It then lists exactly what is returned, including name, address, phone, coordinates, rating, and hours, which makes the tool's action and scope immediately clear and distinguishable from product- or category-focused sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use the tool: when physical store locations in a specific city are needed. It does not explicitly name alternatives or exclusions, but the 'physical stores' framing separates it from bestbuy_product, bestbuy_search, and similar siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the data is public, credential-free, sourced from the AppView API, and warns that the surface is unstable and may change without notice – valuable behavioral context beyond structured fields.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Four short sentences, front-loaded with purpose, and each sentence earns its place: what it returns, the data source, and the stability warning. No redundancy or wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter read-only tool, the description fully explains the output (trending topics and suggested feeds with links), the public data source, and the instability risk. This is sufficient for an agent to invoke and interpret the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has zero parameters, so there is nothing to document. Per rubric, 0 params equals baseline 4. The description adds no parameter-specific info, which is appropriate since none exists.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description uses specific verb 'Returns' and clearly identifies the resource as 'Bluesky's current trending topics and suggested feeds', distinguishing it from sibling BlueSky tools focused on profiles, follows, or threads. The scope is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use vs alternatives is stated. Usage is implied by the tool name and description, but no sibling tools are named or excluded. The stability caveat provides some context but does not direct the agent to alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that data is public, credential-free, and rendered via proxied browser renderers. This is sufficient for a read-only tool, though rate limits or caching are not mentioned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loading the purpose and succinctly adding details. Every sentence contributes meaning without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description lists the returned fields (name, description, category, aggregate rating). For a simple product retrieval, this provides complete context for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description of the product_id parameter. The description adds no further meaning beyond the schema, so it meets the baseline with no additional value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get a Capterra product' and lists the returned fields (name, description, category, aggregate rating). It effectively distinguishes from sibling tools like capterra_search and capterra_reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions 'Credential-free public Capterra data' indicating no authentication needed, and describes the data source. However, it does not explicitly contrast with alternatives or provide when-not-to-use scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full disclosure burden. It clearly states this is credential-free public data, names the primary source (CarMax mobile-app API), and explains the website fallback for fields not exposed by the API—useful behavioral context beyond the tool name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise yet information-dense: a one-line purpose, a structured list of returned data categories, and a source/credential note. Every sentence adds value and the main verb and resource are front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema, the description inventories the principal return contents (specs, equipment, warranty, history, guarantee terms) and notes credential-free access. This is sufficient context for an agent to select and invoke the tool for a vehicle-detail lookup.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description does not add parameter-level meaning beyond the schema; stock_number and store_id are already well documented in the input schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description opens with 'Get CarMax vehicle listing detail,' a specific verb+resource pair that clearly identifies the operation. It further distinguishes itself from sibling search/recommendation tools by enumerating the comprehensive detail fields returned.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is implied by the name and description: retrieve full listing detail for a specific CarMax vehicle. However, it does not explicitly state when to choose this over sibling tools like carmax_search or carmax_vehicle_recommendations, nor does it mention exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes the basic behavior (returns item cards, uses slug, defaults) but lacks disclosure on safety (read-only vs. destructive), rate limits, or authentication requirements. For a simple listing tool, the transparency is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first states purpose and output, second gives examples and defaults. Every sentence is informative, no wasted words. Front-loaded with the key action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool with full schema coverage and no output schema, the description covers the essential aspects: what it does, how to find slugs, and default parameters. It could mention the structure of 'item cards' or if pagination is involved, but it is sufficiently complete for an agent to use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with all parameters described. The description adds significant value beyond the schema by explaining the 'collection' parameter as a slug, providing example slugs, and clarifying default values for 'num', 'country', and 'lang'. It also points to another endpoint for known slugs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List items in a curated Chrome Web Store collection' and specifies that it returns item cards for a given slug. It includes examples of slugs like 'editors_picks_extensions', making the resource and action unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear guidance on how to find collection slugs by referencing '/chromewebstore/categories'. States defaults for parameters, but does not explicitly mention when not to use this tool versus other similar tools like chromewebstore_search.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It does disclose that the tool is a public lookup, returns a full catalog rather than search-filtered subset, and provides the exact returned fields, which is meaningful transparency. It does not mention pagination or output size, but those are secondary for a zero-parameter lookup.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact at two sentences and leads with the core result before expanding on the differentiator. There is some repetition of 'Depop's full brand directory,' but the second sentence earns its place by explaining the search-endpoint use case and data source.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, no-output-schema brand directory tool, this description is quite complete: it identifies the payload fields, the scope, the public source, and the main motivating use case. It does not provide pagination or response structure details, but the intended use is clear enough for an agent to confidently invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no parameters and 100% schema description coverage, so there is no ambiguity for the description to resolve. Per the rubric, zero parameters earns a baseline of 4; the description handles this well because it relies on the empty schema rather than inventing meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool Returns Depop's full brand directory along with its fields (id, name, slug), so the agent knows exactly what resource is being fetched. It also distinguishes itself from the search tool by explicitly noting it is not limited to brands with active listings, which helps disambiguate it from related depop and marketplace directory tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use it: when the agent needs the full brand list or needs to resolve the search endpoint's opaque brand_ids into readable names. It does not explicitly name an alternative tool such as depop_search or state a firm when-not-to-use rule, but the contrast with 'brands with active listings for a given search' makes the intended use reasonably clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It discloses the data source ('Public data sourced from Depop's own item pages'), the normalization behavior, and the conditional 'similar items' carousel. It doesn't cover rate limits or error cases, but for a read-style tool this is solid context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loaded with the action, and every sentence adds value. It avoids redundancy and is appropriately sized for a simple one-parameter tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema and no annotations, the description fully compensates by listing all returned fields (description, photos, price, condition, brand, size, seller info) and noting the conditional carousel behavior. It also clarifies data sourcing, making the tool complete for an agent to select and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter, 'slug', is fully described in the input schema ('Depop item URL slug, e.g. from a search result's id field'). The tool description adds no new parameter syntax or format details, so we rely on the schema's 100% coverage, earning the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Get Depop item detail,' a specific verb+resource statement that clearly distinguishes this tool from sibling tools like depop_search and depop_shop. It further enumerates the exact fields returned, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by stating the slug comes 'from a search result's id field,' which tells the agent to use this tool after searching. However, it doesn't explicitly mention alternatives or when not to use it, so it misses explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries the full burden of disclosing behavior. It adds that the data is public and sourced from Depop's search API, which signals no authentication burden, and it reveals the response contains normalized listing summaries, a pagination cursor, and the total matching count. This provides meaningful context beyond the bare schema, though it doesn't mention rate limits or error behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no filler. The first sentence immediately names the action and resource, and the second packs the filter list and return value into one efficient and readable enumeration. Every phrase contributes useful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 14 parameters, no annotations, and no output schema, this description is complete enough for an agent to select and invoke it correctly. It specifies the search input, the meaningful filter dimensions, the normalization of results, and the pagination cursor behavior, while the input schema documents the remaining field-level details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so each parameter already has a semantic description in the schema. The prose description lists the available filter families but doesn't add format or values beyond the schema, so a baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Search Depop listings' — a specific verb and resource — and elaborates that it searches the resale-fashion marketplace by free-text keyword with optional filters, returning normalized listing summaries. This differentiates it from sibling search tools like depop_search_sellers and depop_search_facets by stating both the target ('listings') and the exact output shape.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly conveys that this tool is for finding listings by keyword and optionally narrowing with price, condition, category, brand, and similar filters. It does not explicitly name alternatives or when to prefer them, but the strong listing-centric framing and output description give an agent sufficient context for the common case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the burden. It describes the output (paginated credits with specific fields) and states the data source and credential-free nature, but omits potential rate limits or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first states the core function, second details return fields and data source. No redundancy, front-loaded, and each sentence serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description adequately explains the return format (paginated, specific fields) and data origin, making it complete for a listing tool with simple parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds marginal value beyond parameter names and types. It does mention pagination and default values, but does not deepen meaning significantly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List a Discogs artist's releases' with a specific verb and resource, and distinguishes it from sibling tools like discogs_artist and discogs_search by detailing the return fields.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions 'Credential-free official Discogs database data', implying public access, but does not explicitly compare with alternatives or state when to use this tool over others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the behavioral burden. It does this by describing the snapshot nature of the live-events response and explicitly disclosing that an empty `events` list is valid, preventing the agent from mistaking an empty result for an error. Additional detail about potential throttling or partial data would be useful, but this is already above the minimum.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and leads with the core statement, followed by contents and an edge-case note. The opening sentence 'DraftKings Sportsbook live events' is somewhat redundant with the second sentence, but the overall structure is clean and each remaining sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema, the description does a solid job of explaining the response essentials and a valid empty-result scenario. It could be more complete by specifying the structure of an individual event object, but for invoking this specific tool and consuming its high-level output, the agent has enough information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the input schema is fully covered and no parameter-specific semantics are required. The description avoids inventing parameter details that do not exist, so it satisfies the baseline for a no-parameter tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb, 'Returns', and a precise resource: live events currently shown by DraftKings Sportsbook. It enumerates the response contents (score state, period, primary markets, market categories), making the tool's function clear and distinguishable from related DraftKings tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It clearly establishes when the tool is relevant — to obtain current live events — and notes that an empty list is a valid outcome when no live events exist. It also hints at downstream use with /draftkings/sportsbook/event-markets, though it does not explicitly name alternatives such as draftkings_league_events for non-live event data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist; the description carries the full burden. It reveals that the data comes from ESPN's public JSON without credentials, indicating it is read-only and freely accessible. However, it omits details like whether rankings are current/historical, pagination, or rate limits, slightly limiting transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core action and resource. Every word serves a purpose: name, source, examples, and parameter constraints. No redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no output schema, two parameters with clear enum values), the description covers all essential information: what it returns, for which leagues, and data source. It is fully adequate for an agent to understand and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of parameters with descriptions, but they are generic ('Sport key', 'College league key'). The description adds concrete, actionable values (e.g., 'football' and 'basketball' for sport, specific league identifiers), saving the agent from guessing or looking up enums. This adds significant value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns poll rankings for college leagues, using a specific verb ("Returns") and resource ("poll rankings"). It distinguishes from sibling tools like espn_standings or espn_teams by specifying the exact domain (college leagues) and giving examples (AP Top 25).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly limits usage to college leagues and lists acceptable values for sport and league. It implies when-to-use (need poll rankings) but does not explicitly state when-not-to-use or mention alternatives among the many sibling ESPN tools. Still, the scope is well-defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full behavioral burden. It discloses the data source (H&M app-backend), the nature of the response (normalized products with pricing, colors, stock), and the crucial edge case that requesting beyond the last page yields an empty array rather than an error. It does not mention auth/read-only semantics, but the browse/return language makes safety non-problematic.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense and well-organized, covering the action, return shape, tag, parameter semantics, and a pagination edge case in four sentences. There is slight redundancy between the first and second sentences ('Browse' and 'Returns one category listing page'), but it is not padded and stays informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, so the description must explain what comes back, which it does (normalized products with pricing, images, colors, per-size stock). It also covers parameter sourcing and out-of-range page behavior. It does not enumerate sort options or output fields, but those are likely enough for a simple listing browsing tool and the schema covers most missing details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so a baseline of 3 is justified, but the description adds meaningful extra semantics for category_id (concrete slug examples and no look-up endpoint mention) and for page (real pagination, overflow behavior). These extras help an agent invoke the tool more correctly than the schema alone would.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
States an explicit verb and resource: 'Browse an H&M category's product listing.' It also defines the return content (normalized products with pricing, images, colors, per-size stock) and clarifies that it is a category-listing page, distinguishing it from product, category, or search tools. The scope is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Gives actionable context: category_id comes from known H&M storefront paths and there is no discovery endpoint, so the agent knows it must already have a slug. Also explains pagination semantics, which helps the agent interpret oversized page requests. It does not explicitly name alternatives like hm_search or hm_categories, but the context is clear enough for call selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden, and it delivers: it discloses the composite response structure (colors → sizes → price/availability), the conditional presence of ratings/reviews, and the concrete failure mode 'An unrecognized product_id returns 404.' It does not disclose potential review-count limits or how recent 'live' availability is, but the core call behavior and error path are well covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single dense passage but front-loads the core operation and then layers detail logically: what is returned, why siblings cannot substitute, how to derive product_id, and the 404 outcome. A few clauses could be tightened or reorganized for scannability, but no sentence is filler and the information hierarchy is sound.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a single required parameter, no annotations, and no output schema, the description does a thorough job describing what comes back, how to source the id, and what failure to expect. Minor gaps remain (e.g., review ordering/limits, whether price is current sale or list price), but for a 1-parameter product fetcher this is close to fully sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers the parameter 100%, so baseline is 3. The description adds genuine meaning beyond the schema: it clarifies that the numeric id can be extracted from the url field's 'productpage.<id>.html' segment—an actionable format hint an agent could otherwise miss when scraping the value. This extra context justifies the above-baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb and resource ('Get an H&M product's full detail') and then enumerates precisely what 'full detail' means: per-color pricing, per-size availability, aggregate rating, and reviews with specific fields. It explicitly differentiates itself from hm-listing and hm-search, telling the agent this richer data is not available there. There is no ambiguity about what this tool returns versus its siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly names the alternatives (hm-listing, hm-search) and the data they lack (per-size price, live availability, reviews), giving the agent a clear condition for selecting this tool. It does not state the inverse—when the lighter hm-listing/hm-search would be the better or cheaper choice—so the guidance is directional rather than fully exclusive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for setting behavioral expectations, and it does this well. It discloses that the recommendation lists genuinely vary by product, that some lists only appear when applicable, and that an unrecognized product_id produces a well-formed empty result rather than an error, which is exactly the kind of non-obvious behavior an agent needs to know.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The primary statement is front-loaded and immediately actionable: 'Get an H&M product's related items.' The following examples and edge-case note are genuinely useful rather than filler, though the parenthetical is slightly long relative to this single required parameter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-required-parameter, no-output-schema, no-annotation tool, the description is remarkably complete: it covers what is returned, how the returned lists vary, and how failures are represented as empty results. The main thing absent is a formal response shape, but the prose adequately describes the functional result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%: the schema already documents product_id as a numeric H&M product id sourced from a listing/search result's id field. The description adds little parameter-level meaning beyond reiterating that the tool relates to one product, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb and resource: 'Get an H&M product's related items.' It goes further by defining the exact scope as every product-detail recommendation list shown in H&M's own app, and the examples ('more from series', 'style with', 'alternatives', 'upsell') clearly distinguish it from a general product-detail or product-search tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is clear: when the agent has an H&M product_id and wants the related/recommendation lists shown on that product's detail page, this is the tool. It does not explicitly name sibling alternatives or exclusion cases, but the context is strong enough to avoid confusion with hm_product or hm_search.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full behavioral disclosure burden. It goes beyond a simple 'search' statement by describing output contents (pricing, images, colors, per-size stock, search-quality metadata), a spelling-correction feature, and pagination edge-case behavior. The only missing context is lower-level operational detail like rate limits, auth, or data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is 3 sentences and information-dense. It front-loads the core action, then covers output composition and edge cases. A small amount of redundancy exists between the first sentence and the opening of the second ('Search H&M product listings by free-text keyword' / 'Runs a free-text keyword search'), which prevents a 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, so the description compensates by summarizing return contents and search-quality metadata. It also handles the pagination contract and empty-result behavior, which are the most common sources of confusion in search tools. It does not claim a full field-level shape, but it provides enough context for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%: query, page, and page_size each already have clear descriptions including defaults and ranges. The tool description adds only mild value by framing query as free-text search and noting real page-based pagination, but the schema already covers the essential parameter meaning. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific action ('Search'), a resource ('H&M product listings'), and the mechanism (free-text keyword). It also distinguishes this tool from category browsing by explicitly describing that nonsense keywords return zero products instead of a fallback. Among H&M siblings like hm_search_suggestions and hm_categories, an agent can clearly tell what this one does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly contrasts this tool with category browsing, stating when to expect genuine empty results versus fallback sets. It also clarifies real page-based pagination and that out-of-range pages return an empty products array rather than an error. This provides enough when-to-use and when-not-to guidance without naming siblings directly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral burden. It explicitly discloses edge-case behavior: unresolvable search and no store within the radius both return well-formed empty results rather than errors. It also reveals that lat/lng bypass coordinate resolution and that radius_meters defaults to 10000.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
All sentences are relevant and front-loaded: purpose first, then parameter modes, defaults, and edge cases. There is a slight repetition of 'empty result rather than an error', but it is used for two distinct failure modes and does not erode clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a four-parameter tool with no annotations and no output schema, the description covers purpose, input alternatives, radius constraints, defaults, and error behavior. It names the return fields but not the exact output structure, which is a minor gap given there is no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3, but the description adds meaning beyond the schema by connecting parameters: search is resolved to coordinates, lat/lng skip that step, and radius_meters has a default and range. This provides the conditional logic needed to select the right invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description opens with a specific verb and resource: 'Find nearby H&M physical stores' and lists return fields (name, phone, full address, coordinates). This clearly distinguishes hm_stores from product/search/catalog siblings like hm_product, hm_search, and hm_categories.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states when to use this tool — to find nearby H&M physical stores — and explains the two input modes: 'Either search, or both lat and lng, is required.' It doesn't explicitly name alternative tools, but the physical-store scope and the parameter conditions give clear contextual guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the parallel probing behavior, that it reports only providers with non-empty boards, the output contents (open-role count and board URL), and that it is credential-free public ATS JSON. It also explains why Workday is excluded, providing useful behavioral context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, with the purpose stated first, then the operational detail, then the exclusion and auth note. Every sentence contributes unique information with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has one parameter and no output schema, and the description explains the return contents (providers, open-role count, board URL) and the query condition (non-empty board). The exclusion of Workday and the credential-free note round out the necessary context for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers the single parameter with a description 'Company careers slug to probe,' which already matches the description's use of 'by slug.' The description does not add any additional syntax, examples, or semantics beyond the schema, so it adds no value beyond the structured field.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Find which ATS a company uses by slug.' It enumerates the exact ATS providers probed and reports the result with open-role count and board URL, clearly distinguishing it from sibling tools that target a single ATS board (e.g., jobs_greenhouse_board).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It states the context: probing multiple ATS in parallel for a slug, and explicitly excludes Workday due to its additional requirements, which is a form of guidance. However, it does not explicitly compare against the single-ATS sibling tools, so the 'when to use vs alternatives' is implied rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context: 'Credential-free public GraphQL' (no auth needed), 'public' scope, and details on what is returned (full HTML description, compensation when available). This goes beyond a simple 'list' statement, though it does not cover all edge behaviors like pagination or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, roughly 40 words, with no fluff. The first sentence is a concise statement of purpose, and the second provides essential details about the posting content and the parameter derivation. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter listing tool with no output schema, the description is sufficient. It explains what the tool returns, how to specify the input, and the auth requirement. Given the low complexity, this is complete and comparable to high-scoring calibration examples.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single 'company' parameter, and the description reiterates the same guidance ('Gem vanity URL slug from its careers URL'). Since the schema already fully documents the parameter, the description adds no new semantic value beyond repetition, warranting the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists a company's Gem job board postings with inline detail. It names the specific platform (Gem/gem.com), distinguishing it from sibling job board tools like Greenhouse or Lever. The verb 'List' and resource 'Gem job board' are specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use the tool: to retrieve a company's public Gem board postings. It also explains how to identify the company parameter (Gem vanity URL slug from careers URL). However, it does not explicitly mention alternatives or exclusions, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that the tool is credential-free, public, and returns JSON. It also notes normalization to a shared shape, but doesn't mention rate limits or pagination.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the main action, and every sentence adds essential information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter list tool, the description covers purpose, parameter sourcing, optional behavior, authentication, and output standardization, making it fully self-contained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds value by explaining the token is the 'Greenhouse board slug from its careers URL' and that content=true includes full HTML descriptions, which is not in the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and the resource 'a company's Greenhouse job board', and normalizes to a shared Job shape, distinguishing it from sibling tools like jobs_greenhouse_job which likely retrieve individual jobs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains where to get the token (careers URL slug) and how to use the content parameter, but does not explicitly contrast with other ATS board tools (e.g., jobs_lever_postings) or state when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses that the tool is credential-free, uses public ATS JSON, and that breakdowns are computed over fetched postings. It does not detail pagination, error handling, or provider-specific limitations, but covers the key access and computational traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the main purpose, and includes only relevant details. Minor redundancy between the first two sentences ('Aggregate hiring signals' vs 'Aggregates... hiring snapshot') but otherwise efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex tool with 10 parameters, no output schema, and no annotations, the description covers purpose, parameter selection, computed metrics, and credential-free access. It does not specify exact output field names, but enumerates the metrics returned, making it reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds value by grouping parameters by provider type ('token / company / org / tenant+datacenter+site / domain'), clarifying that only provider-relevant params are needed. This goes beyond individual schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool aggregates a company's ATS board into a hiring snapshot with specific metrics (total open roles, breakdowns by department/location/title, remote share, new roles in 7/30 days). This distinguishes it from sibling tools that fetch raw job data (e.g., jobs_greenhouse_board, jobs_workday_board).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides usage context ('Aggregate hiring signals... a leading indicator of company growth') and instructs to supply provider plus provider-specific slug params. However, it does not explicitly state when to prefer this over sibling board-fetching tools or list exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses return format (full HTML/text description) and authentication status (credential-free, public ATS JSON). Minor gap: no mention of error handling or validity checks.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, zero waste. Verb and resource are front-loaded. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 2-parameter tool with no output schema and no nested objects, the description fully covers purpose, return type, and access requirements. Complete for the complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are well-defined. The description adds no extra meaning beyond the schema; baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('a single Lever posting'), and distinguishes from siblings like `jobs_lever_postings` by emphasizing singularity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving one posting by ID, but does not explicitly state when to use versus listing tools or provide exclusions. The 'Credential-free public' note adds context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses that the tool is 'Credential-free public data' and uses 'an anonymous, login-free session', which effectively tells the agent no authentication is needed. It also describes the data normalization, though it omits potential rate limits or pagination details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary action, and every sentence adds value: first states the purpose, second details the output and auth nature. No redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool, the description is complete. It names the return fields ('title, price, thumbnail, condition, seller'), specifies the data source (Mercari mobile app API), and notes the credential-free access. No output schema exists, so this textual description fully compensates.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so schema coverage is trivially 100%. The description does not need to explain parameter meaning; it focuses on the output. The baseline for 0 params is 4, and the description appropriately does not invent parameter guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as 'Get Mercari home feed' and explains it returns 'Mercari's own curated home-feed recommendations', which is specific and distinct from siblings like mercari_search or mercari_item. It names the resource and the result.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for fetching a general recommended feed ('curated home-feed recommendations') but does not explicitly state when to use this versus search or item lookup, nor any exclusions. No alternative tools are named.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden. It discloses credential-free access, anonymous anonymous login-free session, and data source (Mercari's mobile-app API). It also describes the return format (normalized listing summaries plus total matching count), offering useful behavioral context beyond a bare 'search'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose and immediately providing key details about input, output, and data source. No filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter and no output schema. The description covers what it returns (summaries + count), authentication requirement, and data source, which is sufficient for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the parameter description 'Free-text keyword search' matches the description's 'free-text keyword'. The description does not add additional meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'Searches Mercari listings' with a specific verb and resource, and adds scope via 'free-text keyword'. It distinguishes from sibling tools like mercari_item and mercari_autocomplete by specifying keyword search over listing search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context: search the live resale marketplace by keyword. It doesn't explicitly name alternative tools or state when NOT to use it, but the keyword-search-specific language makes it obvious that other tools handle item details or autocomplete.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full transparency burden. It discloses the data source (live mirror of Nike.com's nav mega-menu), the exact governance of the data, and the important caveat that seasonal/promotional groups are included without distinction. It does not mention rate limits, caching, or lack of freshness, but the key behavioral risk—promotional vs structural taxonomy—is explicitly disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is longer than a typical tool description. It front-loads the main purpose and then expands details relevant to an agent that will use the taxonomy to power later browsing calls. However, the internal examples of Women/Shop by Color, Jordan organized by Men/Women/Kids, and the slogan note add grit but are slightly beyond the threshold of conciseness and necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Since there is no output schema, the description carries the full burden of explaining what the agent receives, and it does so richly: top-level entries, group breakdowns, subcategory entries, slugs, and URL patterns. The main omission is the concrete JSON data shape (e.g., whether the tree is nested or flat, what fields look like), which the agent would only learn from the actual response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero properties and zero required parameters, so the parameter-semantics burden is minimal. The description correctly avoids talking about parameters and instead spends the space on the meaning of the taxonomy tree, which is the right trade for a 0-parameter tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb 'List' and a specific resource: Nike's category/subcategory taxonomy. It clearly distinguishes this tool from search, product, review, and store siblings, and enumerates the exact top-level categories (Men, Women, Kids, Jordan) and the origin of the data (Nike.com mega-menu).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly shows when to use this tool: when an agent needs Nike's taxonomy tree or slugs for downstream category browsing (explicitly stated as usable input for a future category-browse endpoint and directly browsable today at nike.com/w/<slug>). It does not explicitly name alternative tools to avoid, but for a 0-parameter list tool the usage context is quite clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses the tool is credential-free and returns specific indices, covering key behavioral aspects for a simple retrieval tool. It lacks details on rate limits or response structure but is adequate given simplicity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences with no wasted words, front-loaded with the main purpose. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool without an output schema, the description is mostly complete, stating the resource, returned data, and public nature. It could mention that the ranking covers all countries or ordering, but overall sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist and schema coverage is 100%, so the description need not add parameter meaning. The description adds value by listing the indices returned, earning a top score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves the global Numbeo cost-of-living country ranking, specifying the indices included. This distinguishes it from sibling tools like city-level or country-specific cost-of-living tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for global country rankings but does not explicitly guide when to use this tool versus alternatives like city-specific or indices tools. No when-not-to-use or alternative tool names are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It states 'credential-free public season page' (no auth needed) and lists returned data types. However, lacks details on side effects, rate limits, or caching behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first states purpose and return content, second gives parameter usage rule. No unnecessary words, front-loaded with essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the description lists what is returned, it lacks details on output structure (no output schema). Given the complexity of season data, more information about return format could be helpful. Otherwise adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with descriptions for both parameters. The description adds the crucial constraint 'Pass exactly one of path or url', which is not in the schema, providing significant added value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'Rotten Tomatoes season detail' with specific data types (metadata, scorecard, parent series, episodes). It distinguishes from siblings like rottentomatoes_episode and rottentomatoes_series by targeting season-level data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear instruction to 'Pass exactly one of path or url', which is critical since the schema doesn't enforce this. No explicit when-to-use or exclusions, but the purpose implies use for season details.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears the burden of behavioral disclosure. It states the tool is credential-free, public, and explains pagination behavior (paging past total returns empty page). It lacks explicit read-only declaration but implies it.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph but concise and front-loaded. It covers all key aspects without verbosity. Could benefit from structural separation but remains effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 18 parameters, no output schema, and no annotations, the description is fairly complete. It explains the browsing nature, filtering, pagination, and credential-free access. It gives a hint about response rows. Missing error handling but acceptable for a browse tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining pagination edge cases and tag resolution, which goes beyond the schema. It also contextualizes parameters like filter as 'curated preset'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool browses the Steam store by community tag and store facets, explicitly noting 'no free-text term', which distinguishes it from sibling tools like steam_search. It specifies the verb and resource precisely.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains how to use the tool, including filter options, sorting, and pagination. It mentions resolving tag ids via /steam/tags/list. While it doesn't explicitly state when not to use it, the differentiation from free-text search is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that the tool is credential-free and public, and returns popular community tags. No annotations exist, so no contradiction. Lacks details on pagination or rate limits, but adequate for a simple list.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, no filler. Front-loaded with action and return content. Every sentence adds essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Describes return format (numeric id + localized name), purpose, and parameter usage. No output schema exists, but description covers what the agent needs to know. Complete for a simple list tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Single optional parameter 'l' for language is fully described in both schema and description, which adds context that it controls localization of tag labels. Schema coverage is 100%, so description adds marginal value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool lists Steam community tag ids and names, with specific purpose to map tag names to IDs for /steam/tags and /steam/category. Distinguishes from sibling tools like 'steam_tags' which likely applies tags.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly explains the use case: mapping a tag name to its ID for downstream endpoints. Does not mention when not to use or alternatives, but the context is sufficiently clear for a straightforward listing tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the data is credential-free, public, sourced from StockX's own GraphQL API, and returns a normalized product. This goes beyond a simple 'get product' statement, but it does not address rate limits, error conditions, or data freshness—minor gaps for a read-only lookup.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the purpose ('Get StockX product detail') then uses a parenthetical list to enumerate all return sections. Every clause adds value: the data categories, the credential-free note, and the source API. No filler or redundant phrasing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (multiple data categories returned) and the absence of an output schema, the description is exceptionally complete. It lists every major return component (identity, market data, listings, related products, badges), specifies the public/credential-free nature, and names the underlying API. An example slug would be the only minor addition, but the schema parameter description already covers that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'slug' is fully described in the schema with a precise explanation (URL path segment). Since schema coverage is 100%, the description adds no new parameter-level detail. The description's mention of 'normalized' is about output, not parameters. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb and resource: 'Get StockX product detail.' It enumerates exactly what is returned (identity, market data, seller listings, related products, badges), distinguishing it from sibling tools like stockx_search (which find products) and stockx_brands/categories/releases (which return lists). The purpose is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context that this tool is for retrieving a single product's details when you have a slug, but it does not explicitly mention alternatives or exclusions (e.g., 'use stockx_search to find products'). Since the parameter schema already explains the slug, the intended use is strongly implied, though not spelled out in contrast to siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure and excels: it reveals the TikTok One login gating for the true result-set, the anonymous 4-video page-1 limit regardless of sort/period, uneven country coverage, and that empty videos arrays are genuine no-data responses rather than errors. This is exemplary beyond what annotations could provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The content is dense and each of the two behavioral sentences earns its place with high-value caveats. However, the opening is redundant: 'Retrieve TikTok Creative Center trending videos' followed immediately by 'Returns TikTok Creative Center's ranked trending videos' repeats the same idea, preventing a top score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description compensates by explaining key response characteristics: total_count/page_count fields, the fixed 4-video anonymous page, and the possibility of an empty videos array for unsupported countries. It does not describe the shape of individual video entries, which is the only notable remaining gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description references country, period, and sort order in the context of the anonymous-access limitation and points to total_count/page_count in the response, but it adds no parameter-level format, valid-value, or detailed behavioral guidance beyond the schema's brief definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Retrieve') and names a precise resource ('TikTok Creative Center trending videos'), then states exactly what is returned: ranked trending videos for a country, period, and sort order. It clearly distinguishes this tool from related siblings like tiktok_trending, tiktok_search, or tiktok_top_ads_list by anchoring on the Creative Center dataset.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear decision-relevant context: anonymous requests only get page 1 (4 videos), and only US, JP, ID, VN, and TH reliably return populated results. This effectively tells the agent when the tool will be useful. However, it never explicitly names alternative tools or states when-not-to-use scenarios relative to siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral burden. It states the tool is 'credential-free' and 'public', and lists the return fields. This provides important context about auth and data content, though it omits rate limits or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no extraneous words. The first sentence states the core action, the second lists return fields and credentials. Highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool (single parameter, no output schema), the description adequately covers what the tool does, what it returns, and its public nature. No gaps for typical use cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema describes the 'id' parameter minimally. The description adds meaning by explaining what the returned data contains (overview, tagline, etc.) and that it is normalized TMDB data, going beyond the schema to help the agent understand the tool's output.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'TMDB TV show', and lists the data fields returned. It implicitly distinguishes from tmdb_tv_list and tmdb_search by focusing on a single show retrieved by ID.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like tmdb_search or tmdb_tv_list. The description implies it is for fetching a single show by ID, but does not state prerequisites or exclude other use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the full behavioral disclosure burden, and it does so well. It discloses that the source is Twitch's search-typeahead surface, that results are a capped suggestion list rather than a fully paginated results page, and that live channels include viewer count and stream title. This gives the agent material behavioral expectations beyond the raw search operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each earning its place: purpose, results shape, and source/limitation. The content is front-loaded and free of filler, making the critical caveat easy to weigh.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity search tool with no output schema, the description provides enough behavioral and result context to invoke it correctly. The capped, non-paginated caveat is especially important because an agent could otherwise attempt pagination or assume exhaustive search coverage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%: query and limit are already described in the input schema, including the default and maximum for limit. The description does not add additional meaning or syntax guidance for the params, so it stays at the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: search Twitch channels and games/categories. It further clarifies that results are a mixed set of channel and category matches, which distinguishes it from more targeted siblings like twitch_channel, twitch_streams, or twitch_top_games.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives useful context: this is a lightweight typeahead-style search, capped and non-paginated, so it should be used for quick discovery rather than exhaustive result collection. However, it does not explicitly name alternative tools or state when-not-to-use scenarios, so the guidance is implied rather than fully articulated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the behavioral burden. It discloses that this is a paginated endpoint, that it returns one page at a time, that it starts at an offset, and that the data is public from Twitch's GraphQL API. This is valuable transparency. It doesn't mention rate limits or return format, but the pagination disclosure is more than typical.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is reasonably concise and front-loaded with the main purpose. Each sentence adds information: what it does, how paging works, and the data source. No filler. Minor omissions like an explicit page size hint or rate-limit note would improve completeness, but the structure is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with two parameters, a required schema description, and no output schema, the description covers the critical operational details: how to start and how to paginate. It lacks any statement about response structure, max page size, or rate limits, but given the complexity is low, a 4 is fair.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters clearly. The description adds the crucial pagination semantics by explaining that offset_seconds from a returned comment becomes the next request's offset. This is extra meaning beyond the schema that helps an agent correctly paginate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets a Twitch VOD's chat replay, a specific resource and verb. It also explains it returns one page of past-broadcast chat messages starting at a given point, which distinguishes it from other Twitch tools and gives a specific sense of its function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains how to use it: start at a given point and paginate by re-requesting with the last returned comment's offset_seconds. This is a clear usage pattern. It doesn't explicitly mention when not to use it or name an alternative, but the pagination guidance is strong and practical.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It discloses valuable behavioral details: real page-based pagination, guided-navigation filtering, the discoverability of facet codes, and a 404 for unrecognized categories. It does not describe the output shape, but for a browsing operation this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense and mostly efficient, but the opening two sentences slightly duplicate each other ('Browse an Ulta Beauty category page' followed by 'Browses an Ulta Beauty category page's product grid'). Still, every key detail has a place and the examples are compact.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description is the only guidance. It covers parameter formats, filtering behavior, pagination, and the failure case. It does not fully describe the response structure, but it does mention the product grid and facets response fields, which is enough for a competent agent to understand prior expectations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds useful semantics beyond the schema: category accepts either a path or copied URL, filter uses either a single facet code or comma-joined combination, and valid filter values are directly available in the response's facets field. These examples make calling correct.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action and resource: browsing an Ulta Beauty category page's product grid. It names the key distinguishing behavior (real page-based pagination and guided-navigation filters), which separates it from sibling tools like ulta_categories or generic search tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives concrete usage guidance: category accepts a category path or full URL copied from Ulta navigation, filter expects a specific facet-code shape, and valid codes should be discovered from the category's own facets field. It does not explicitly contrast with sibling tools, but the intended context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It goes beyond generic search behavior by disclosing real page-based pagination, normalized product output, genuine empty results for nonsense keywords, and empty results instead of errors for out-of-range pages. These are valuable, non-obvious behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded and efficient, with edge-case behaviors clearly stated. However, the first two sentences are slightly redundant — 'Search Ulta Beauty products' and 'Searches Ulta Beauty's product catalog by keyword' — so not every sentence earns its place fully.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter search tool with no output schema and no annotations, the description covers the purpose, return fields, pagination behavior, and edge cases. It does not specify page size or sort order, but these are not necessary for correctly invoking the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers 100% of the two parameters, including descriptions for query and page. The description reinforces 'keyword' and 'page-based pagination' but does not add meaningful new semantic detail beyond what the schema provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Search Ulta Beauty products' and elaborates that it searches the catalog by keyword, returning normalized products with brand, pricing, rating, and review count. This clearly distinguishes it from sibling tools like ulta_category, ulta_product, or ulta_suggest.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It clearly frames when to use the tool by specifying keyword search of Ulta Beauty's product catalog and real page-based pagination. However, it does not explicitly name or exclude alternatives such as ulta_category or ulta_product, so no when-not guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden and does well: it enumerates the returned fields, discloses per-variation detail, and explicitly states that an unrecognized id returns 404. It does not cover rate limiting, caching, or auth, but those are minor considerations for a single-product read tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences economically cover return values, id provenance, and error behavior; information is front-loaded. The slight repetition of 'full detail' in the first two sentences is the only minor waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter lookup, the definition is almost complete: it says exactly what the id is, where to get it, what the return includes, and what happens with an invalid id. Since there is no output schema, the field list is the main completeness element, and it is present.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and already specifies the id as a 24-character hex string. The description adds meaning by naming both valid id sources — a search result's product_id and a product page's URL — which helps an agent understand how to obtain the parameter in practice.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear, specific verb and resource: 'Get a Wish product's full detail.' It then names the returned content (name, price, sold-out state, rating, images, variations), which separates it from search/reviews/related sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides clear usage context: the id comes from a search result's product_id field or a product page's URL, so this is the detail lookup step after searching. It does not explicitly name alternative tools or state when not to use this for reviews or related products, but the workflow intent is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full behavioral burden. It discloses the edge case of zero reviews returning an empty result instead of an error, explains the pagination limitation with a reason (upstream doesn't support offset/cursor), and notes reviews are normalized. It doesn't describe the review payload structure or error scenarios beyond zero reviews, but the disclosed edge cases are genuinely useful.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is mostly compact and the key facts are front-loaded. The only minor redundancy is the first two sentences both stating the same thing: 'get reviews' and 'returns reviews'. The remaining sentences each add distinct value: id source, zero-result behavior, and pagination guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter tool with no output schema, the description covers what's needed to invoke correctly: realistic resource, id provenance, count behavior, and edge case handling. The only gap is that it doesn't describe the actual review payload fields (e.g., rating, text, author), but the invocation and expected return pattern are clear enough for an agent to call and interpret the result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds important semantic nuance by explaining that count is the only pagination mechanism (since offset/cursor is unsupported) and by giving the id provenance (from search result or URL). This goes beyond the schema's basic '24-character hex id' description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Get' and the resource 'Wish product's customer reviews', which distinguishes it from the many sibling product-review tools (e.g., walmart_product_reviews, bestbuy_product_reviews) by naming the Wish platform. The resource boundary is immediately obvious even without opening the schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides practical guidance: the id is sourced from a search result's product_id or a product URL, and when more reviews are needed, the caller should re-request with a larger count. It explicitly states this endpoint does not support offset/cursor pagination, which is a clear 'when-not' instruction. It doesn't name alternatives for other platforms, but the Wish-specific scope makes that less necessary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly states that the tool returns the full article content and lists exactly which fields are included. It also discloses the input requirement (canonical URL). While it doesn't mention failure modes or read-only behavior explicitly, for a simple content fetcher this is sufficient and does not hide any surprising side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences and front-loads the purpose, then lists the exact content fields and input requirement. It is concise with no fluff, though the first sentence could be considered slightly redundant with the tool name, but the field enumeration and URL guidance justify its existence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no annotations and no output schema, the description is reasonably complete: it names the output fields, the input type, and the canonical URL source. An agent knows what to provide and what to expect in return. Missing details such as error behavior or how to handle non-Autos URLs are minor for this straightforward fetch tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds value by clarifying what constitutes a valid 'canonical' URL and providing a concrete source example ('such as one returned by the home or category story streams'). This gives the agent useful guidance beyond the schema's simple 'Canonical autos.yahoo.com article URL'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Returns') and resource ('a single Yahoo Autos article's full content'), and explicitly enumerates the fields returned (title, author, body paragraphs, etc.). It clearly distinguishes from siblings like yahoo_autos_home and yahoo_autos_category by specifying 'single article' and 'canonical autos.yahoo.com article URL', making the tool's scope unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides concrete guidance on when to use the tool: when you have a canonical autos.yahoo.com article URL, specifically one returned by the home or category story streams. It does not explicitly exclude alternatives (e.g., other yahoo_*_article tools), but the domain and input type make the intended use clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full disclosure burden. It does well by revealing the data source (the retailer's shopping.yahoo.com store page's structured product data), the fixed scope of the result set, and that it is not a keyword search. It does not discuss failure modes, caching behavior, or availability limitations, but for a simple single-retailer lookup that is a minor gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficient and front-loaded. The first sentence states what the tool does, the second defines the output fields, the third gives the data source and scope, and the last provides the needed prerequisite. Every sentence earns its place, with no repetition or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a single required parameter and no output schema, the description adequately explains what will be returned, what the result set represents, where the data comes from, and how to obtain the required store slug. The tool is simple and the description covers everything an agent needs to select and call it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There is only one parameter and the schema already documents 'store' as the retailer slug from GET /yahoo-shopping/stores, so schema description coverage is 100%. The description reinforces this by instructing the agent to find the slug via GET /yahoo-shopping/stores, but it does not add new meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns one retailer's current deals on Yahoo Shopping and enumerates the exact fields returned for each offer: product title, direct retailer product URL, image, brand, currency, price, and sale price. It also differentiates this from a keyword search tool, which helps distinguish it from similar shopping siblings like yahoo_shopping_stores.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives concrete practical guidance by telling the agent to use GET /yahoo-shopping/stores to find a retailer's slug before using this tool. It also clarifies that this endpoint returns a fixed set of currently-featured deals rather than a keyword search. However, it does not explicitly name alternative shopping/search tools or state when to prefer them over this one.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the behavioral burden. It makes clear the tool is a read-style operation: it returns articles with specific fields from sports.yahoo.com's server-rendered news page. However, it does not disclose pagination, article count, ordering, freshness limits, or behavior for invalid league keys, so some behavioral gaps remain.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded: the purpose is in the first sentence, return fields come immediately after, and the parameter value list is the only long section. There is no boilerplate or filler. The long enum list earns its place because the schema leaves the accepted values undocumented.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter tool with no output schema, the description already gives the output shape, the source page, and the canonical league values. The main missing context is article count/pagination and whether the result is a fixed-length feed, but a caller can still invoke the tool correctly with what is provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only describes `league` as "League key", but the description provides the complete, authoritative list of accepted league identifiers such as `nfl`, `nba`, `mls`, and many more. Without that list, a caller would have to guess the value. This materially exceeds what the input schema alone communicates.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a concrete resource and action: it returns recent news articles for a Yahoo Sports league, and even lists the returned fields (title, summary, author, published time, link). This clearly differentiates it from sibling tools like yahoo_sports_scoreboard or yahoo_sports_standings, which expose different data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the intended use: call this when you need recent league-level news from Yahoo Sports, and use the `league` parameter to pick the specific league. It does not explicitly name alternatives or say when not to use it, but the league-news framing and the source mention provide enough situational context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full transparency burden. It discloses the data origin (server-rendered rankings page), what is returned, and the lack of player IDs. However, it omits details like rate limits, freshness, pagination, or failure modes, which leaves non-trivial behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences with no filler: a lead-in, the returned content, and a critical constraint. Every sentence carries useful information and is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter read-only ranking tool with no output schema, the description is nearly self-sufficient: it specifies the parameter choices, the output shape, and a data caveat. It could further describe pagination/limit behavior or explicit formatting, but those are minor given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only says 'Rankings type' and has no enum defined. The description is what actually turns this into an actionable parameter by listing the four accepted values (mens-singles, womens-singles, mens-doubles, womens-doubles), giving the agent exactly what it must pass.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: it returns an ATP/WTA singles/doubles tennis ranking list, enumerates the output fields (rank, points, player name, country, age), and pins the source to Yahoo Sports' server-rendered rankings page. This clearly distinguishes it from related tennis schedule and scoreboard siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Clearly communicates the exact accepted type values and a key constraint (no stable player ID available), which guides correct invocation. It does not explicitly route users away from alternative tools, such as saying 'use scoreboard for match results,' so the guidance is implicit rather than exhaustive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It usefully explains that the response is a flat list of suggested phrases, that it contains no product data, and notably that a partial query with no real matches returns an empty result rather than an error. This goes beyond what a schema could convey, though it does not address rate limits, authorization needs, or exact serialization; those are less critical for a simple reads.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences cover: the tool's purpose, the type of returned data, and the no-match behavior. There is no repeated content, and the most important information is front-loaded. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-param tool with no output schema and no annotations, the description fully specifies the behavior: it tells the agent the input is partial, the output is a flat list, the content is 'search phrases', and that no-match calls return an empty result instead of error. Nothing required for calling this tool appears missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the only parameter (query = 'Partial search query'). The description calls it a 'partial query' but adds minimal semantic detail beyond the schema. By the rubric, full coverage defaults to 3, and the description does not add meaningful new parameter-level information to raise the score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb ('Get'), a specific resource (Zappos search-box suggestions), and a unique scope (typeahead for partial queries). It explicitly differentiates itself from full product search by saying 'no product data' and describes the response shape as a flat list of phrases, so an agent can distinguish it from zappos_search and similar siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly identifies that this tool is for partial-query typeahead suggestions and indicates this is not a product search. It does not explicitly name an alternative tool or state 'when not to use this tool,' but the 'no product data' phrasing and the partial-query mention provide enough contextual guidance for an agent to know when it is appropriate. It lacks an explicit exclusion for full product search, so it does not reach a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for behavioral disclosure. It reveals key traits: the data comes from Zara's own category browse source, is not paginated, always returns the complete listing, and uses color-variant-level entries rather than product families. This prevents agents from misinterpreting pagination or grouping semantics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is slightly long but every sentence serves a purpose: scope, source, pagination behavior, and color-variant semantics. The key behavioral detail (no pagination) appears early, and there is no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Even without an output schema, the description gives a clear picture of what is returned: normalized products, pricing, images, availability, and one entry per color variant. It correctly directs agents to zara-categories to obtain a valid categoryId. It does not preview potential error cases, but for a one-parameter read tool this is largely sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents categoryId completely. The description mainly echoes that categoryId is a numeric id from zara_categories. It adds no additional semantics beyond what the schema already provided, but the schema is sufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb+resource combination: 'Browse a Zara category's product listing.' It further specifies what is returned (full product listing with pricing, images, availability) and distinguishes itself from related tools like zara_categories and zara_product by describing the exact nature of this listing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description tells the agent how to get a categoryId ('from zara-categories') and states that this endpoint returns the full listing in one call, unlike a paginated endpoint. It does not explicitly contrast with zara_search or zara_product, but the context is strong enough that an agent can infer when to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the full burden of disclosure, and it does so reasonably well: it tells the agent exactly what the response contains (color variants, real marketing descriptions, per-size inventory, image galleries) and documents an error case ('unrecognized productId returns 404'). It doesn't cover auth, rate limits, or pagination, but for a single-id lookup tool with no output schema, the behavior is disclosed well enough for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
At roughly two sentences, the definition is brief and front-loaded with the core action and output composition. There is minor duplication — 'Get a full product detail' is restated as 'Returns a full product detail' — but every component (returned fields, sibling differentiation, id derivation, error behavior) earns its place in a compact form.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter id-based lookup with no output schema, the description provides most of what an agent needs: what is returned, where the id comes from, and what happens on bad input. It also names the neighboring summary tools, which helps an agent decide when to call the detail endpoint. Minor gaps, such as whether stock is numeric quantities vs availability booleans and whether prices are included, don't seem fatal given the descriptive list already given.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents productId's has 100% coverage, so the baseline is 3. The description adds extraction guidance that is genuinely beyond the schema — specifically that productId is the digits after '-p' in the product-detail URL. This tells an agent how to transform a natural-language URL reference into a callable argument, which raises the value above baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource pair — 'Get a Zara product's full detail' — and then enumerates exactly what that detail contains (color variants, marketing description, per-size stock, image gallery). It also differentiates the tool from zara-category-products and zara-search by describing its output as 'richer' than their summaries, so an agent can disambiguate at a glance.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description names the alternatives (zara-category-products and zara-search) and implies the condition for choosing this tool: pull up a full detail view when summaries are insufficient. It also communicates the prerequisite workflow by explaining that productId comes from a search/category result's url field. It stops short of explicitly stating when not to use the tool or framing the choice as an if/else decision.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses behavioral nuances: keyword fallback to resolved city name, city_id precedence, and credential-free public data sourcing. It stops short of describing pagination or result format, but for a search tool this is notably transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, each packed with distinct information. Front-loaded verb and resource, no fluff, and the fallback/precedence rules are stated compactly without repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (3 optional params, no output schema), the description covers the main invocation patterns and parameter interactions. It could mention result structure or limits, but the core selection criteria are well addressed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema already covers all three parameters with descriptions, but the description adds meaningful behavioral semantics: how keyword omission triggers city-name search, and the city_id > city precedence rule. This goes beyond simple parameter mapping.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Search Agoda activities' and clarifies the result type as 'tours, attractions, experiences'. This clearly distinguishes the tool from the sibling agoda_activity_detail (which retrieves a single activity) and other Agoda search tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear usage context: can search by keyword and/or city, fallback to city name when keyword is omitted, and city_id precedence over city. However, it does not explicitly name alternative tools or state when not to use this tool, so it misses the top tier for explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the credential-free nature (no auth required), the fact that results include full descriptions and qualifications, and the exact sort semantics (relevant vs recent). It also clarifies that category works standalone. This is substantial behavioral information, though it doesn't cover pagination limits or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at roughly 100 words, front-loaded with the tool's purpose, and each sentence provides essential information: purpose, output content, sort options, and the q/category requirement. There is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 6 parameters, no annotations, and no output schema, the description covers the critical aspects: data source, auth-free access, result contents, sort values, and the q/category constraint. It doesn't describe pagination controls (though page/limit are in the schema) or return envelope details, but the provided information is sufficient for an agent to make informed calls.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents all 6 parameters with descriptions (100% coverage), so the baseline is 3. The description adds value by enumerating the valid sort values (`relevant` default and `recent`) and explaining that category can be used without a text query, which is not clear from the schema alone. This additional context justifies a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches Amazon's public careers site (amazon.jobs) via a credential-free JSON API, distinguishing it from other search tools like amazon_search (product search) and amazon_jobs_job (likely job detail). The verb 'searches' and explicit resource make the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool: to search Amazon's public careers site. It also includes important usage constraints like the need to provide either q or category, and explains that category can work with no text query. However, it doesn't explicitly name alternative tools or when not to use this tool, so it falls short of a perfect score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently enumerates what is included (editorial shelves like New Shows, New Seasons, Essentials) and what is excluded (charts-mirroring shelves), adding context beyond basic read behavior. It does not mention pagination or return structure, but the core behavioral scope is clearly defined.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, both dense with relevant information. The first sentence states the purpose and likely content, while the second explains the scope exclusion without any redundant phrasing. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter read tool with no output schema, the description sufficiently covers the main aspects: what it returns, examples of content, and the exclusion of charts-mirroring shelves. It could benefit from more detail on the return structure (e.g., shape of a shelf), but the examples and scope are enough for an agent to decide whether to use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides a clear description for the `country` parameter ('Two-letter storefront country code'), covering 100% of parameters. The tool description adds minimal parameter-specific value, though it does reference the URL pattern with `{country}`, which reinforces the parameter's role. Baseline 3 is appropriate given the high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb and resource: 'Retrieve Apple Podcasts curated "New" editorial shelves.' It provides concrete examples of what the shelves contain and explicitly distinguishes itself from sibling tool `/apple-podcasts/charts/rankings` by noting it omits charts-mirroring shelves.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit usage guidance by stating that charts-mirroring shelves are omitted and pointing to `/apple-podcasts/charts/rankings` as the alternative for that data. This clearly tells the agent when not to use this tool and which sibling covers the other case. The first sentence implies the intended use case: retrieving curated editorial 'New' shelves.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full disclosure burden. It explains the data is sourced from Best Buy's own 'Name Brands' page, identifies the returned fields, and even documents the downstream compatibility of IDs. It doesn't mention pagination or response formatting, but for a simple full-directory retrieval this is reasonably transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the main purpose. It does contain minor redundancy—"Get Best Buy's full brand directory" and "Returns Best Buy's full brand directory" overlap—but the remaining details about the source and downstream ID usage earn their place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter directory-listing tool with no output schema, the description supplies the essential context: what is returned, the field names, the source of truth, and how to use the IDs in a related tool. Nothing material is missing for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, which means there are no input ambiguities for an agent to resolve. The schema description coverage is complete by virtue of having no properties, so the description does not need to add parameter-level details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: "Get Best Buy's full brand directory." It also states the returned data shape (name, category id, url), which makes what the tool does immediately clear and distinguishes it from sibling tools like bestbuy_categories or bestbuy_product.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: use this tool when you need Best Buy's full brand directory, and it explicitly explains how the returned IDs feed into bestbuy_category. It doesn't list excluded cases or alternative tools explicitly, but for a zero-parameter reference-list tool that context is sufficiently actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool returns 'normalized release rows' (output behavior), that it accesses a 'public' page (implying no auth required), and that exactly one of id/path/url must be passed (input validation). It does not cover rate limits or error behavior, but for a read-only data retrieval tool, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loaded with the tool's purpose and followed by a necessary usage constraint. Every sentence earns its place with zero waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema or annotations, the description covers the core functionality, the input selector constraint, and the public nature of the data. It mentions the output type ('release rows') but doesn't detail the row structure or pagination behavior. For a simple fetch tool, this is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the parameters are already documented. The description adds meaningful constraint beyond the schema: 'Pass exactly one of id, path, or url,' which is critical for correct invocation and is not expressed in the schema's optional fields. This elevates the score above the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Box Office Mojo franchise detail. Returns normalized release rows from a public Box Office Mojo franchise page.' It uses a specific verb+resource combination and distinguishes itself from sibling tools like boxofficemojo_franchises (list) by focusing on a single franchise's detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context that this tool is for retrieving franchise details and gives an explicit input constraint: 'Pass exactly one of id, path, or url.' However, it does not explicitly state when to use this tool over alternatives or mention exclusions, so it lacks explicit when/when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that suggestions are fetched from public Brave Search suggest JSON and trimmed to the requested count. Locale defaults are also stated. Does not mention authorization or rate limits, but for a suggest endpoint, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each providing essential information: purpose, return value, defaults, and source. No redundant or irrelevant content. Front-loaded with the primary action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and 4 well-documented parameters, the description covers the core functionality. It explains the data source and trimming behavior. Missing details on return format (e.g., list of strings) and error handling, but these are inferred for a suggest tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds extra context: 'query prefix' for q, 'trimmed to the requested count' for count, and locale defaults for country/lang. This goes beyond the schema descriptions, justifying above baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool suggests Brave search queries and returns autocomplete completions for a query prefix. It uses specific verbs ('Suggest', 'Returns') and distinguishes from sibling tools like brave_search by specifying 'autosuggest query completions'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for autocomplete without explicitly stating when not to use. However, the mention of 'autosuggest' and 'query prefix' makes it clear this is not for general search results. Does not name alternative tools like brave_search, but context with siblings signals its specific role.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and does an excellent job detailing the returned fields (e.g., Superhost share, Guest Favorite share as lower bound, avg_person_capacity, currency conversion notes, and 404 for suppression). It discloses behavioral traits thoroughly.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core action and then enumerates return fields. While somewhat lengthy, every sentence adds value and the structure is logical. Could be slightly more concise, but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description compensates fully by listing all expected fields (ratings, top metros, bounding box, price percentiles, etc.). It also clarifies aggregate nature and potential 404, making the tool's behavior complete for agent decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter 'country' clearly described as ISO-3166-1 alpha-2. The description adds no extra meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves an Airbnb market for a country, specifying it's aggregate data from the 'airbnb-markets' dataset. It distinguishes itself from siblings like datasets_airbnb_search by focusing on a single country's full profile.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description notes that the tool is aggregate-only and returns 404 for suppressed countries, providing clear context. However, it lacks explicit comparison to alternatives or when-not-to-use, but still offers sufficient guidance for basic usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully carries the burden. It describes the output fields (centroid, listing count, Superhost share) and behavior (thin cells suppressed). It does not mention permissions or side effects, but the tool appears to be read-only and safe.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words: first sentence defines the tool's purpose and output type, second adds details on output fields and behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main output and behavior. With no output schema, it adequately describes what is returned. It could explicitly state that it does not return individual listings, but 'aggregate-only' implies this.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, providing baseline 3. The description adds context about the geohash grid and aggregation, and notes that thin cells are suppressed, adding value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it returns an aggregate geohash-grid density map of Airbnb listings near a coordinate, from a specific dataset. This distinguishes it from sibling tools like `airbnb_search` which return individual listings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description specifies that it returns aggregate data only ('Aggregate-only'), indicating it is not for individual listing details. It does not explicitly list alternatives or when not to use, but the context from sibling tools and the description provide sufficient guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral transparency burden. It discloses the data source, document structure (one per chart × snapshot × rank), default date behavior, and enums. Missing operational details like rate limits or exact return format, but the core behavior is well explained.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded: the first sentence states the purpose, followed by data model, defaults, and usage examples. Every sentence earns its place—no redundant fluff or repetition of schema content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 12 parameters, no annotations, and no output schema, the description covers the key aspects: data scope, source, defaults, enums, and a time-series use case. It does not explicitly describe return fields or pagination limits, but the schema covers parameter constraints, making this sufficient for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 100% schema coverage, the description adds value beyond the schema by explaining enum semantics (store, chart type, platform, sort), the default behavior of `date`, and the app_id/sort combination for rank history. This enriches the bare schema descriptions with practical meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search the app-charts dataset' and specifies the exact resource: daily top-chart snapshots from iOS App Store and Google Play. It distinguishes this from sibling tools like datasets_apps_search by focusing on chart snapshots and rank data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides concrete usage patterns: 'With no `date` the latest snapshot is returned' and 'pair `app_id` with `sort=date_desc` for an app's rank over time'. This gives clear context for common cases, though it does not explicitly mention when not to use this tool versus alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses several important data quirks: category may be localized/non-ASCII/punctuated, rating null means no rating, review_count null vs 0 distinction, and geo null for locationless businesses. These details go well beyond a basic 'get item' description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded with the core purpose. Each subsequent sentence provides distinct and valuable behavioral details (category, rating, review_count, geo) without being verbose or repetitive.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description explains key nuances of returned fields (category, rating, review_count, geo) but does not enumerate all fields. This is a strong, concise coverage of the most likely confusing aspects, making it more complete than a minimal 'Returns a business' description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers the place_id parameter with a clear description ('Google Place ID, max 256 characters'). The tool description adds no extra meaning about the parameter itself, so the baseline of 3 is appropriate given 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a stored Google Maps business by Google place_id, specifically from the `google-map-businesses` dataset. This is a specific verb+resource+scope, and distinguishes it from search/facets/nearby siblings by emphasizing 'stored' and 'by place_id'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies clear usage context: use this when you have a place_id and need a single stored business item. It does not explicitly name alternatives or exclusions, but 'stored' and 'by place_id' provide enough context to differentiate from search or nearby tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does well: it explains null rating and review_count semantics, the difference between null and 0, sort behavior for unrated businesses, and min_rating exclusion behavior. Minor omissions like rate limits or response shape are acceptable for a read-only search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single dense paragraph with all sentences contributing useful information. It is slightly long given the 18 parameters, but each sentence earns its place; there is no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the high parameter count and absence of annotations/output schema, the description covers parameter behavior comprehensively and explains edge-case semantics. It does not describe the return list shape, but this is a minor gap for a search tool whose primary purpose is clear from the schema and name.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Even with 100% schema coverage, the description adds significant meaning: category can be localized/non-ASCII, rating null vs 0, rating_desc sorts unrated last, min_rating>0 excludes nulls, and has_geo=false for locationless businesses. These details go well beyond the schema property descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search stored Google Maps businesses' and 'Searches Google Maps business records stored in a search index', which uses a specific verb+resource and 'stored' distinguishes it from live google_map_search and related dataset tools. It is unambiguous about its function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives practical guidance such as using the category facet to discover exact filter values and using has_geo=false to isolate locationless businesses. It does not explicitly say when to prefer this tool over sibling tools, but the 'stored' qualifier plus the facet suggestion provide useful context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully discloses behavioral traits: it explains the return format (lines and ratios keys with examples), edge cases (unknown CIK returns empty series, most filers without ticker have no data), and enumerates the statement and period options. This provides complete visibility into the tool's operation and output structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single well-organized paragraph that efficiently conveys all necessary information. It begins with the core purpose, then details return structure, edge cases, and key enumerations. No extraneous content exists. Minor improvement could be using bullet points for the key lists, but current structure is clear and not overly verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description adequately covers the tool's functionality given its complexity (6 parameters, no output schema, no annotations). It explains the return format in detail, edge cases, and parameter choices (statement/period enums). However, it does not mention pagination behavior (beyond limit/max points), and the ordering is noted but could be more explicit. Overall, it provides sufficient context for correct use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although the input schema has 100% description coverage, the tool description adds significant value by explaining the meaning of returned data (e.g., `lines` keys like revenue, net_income; `ratios` keys like gross_margin) and elaborating on the statement and period enums (income, balance, cash_flow; annual, quarterly). This context goes beyond the schema's parameter descriptions and aids correct parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get a SEC company's financial-statement history.' It specifies the resource (financial-statement history) and distinguishes it from sibling tools like datasets_sec_companies_item or datasets_sec_companies_search by focusing on normalized financial statements (income, balance, cash flow). The action verb 'Get' is precise and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly defines usage (to retrieve financial history) but does not explicitly state when to avoid this tool or which alternatives to use. It mentions behavior for unknown CIK (empty series) but lacks guidance on using other datasets_sec_companies tools for different data (e.g., company details or insider transactions). The context of use is clear but lacks exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden for behavior disclosure. It transparently defines the one-document-per-appid×achievement structure and clarifies sort semantics (most-unlocked vs rarest first). It does not describe pagination behavior or return format, but those are partially covered by the schema's page/page_size descriptions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the core purpose. Every clause adds value: dataset scope, document model, app_id usage, and sort semantics with defaults. No filler or redundancy with schema fields.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description adequately covers the main search use case with document granularity and sort defaults. It does not explicitly state behavior when app_id is absent or list return fields, but given only four simple optional parameters and no output schema, it is sufficiently complete for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds meaningful semantic value by specifying that app_id triggers listing a game's achievements and by elaborating the sort enum: percent_desc = most-unlocked first, percent_asc = rarest first, rank_asc. This goes beyond the schema's bare enum listing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Search steam-achievements dataset' and specifies the exact data content: 'per-game global achievement unlock percentages (one document per appid × achievement)'. This clearly identifies the resource and its granularity, distinguishing it from sibling dataset tools like datasets_steam_playercounts_search and datasets_steam_reviews_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides concrete usage guidance: 'Pass `app_id` to list a game's achievements' and explains the three sort options with their meanings and default. However, it does not mention when to prefer this tool over other Steam-related dataset tools or what happens when app_id is omitted.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full transparency burden and does well: it explains the search index structure (one document per chart × country × snapshot × rank), history accumulation, and default snapshot behavior. It does not describe pagination quirks or return format, but those are partially visible in the schema and less critical for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four dense but well-structured sentences. It front-loads the core purpose and packs the data model, chart types, defaults, and key parameter interactions without fluff or redundancy. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having 8 parameters and no output schema, the description covers the essential context: dataset contents, document structure, chart types, default date, and country conventions. It could say a bit more about full-text `q` search behavior and pagination constraints, but the schema descriptions already cover those parameter details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents all 8 parameters, so the baseline is 3. The description adds meaningful semantics beyond the schema by explaining chart enum values, the default date behavior, country mapping, and the app_id + sort=date_desc combination for time-series lookups, exceeding the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches the steam-charts dataset, which contains daily snapshots of Steam's player-count and sales charts. It names the specific chart types (`most_played`, `concurrent`, `top_sellers`) and their meanings, distinguishing this tool from sibling Steam tools like `datasets_steam_playercounts_search` and `datasets_steam_news_search`.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides strong operational guidance: no `date` returns the latest snapshot, pairing `app_id` with `sort=date_desc` fetches an app's history, and country is `global` for player-count charts but an ISO code for `top_sellers`. It doesn't explicitly name sibling alternatives or exclusionary conditions, but the context is clear enough for an agent to decide when to use this search tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses the data model (one document per appid×gid), the fact that only the latest items per app are kept, what fields `q` searches, and the sort enum with default. This gives the agent useful behavioral context. It doesn't describe the return format or rate limits, but for a search tool the key behaviors are covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, no filler. The information is front-loaded with the verb 'Search' and each sentence provides distinct value: dataset scope, filter options, and sort defaults. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 5 parameters (all documented in schema) and no output schema or annotations. The description covers dataset scope, filter semantics, and sort behavior, which is sufficient for an agent to invoke it correctly. It doesn't explain the response shape, but given the search context and schema completeness, the description is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds meaning beyond the schema: it explains `app_id` is for a single game's news, `q` searches title+contents, and adds that `date_desc` is the default sort and means 'newest first'. This is genuinely helpful, lifting the score above baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Search' and names the resource 'steam-news dataset'. It clearly distinguishes from sibling tools by stating the dataset's scope: 'Steam news + announcements for tracked apps (one document per appid × gid; the latest items per app are kept)'. This makes the tool's purpose unambiguous and differentiates it from other Steam or datasets search tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on how to use the tool: filter by `app_id` for a single game's news or use full-text `q` over title+contents. It also notes the sort options and defaults. It does not explicitly name alternative tools or say when not to use it, but the usage context is clear enough for an agent to decide when this search is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It explains the data model (one doc per appid × day) and sort defaults, which helps the agent understand what to expect. It doesn't cover all behaviors like pagination or response format, but it provides meaningful insight beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loading the tool's core function, then providing usage patterns, then the sort enum. Every sentence adds critical information with no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with no output schema, it explains the dataset and common use cases well. Pagination and response fields are not covered, but the schema documents page and page_size, and the tool's name clearly indicates a search over player counts. It's suitably complete for most agent decisions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds value by explaining how parameters combine: `app_id` with `sort=date_desc` yields history, and `date` yields a snapshot. It also clarifies the sort enum meaning, enriching the schema's default descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search steam-playercounts dataset' and specifies the data structure (daily concurrent-player time series for tracked games, one document per appid × day). This distinguishes it from sibling dataset search tools by naming the exact dataset and its granularity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides concrete usage patterns: pair `app_id` with `sort=date_desc` for a game's history, or pass `date` for a snapshot. While it doesn't explicitly mention alternatives or exclusions, it gives clear context on when to use specific parameters, which is sufficient for a dataset search tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden and does well by disclosing that this is a public event directory, that results include availability tags, and that it deliberately excludes betting markets and odds. It stops short of 5 because it doesn't mention pagination, response formatting, or other operational limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact, front-loaded, and uses two sentences to cover what the tool returns, what fields are included, where the league_id comes from, and what is excluded. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter directory lookup, the description provides enough context: what to supply, where to source it, and what the response will contain. It does not describe pagination or a return structure, but the absence of an output schema is partially mitigated by the explicit field list.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so a baseline of 3 applies, but the description adds real value by telling the agent exactly where to source a valid league_id from, which helps avoid invalid inputs. It reinforces that the ID is numeric and is a league-level identifier rather than an event-level one.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: it 'returns' a DraftKings Sportsbook league's current public event directory, and lists concrete returned fields such as event IDs, participants, start times, status, and availability tags. It also distinguishes itself from odds/market-focused tools by stating 'does not include betting markets or odds.'
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly explains how to obtain the required league_id from specific related endpoints, such as /draftkings/sportsbook/leagues and /draftkings/sportsbook/featured-leagues. It also signals when not to use this tool by excluding markets and odds, though it does not explicitly name sibling alternatives like draftkings_odds.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden, and it does good work: it discloses that the data is credential-free, sourced from public JSON, and that an empty response is a legitimate outcome rather than an error. It does not go deep into rate limits, response shape, or failure modes, but for a simple read-only odds lookup the core behavioral traits are honestly exposed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and efficient: it leads with the tool's purpose, names the response scope, gives parameter guidance, and clarifies the empty-list behavior. Every sentence earns its place, and no extraneous information is included.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter tool with no output schema, the description covers the necessary selection, parameter, and expected-result information. It does not fully specify the response fields or nested event structure, but it communicates the all-important empty-response case and tells the agent exactly what kind of data will be returned. That is reasonably complete for this complexity level.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only says 'Numeric DraftKings league ID', and the description adds meaningful context by explaining that league_id is a numeric DraftKings identifier and telling the agent where to find it from the league's Sportsbook page. Since schema coverage is 100%, the baseline is a 3, but this description goes beyond it with discovery guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: it returns primary betting markets (moneyline, spread, total) for every upcoming event in a DraftKings Sportsbook league. It also names the source data, making it clear this is league-wide odds retrieval rather than event-specific or futures data, which helps distinguish it from sibling tools like draftkings_event_markets and draftkings_futures.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies the intended use case: retrieve standard odds across an entire DraftKings Sportsbook league. It provides useful context by explaining how to find league_id and noting that an empty events list is a valid response when nothing is scheduled. It stops short of explicitly naming alternatives or stating when not to use this tool, but the league-scope and market-scope constraints make its usage context clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It clearly states the return is ordered and reflects current home page prioritization, which conveys the dynamic nature and the ordering guarantee. It doesn't disclose pagination or any potential empty result behavior, but for a zero-parameter tool this is acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences that are entirely value-dense; the first clearly states the resource and ordering semantics, the second explains the league_id's usefulness for downstream calls. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter list tool, the description covers purpose, scope, ordering, and downstream use of the returned league IDs. The absence of an output schema is partially compensated by the description's mention of a numeric league_id per item. It doesn't list other fields in items, which is a mild gap, but not critical for selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters, so schema coverage is effectively 100%. The description doesn't need to explain parameters since there are none. The baseline of 4 for zero-parameter tools applies, and the description's mention of the output shape gets the semantics to a solid level.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Returns the ordered league shortcuts currently prioritized on DraftKings Sportsbook's public home page' with a specific verb and resource. This distinguishes it from sibling tools like draftkings_odds or draftkings_futures by explaining it returns navigation shortcuts, not betting data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly signals when to use this tool: when you need the current prioritized league shortcuts from the home page. It doesn't explicitly mention alternatives, but the clarity of the resource makes the use case evident. The included note that each league_id is accepted by /draftkings/sportsbook/odds and /draftkings/sportsbook/futures adds practical downstream routing guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses pagination, the specific fields returned, the extra internal request to resolve the separate work id, and the upstream error when no editions data exists. This is rich, honest behavioral context beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, each adding value: purpose and scope, return fields, and behavioral caveat/error. It is dense but not bloated, and the main purpose is front-loaded. Slightly longer than the two-sentence ideal but justified by the important caveats.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (extra internal request, error behavior, pagination) and the absence of an output schema, the description is remarkably complete. It covers what data is returned, how pagination works, the work-id mismatch, and the failure mode, giving an agent enough to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for both parameters (id and page), so the baseline is 3. The description adds meaningful context by explaining that the id is a 'book id in the path' and that Goodreads keys by a separate work id, which clarifies why an extra request is made. It also implies the page parameter via 'paginated edition list'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description begins with 'List a Goodreads book's editions', which uses a specific verb and resource, and clearly differentiates from siblings like goodreads_book and goodreads_author_books by focusing on editions. It even clarifies the scope as 'every other translation, printing, and format of the requested book id'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage context is implied but not explicit. The description states the tool returns all editions of a book, which suggests when to use it, but it does not name alternatives or provide when-not-to-use guidance. There is no explicit comparison with sibling tools like goodreads_book or goodreads_search.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the scope of returned data (installs, ratings, pricing, version info, developer metadata, media assets, release state, selected comments, recommendation rails) and introduces default country/lang values. It doesn't mention rate limits, auth, or error cases, but for a read-style details endpoint this is solid coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences: first states the core action, second lists what's returned, third provides the sibling pointer and defaults. Every sentence contributes new, relevant information with no waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is strong for a details tool: it enumerates the included data fields, points to a related tool for alternative breakdowns, and gives defaults. It doesn't describe the exact output shape, but with no output schema, the field list is a good proxy. There is a slight gap on whether 'full details' includes all possible storefront variations, but the defaults and pointer cover most needs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already covers all three parameters with descriptions (100% coverage), so baseline is 3. The description adds valuable default values (`country=us`, `lang=en`), which are not present in the schema, giving it a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Retrieve full Google Play app details.' It enumerates the specific data categories returned (installs, ratings, pricing, etc.) and distinguishes itself from the sibling `/googleplay/ratings` tool by directing users there for per-device ratings breakdowns.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: it returns full app metadata from a details page. It also provides an explicit alternative: for per-device ratings/reviews, use `/googleplay/ratings`. However, it doesn't explicitly state when to choose this over other siblings like `googleplay_search` or `googleplay_similar`, so it's not a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral transparency burden. It discloses the transport mechanism (primary credential-free GraphQL API, fallback to web-page transport) and notes that no credentials are required. This is helpful context beyond the schema, though it does not cover failure modes or response structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no redundancy. The first sentence front-loads the purpose, and the second sentence adds relevant behavioral details about transport and credentials. Every phrase earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter read-only tool with no output schema, the description is reasonably complete. It covers the input source and transport fallback, which is important for an agent to know. It does not describe return fields or error behavior, but those are less critical given the straightforward nature of the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% coverage by describing `jk` as an Indeed job key (16-character hex). The description adds the origin of the key (the `job_key` field returned by search), which helps the agent understand how to populate the parameter correctly, going beyond the schema's static description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states clearly that the tool returns a single Indeed job posting identified by its job key. The verb 'Returns' plus the resource 'Indeed job posting' and the key reference make the purpose explicit and distinguish it from search tools like indeed_search that return multiple results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage after a search by referencing the `job_key` field returned by indeed_search. This is clear contextual guidance, though it does not explicitly name alternatives or state when not to use this tool. The sibling context provides additional differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It thoroughly explains the tool's behavior: returns term-level suggestions with a representative thumbnail, mirrors the site's search box dropdown, is scoped to one store, and uses public data. This provides rich context beyond the bare function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the core purpose. Each sentence adds distinct value: the scope ('at a store'), the output type ('autosuggestions... dropdown'), and the nature of the data ('term-level', 'not a product list', 'public data'). No fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively simple, and the description covers the essential behavior, scope, and data source. There is no output schema, but the description gives a clear mental model of the response (suggestions with thumbnails). It could specify the exact output fields, but given the context, the description is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for all three parameters, so the baseline is 3. The description does not add further parameter-level details, but the schema already documents what q, shop_id, and store_slug mean. The tool's description does not need to compensate for any gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Search Instacart product terms at a store.' It further distinguishes itself by specifying it returns autosuggestions (term-level) rather than a paginated product-results list, which differentiates it from sibling tools like instacart_item or a general product search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states the intended use case: getting Instacart's own autosuggestions for a keyword within one store. It also provides a clear exclusion: 'not a paginated product-results list,' which tells the agent what it won't return. However, it does not name alternative tools for product searches, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the data is public, comes from Instacart's cross-retailer search, and that results are popular/trending terms. No side effects or destructive actions are implied, which is appropriate for a read-only lookup. It doesn't cover rate limits or output formatting, but that's minor for this tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no filler. Action verb and resource appear immediately, and every clause adds distinct value (scope, source, use case). Excellent front-loading.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no output schema, the description sufficiently conveys what is returned (trending search terms) and from where. It could specify whether results are ranked or limited, but this isn't essential for selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the lone parameter postal_code already has a description. The tool description enhances it by noting results span 'every retailer serving a postal code,' clarifying the geographic scope and aggregation behavior beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get Instacart trending search terms near a postal code' with a specific verb, resource, and scope. It distinguishes from related tools like instacart_search by explaining it returns blank-state suggestions, not item search results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use it (to see popular/trending search terms across retailers for a location) and even illustrates the use case with 'blank-state suggestions.' It doesn't explicitly name alternative tools or exclusions, but the intent is unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description mentions 'Credential-free public ATS JSON', indicating no authentication needed. Discloses that it returns thin listings. No annotations provided, so description carries full burden. Lacks pagination or rate limit info but sufficient for basic behavioral understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, each adding value: purpose, data scope, URL format, and credential requirements. Efficiently front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, data content, URL format, and authentication. Could mention pagination or result limits, but for a simple listing tool the description is nearly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds context for the company parameter by specifying the exact URL format (https://ats.rippling.com/{company}/jobs), enriching schema description. Other parameters are well-described in schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool lists a company's Rippling job board postings, specifying the data included (title, department, work location) and differentiating from the detail endpoint. Distinguishes from sibling tool jobs_rippling_job.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description implicitly guides use by indicating this tool provides thin listings and points to a separate endpoint for full details. However, it lacks explicit when-to-use vs alternative job board tools (e.g., Ashby, Greenhouse).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior. It states the tool is a read operation (list), public and credential-free, and explains the company parameter derivation. However, it does not mention pagination, rate limits, or response size limitations, which would be useful.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences: main action, details on normalization and filtering, and company identification. No unnecessary words or redundancy. Front-loaded with the primary purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema, the description mentions 'normalized to the shared Job shape with detail inline', providing some output context. It also notes the credential-free nature. Could be improved by briefly describing the job shape structure or linking to a common schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions. The description adds value by explaining the 'company' param as the Teamtailor subdomain and confirms optional filtering. This supplements the schema without redundancy.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists a company's Teamtailor job board, specifying the output format (normalized to shared Job shape) and the source (public JSON feed). It distinctly identifies the ATS type (Teamtailor), differentiating it from sibling job board tools for other ATS systems.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly indicates when to use the tool (to list jobs from a Teamtailor board) and notes it requires no credentials. While it doesn't explicitly list alternatives among siblings, the specificity to Teamtailor implies its niche. Missing explicit when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the tool fetches and summarizes data, implying a read-only operation. It lists the types of information returned (provider availability, monetization buckets, etc.), which is helpful. However, it does not explicitly state that the tool is read-only or non-destructive, nor does it mention any potential side effects (though none are expected).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long: the first explains the tool's purpose and output, and the second provides a critical usage instruction. Every sentence earns its place, and the structure is front-loaded with the most important information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 optional parameters, no output schema, no annotations), the description provides sufficient context about what the tool does and returns. It summarizes the key output categories (provider availability, monetization buckets, etc.), which is adequate for an agent to understand the return value. The lack of an output schema is compensated by the description's detail.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% coverage with descriptions for both parameters. The description adds value by instructing 'Pass exactly one of `path` or `url`', which clarifies that despite both being optional in the schema, exactly one should be provided. This prevents ambiguity and helps the AI agent avoid invalid API calls.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Analyze' and the resource 'JustWatch title availability'. It specifies that it fetches a title page and summarizes provider availability, monetization buckets, formats, price ranges, and best options, which distinguishes it from sibling tools like justwatch_title (which likely returns raw title data) and justwatch_title_offers (which may focus on individual offers).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Pass exactly one of `path` or `url`', which is a clear usage instruction. However, it does not provide guidance on when to use this tool versus alternative sibling tools, nor does it state when not to use it. A brief mention of scenarios (e.g., 'Use this for a summarized overview instead of raw title data') would improve the score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral disclosure burden. It states the pagination behavior, the page size of 10, the normalized shape of reviews, and the edge case that a zero-review web_id returns a genuine zero-result response rather than an error. This is strong behavioral transparency without annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded; the first sentence states the operation and target, and the remaining sentences earn their place by defining the return content, the input source, and a critical edge case. There is no filler or repeated schema content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple 2-parameter interface and absence of an output schema, the description is comprehensive enough: it covers page, page size, return fields, web_id provenance, and the zero-result behavior. It leaves minor terminal details, such as sort order or exact response shape, implicit, but nothing obstructs a correct call.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is already solid. The description adds meaningful parameter context beyond the schema, especially that web_id comes from a /category product response and that pagination is page-based. This will help an agent know where to source the required web_id.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Browse a Kohl's product's customer reviews,' and immediately explains it returns one page of normalized review fields. It is unambiguous and distinct from the other kohls_* siblings, which handle categories, stores, and suggestions rather than reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear usage context: it returns one page of reviews for a Kohl's product, and explicitly explains that web_id is the same identifier carried by a GET /kohls/category response's products[].web_id. It does not explicitly name excluded alternatives, but with no competing Kohl's reviews sibling this is acceptable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Behavioral Transparency: The description carries substantial behavioral detail: it says what is returned (anchor product plus complementary items), clarifies id-space differences, states recommended items have third-party ids, directs users to each item's URL, and warns about 404 on unknown input. No annotations are provided, so this is a strong behavioral disclosure, though it does not cover todos limit, or authentication.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The text is dense but not bloated; every sentence adds either scope, id-space guidance, or error behavior. It begins with a clear summary and then provides necessary pointer and caveats, so the structure aids quick scanning. It is somewhat lengthy for a two-parameter tool, but the added detail is justified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is complete enough for the tool's scope: it covers what the tool returns, how to source the input ids, the id-space pitfalls, how to reach product pages, and the exact error condition (404). Given that there is no output schema, the description fills all essential gaps for a safe and correct call.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents both parameters fully, so a baseline of 3 applies. The description adds helpful semantic nuance beyond the schema: it defines both the source of unified_id and color_code, and explicitly warns that the id is not the same as lululemon-product's product_id. This meaningfully reduces risk of misuse.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Get lululemon's outfit/style recommendations for a product color.' It clearly narrows the scope to one product color and states the result includes both the anchor product and every complementary item. This distinguishes it from sibling tools like lululemon_product and lululemon_category without ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: it is used with a unified_id and color_code obtained from lululemon-product's response, and an unrecognized pair returns 404. It does not explicitly name alternative tools or say when not to use it, but the context of 'outfit/style recommendations for a product color' makes the intended usage obvious.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description compensates by disclosing important behavioral traits: the data is from the endpoint's own research and may be stale, filters are applied locally, and there is no live geo-search API. It also states the return content (weekly hours and amenities). This goes beyond just saying 'stores' and provides useful operational context for the agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single dense paragraph, yet each sentence contributes a distinct fact, from directory size to filter behavior to maintenance notes. It could be slightly more structured, but it is not bloated and stays on topic.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given five parameters, no output schema, and no annotations, this description covers the essential details: what the tool returns, which regions and how many stores, the local filtering behavior, parameter constraints and defaults. The pointer to maintenance notes further aids a cautious agent. Nothing needed to invoke it correctly is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3, but the description adds worthwhile nuance: country and state are free-text equality filters not enum-constrained, lat/lng are required together, and radius_miles has a 1–500 range with a default of 50. It also clarifies that all filters are locally applied after fetching the directory, which is important for interpretation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource, 'Browse lululemon's physical store directory,' and clarifies the exact scope by citing 480 US and 86 Canada locations. It clearly distinguishes this tool from other retail store locators by naming the brand and ownership of the data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear filter semantics: all optional, applied locally, and no live geo-search API. It explains constraints like lat/lng required together and radius limits, but it does not explicitly call out a sibling store-locator tool or state when to use this one over alternative directory endpoints, so it falls short of an explicit when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations available, the description carries the full behavioral burden and handles it well: it discloses pagination, normalization, the site-wide summary, the third-party source, and the non-error empty result for zero-review or unknown products. This is notably richer and more transparent than most tool descriptions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact but information-dense, with no filler. It leads with the purpose, then layers return details, source distinction, and edge-case behavior in an efficiently structured sequence, and every sentence contributes useful content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema and no annotations, the description gives enough context to decide when and how to call the tool, including pagination and error behavior. A minor gap is that it does not outline the shape of the normalized review objects or clarify sorting, but these are not blocking for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema is already fully documented, so the baseline is 3. The description adds value by explicitly linking product_id to the same identifier used by the catalog endpoint and clarifying that unrecognized but well-formed IDs return empty results, which helps an agent understand parameter provenance and failure semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a clear verb and resource: 'Get a Macy's product's customer reviews,' then precisely details return content (one page of normalized reviews plus a rating summary). It also distinguishes itself from the product catalog by identifying the review platform as a separate source.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes the tool's general purpose obvious and adds important context that reviews come from a separate platform rather than the product catalog. However, it never explicitly says when to prefer this tool over siblings like macys_product or pkg explicitly, so guidance on alternative selection remains implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full transparency burden. It reveals data sources (credential-free AniList, scraped MAL), that mal adds one fetch, and that enrichment is skipped when no MAL ID. It could mention read-only nature, but overall good.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, starting with the main purpose, then listing fields, then explaining the optional parameter. No redundant sentences; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 2-parameter tool with no output schema or annotations, the description adequately covers the return structure (fields list) and optional behavior. It could mention that the id is required, but that's in the schema. Slightly incomplete on error handling, but sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage, baseline 3. The description adds meaning by explaining that mal enriches with MAL community score (including score and scored-by count) and that it's credential-free. This goes beyond the schema's brief description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets a manga by AniList ID and lists all returned fields (titles, scores, popularity, etc.). It distinguishes itself from siblings like manga_search and manga_rankings by focusing on retrieval by ID.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when an AniList ID is available and explains the optional mal enrichment. However, it does not explicitly contrast with manga_search or provide when-not scenarios, which would elevate it to a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the tool returns a page of public sitemap data, lists the fields returned, and explicitly states there is no filtering. It also implies read-only behavior ('Returns'), which is appropriate for a listing tool. It does not detail response format or ordering, but this is sufficient for a simple catalog endpoint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the tool's purpose ('Meta Jobs catalog listing'), and every clause adds value: what is returned, its key fields, and when to use which tool. There is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a simple input schema (2 optional params) and no output schema, but the description compensates by listing return fields and providing use cases (enumeration, change tracking). It does not describe pagination beyond the schema, but the combination of description and schema is sufficient for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: both 'page' and 'page_size' are described in the schema with defaults and max. The description itself adds nothing beyond mentioning 'page', so it does not elevate the semantics beyond the schema. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Returns'), a resource ('Meta's own public job sitemap'), and the exact scope ('every open requisition's id, canonical URL, and last-modified timestamp'). It also explicitly contrasts with 'search' by noting there is 'no team/location/keyword filtering', which distinguishes it from sibling tools like meta_jobs_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance: 'Use this for full-catalog enumeration or change tracking via last_modified; use search when you need to filter by team, technology, location, employment type, or keyword.' This clearly states when to use this tool and when to use an alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the anonymous endpoint, the empty-request behavior (returns entire catalog), the AND filter semantics, and the limitation of q. It does not mention response format or potential rate limits, but it provides meaningful behavioral context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is long, but almost every sentence provides necessary information, especially the enum lists that are absent from the schema. The structure is logical: purpose, semantics, then parameter details. It is front-loaded with the core action and follows with essential constraints. The length is justified by the complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the endpoint, filter behavior, empty-request behavior, q semantics, and enums. It does not explicitly describe the response format, but the lack of an output schema suggests the agent must infer it. Given the complexity and the absence of annotations, this is a highly complete description, with minor gaps around return value structure and potential errors.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds significant value by providing the full enum lists for teams and roles, which the schema lacks, and by clarifying q's special semantics (not free-text). It also explains that all filters are optional and combine with AND, adding meaning beyond the raw schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches Meta's public careers site via a specific GraphQL endpoint. It names the resource (metacareers.com) and the action (search), and distinguishes it from sibling tools like meta_jobs_job and meta_jobs_list by focusing on the search/filter behavior.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the tool (searching Meta jobs with filters) and provides important behavioral guidance, such as the q parameter not being a free-text title/description search and the AND semantics for combining filters. However, it does not explicitly mention alternatives like meta_jobs_job or meta_jobs_list, nor does it state when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral disclosure, and it does so well: it states the operation is a read that returns 'normalized' data, targets exactly one color variant rather than the entire product, and names the output dimensions. It also reveals the slug/style_color relationship to Nike's canonical URL. It stops short of mentioning failure/error behavior or currency/locale assumptions, but nothing here contradicts the tool's read-only nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences accomplish three jobs with no wasted words: the scope declaration (one color variant), the output summary (fields returned), and the input key provenance (nike-search tie-in + URL). The riskiest detail, that it is a single-variant fetch, is front-loaded instead of buried.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and no annotations, but the description gives the agent the essential contract: what is required (slug, style_color), where those come from, what data comes back, and the exact URL it maps to. The omissions (error behavior, currency, image size conventions) are tolerable for a single-product 'get' call, making this near-complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3 even with no parameter prose. The description adds meaningful semantics on top: slug and style_color 'together reproduce Nike's own product page URL' and are derived from the same colors[] array in search results. This relational information strengthens the two separate opaque identifiers into a compound key with a known URL format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Opens with a specific verb and resource ('Get a Nike product') and immediately narrows scope to 'one color variant' with an enumeration of returned fields (title, description, pricing, images, sizes, alternate colors). This distinguishes it clearly from siblings such as nike_search (query results), nike_product_reviews (feedback), and nike_categories (menu structure), so an agent can tell it apart even before reading the schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description establishes the intended call pattern by stating that both inputs come from a preceding nike-search result's colors[].slug and colors[].style_color fields, so an agent knows it should follow a search with this detail lookup. It does not explicitly name alternatives to avoid (e.g., 'use nike_product_reviews for reviews'), but the clear field-level provenance is strong contextual guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden and does a solid job: it describes the returned content, states that a no-review product returns a well-formed empty result, and warns that an out-of-range page returns a not-found error. It does not disclose every possible behavior like rate limits, but for a read-only reviews endpoint the critical edge cases are covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
This is a tightly written description: it leads with the operation, explains the output, connects the parameters to a sibling tool, and includes two relevant edge cases. No sentence is filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and no annotations, this description is notably complete: it says what the result contains, when the result is empty, and when it errors. The lack of specific field names in the review objects is a minor gap, but the agent can correctly select and invoke the tool based on the provided details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already explains all three parameters at 100% coverage, so the baseline is 3; the description adds real value by tying slug and style_color to the nike_product and search-result fields, and by clarifying that the tool returns one page at a time. This helps an agent understand what to pass and what to expect.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Get Nike product reviews.' It further specifies the return value as normalized reviews plus an aggregate rating summary, and distinguishes itself from Nike's product-detail endpoint, so the tool's purpose is unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It explains that slug and style_color are the same values nike-product accepts and come from a search result's colors[].slug and colors[].style_color fields, which gives an agent a concrete path from search to this tool. It also notes that the rating summary is not exposed by the product-detail endpoint, implying a key reason to use reviews, though it does not explicitly list when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries full behavioral burden and it does well: it discloses that cid is opaque, that no API-complete category-id list exists 'for now' (a change/fragility note), and that results are normalized product summaries with per-color inventory and live facet counts. It stops short of covering error behavior, auth, rate limits, and pagination details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, each earning its place: core action first, then the cid-provenance constraint, then the brand parameter mapping, then the return payload. No padding or repeated schema content; the guidance is front-loaded so the agent gets the essential behavior in the first sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Because no input schema exists, the description compensates by naming the outputs (subcategory breakdown, normalized product summaries, per-color inventory, live facet counts), which is enough for an agent to judge whether to call it. The gaps — error behavior on mismatched brand/cid, pagination specifics beyond 'one-based', and whether products pages link back — would be nice but are minor for a browse tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema already covers all three params, so the baseline is 3, but the description adds real value: it explains that cid is an opaque Gap Inc id sourced from a browse-page URL, and it enumerates the brand codes (`on`, `gap`, `br`, `at`) with the default and the match-must constraint — all absent from the schema's minimal property text for `brand`.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Opens with a specific verb and resource: "Browse an Old Navy, Gap, Banana Republic, or Athleta category." It then states exactly what is returned (subcategory breakdown, normalized product summaries, per-color inventory, facets) and names the core input (cid), so an agent can tell it apart from sibling tools like oldnavy_search, oldnavy_categories, and oldnavy_product without opening their schemas.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives concrete sourcing guidance: oldnavy-search and the category tool do not list category ids, so the agent must pull cid from the storefront's /browse/... page URLs, and it warns that brand must match the brand the cid was found under. It does not explicitly state when to prefer this tool over the search or product-detail siblings, so the when-to-use decision is mostly implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the return is normalized to one color variant, everything offers beyond sizes are separate priced offers, and the pid must be color-specific rather than a base product id. It omits error behaviors or auth/rate-limit notes, but the essential behavioral quirk is filled.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Each of the three sentences carries a distinct purpose: brand scope, return payload, and pid/brand parameter guidance. The description is a bit dense with dashes a semicolon, but no sentence is filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With only two parameters, no output schema, and no annotations, the description gives enough to select and invoke the tool correctly, including return content and parameter semantics. It would be fully complete if it briefly covered error/return-shape edge cases, but that is not essential.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 100% schema coverage, the description adds concrete value: for brand it enumerates the valid values (`on`, `gap`, `br`, `at`) and documents the default, and for pid it states the exact source field and explicitly warns 'not the bare base product id' and the requirement that pid matches the brand. This goes well beyond the schema's terse property descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a concrete verb and resource ('Get an Old Navy, Gap, Banana Republic, or Athleta product') and immediately defines the exact scope: one color variant, with a specific return payload (name, description, images, aggregate rating, size-priced offers). It also distinguishes itself from sibling product tools by explaining that pid is a color-specific product id, not the bare base product id.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives clear usage context: this tool is intended after obtaining a pid from oldnavy-search's product colors[].id field, and the brand must match the storefront under which the pid was found. It doesn't explicitly list alternatives like oldnavy_product_reviews or oldnavy_product_availability, but the intended workflow is well communicated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of explaining behavior. It discloses that results are per-size, per-store, with stock statuses of in_stock, out_of_stock, or low_stock, and that the tool resolves nearest stores when zip or lat/lng is given. It could add detail on error behavior or mutual exclusivity of store selection parameters, but the core behavioral content is strong.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense and well-organized: first what it checks, then the pid relationship, then store selection options, then brand values and result content. Every sentence adds operational value, and the most important information (purpose) is front-loaded. There is no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
All essential details are present: required pid, store resolution options, brand mapping, and output statuses. The field is complete enough for an agent to invoke successfully. Minor gaps: no statement about conflict handling if multiple store location modes are provided, and no pagination/rate limit hints, though these are largely irrelevant for a small JSON-response endpoint.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description doesn't need to restate parameter semantics. Still, it adds useful meaning by defining brand storefront aliases and clarifying that store_id is pluralizable with comma-separated ids. This exceeds the schema baseline of 3, though the description could go further by explaining conflicting inputs; hence 4 might be slightly generous, 3 is the safe grounded score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('check in-store pickup stock'), the resource ('one color (pid) at one or more physical stores'), and the brand scope (Old Navy, Gap, Banana Republic, Athleta). It distinguishes itself from sibling tools by emphasizing per-size per-store stock status, which is unique among the retail siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly explains when to use which store locator input: store_id directly, zip, or lat/lng, and that the latter two resolve nearest stores automatically. It also gives exact brand parameter values (`on`, `gap`, `br`, `at`, default `on`) and clarifies that pid matches oldnavy-product's color-level id, which clearly guides cross-tool usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, and it does well by explaining search options, required lat/lng pairing, brand selection, and the return fields. It doesn't mention edge cases like empty results or invalid coordinates, but for a simple lookup tool this is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with the core purpose, then parameter details, then return fields, then scope boundaries. It loses points for the 'Athlete'/'Athleta' typo and a slight redundancy between 'and/or coordinates' and 'Provide search, or both lat and lng'.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a four-parameter store-locator with no output schema, the description provides everything an agent needs: parameters, brand values, defaults, input constraints, return fields, and what the tool does not do. It also names the relevant alternative, making it complete for tool selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers each parameter at 100%, but the description adds real value by enumerating brand values (`on`, `gap`, `br`, `at`) and the default. It also reinforces the combined lat/lng requirement that is only implicit in the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a concrete action (find physical store locations) and names the four supported brands. It also explicitly says this tool is location search only and differentiates it from oldnavy-product-availability, so an agent can tell the store locator apart from an inventory tool without opening the schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It clearly states when to use the tool (location search) and when not to use it ('does not report per-item, per-store stock levels') while pointing to oldnavy-product-availability as the alternative. The reference is slightly imprecise because the actual sibling is named oldnavy_product_availability, but the boundary is still explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses that results include inline live availability and that the tool is credential-free, adding useful behavior context. However, it omits details like pagination or result limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the core purpose, and every clause adds value. No redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all key input dimensions (term, location, time, party size) and notes the live availability output. Without an output schema, the availability note helps predict returns, but deeper response structure and edge-case behaviors are not described.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all parameters, so baseline is 3. The description adds meaning by explaining 'term' as cuisine/name/neighborhood and clarifying that lat/long define the search center, plus date/time and party size context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies a search over OpenTable restaurants with location, free-text term, date/time, and party size, and highlights inline live availability. This differentiates it from opentable_restaurant (likely detail lookup) and other domain search tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It clearly describes when to use the tool: find restaurants matching a term near a location with availability. It does not explicitly name alternative tools or exclusions, but the context is clear enough for an agent to select it over a restaurant detail tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It transparently discloses that PitchBook gates numeric figures and full lists, and that missing data comes through as empty cells rather than being fabricated. This is valuable behavioral context that prevents the agent from misinterpreting empty results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with the tool's purpose, then content details, then parameter constraint. No fluff, every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 2-parameter tool with no output schema, the description adequately lists what is returned (overview, description, contact/HQ, previews) and the important caveat about gated content. It lacks details on error behavior, but the essential information for invocation and interpretation is present.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers both parameters, so baseline is 3. The description adds value by specifying 'exactly one' of id or url, clarifying mutual exclusivity that the schema does not convey. This is a meaningful semantic addition beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly specifies the resource (PitchBook advisor profile) and the verb (returns). It describes the specific content types (overview, description, contact/HQ, previews) and distinguishes itself from sibling PitchBook tools by focusing on advisors (service providers) rather than companies, funds, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context about what data is returned (free/teaser content) and the subscription gating. Explicitly instructs to pass exactly one of id or url. However, it does not name alternative tools or explicitly state when not to use this tool, though the advisor-specific focus is implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It transparently discloses that the tool returns only free/teaser content and that gated numeric figures appear as empty cells (not fabricated). This is good disclosure of data limitations. It does not discuss authentication or rate limits, but for a read-only data tool this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. The first sentence states the purpose and content, the second adds usage constraints and data limitations. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description explains the return content in detail (overview, description, contact/HQ, preview of investments, exits, co-investors) and addresses the empty cell behavior. This is fairly complete for a simple data retrieval tool, though it could add more about the structure of the response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (both parameters described). The description adds value by clarifying that exactly one of `id` or `url` must be passed and that the URL is an absolute https URL. This goes beyond the schema descriptions, which are simple labels.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as returning the free/teaser content of a PitchBook investor profile, listing specific sections (overview, description, contact/HQ, preview of investments, exits, co-investors). It uses a specific verb 'Returns' and resource 'PitchBook investor profile', distinguishing it from other PitchBook tools like company and fund profiles.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states to pass exactly one of `id` or `url`, which is a clear usage instruction. It also warns that gated figures appear as empty cells, setting expectations. However, it does not mention when not to use this tool compared to siblings like `pitchbook_company` or `pitchbook_fund`, which would improve guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden. It explicitly states 'Credential-free public PlayStation Store data', implying read-only. It describes the output (shelves and collection links) but omits rate limits or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: main action, output, next steps, examples, parameter details. It is efficient but slightly wordy; every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, it describes the return structure (shelves, collection links with category_id) and provides known aliases. It lacks details on pagination or error states, but for a read-only page retrieval, it is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds value by explaining the roles of 'cc' (region/currency) and 'l' (language), and listing known alias values (collections, subscriptions, deals, latest). This goes beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with 'Get a PlayStation Store merchandising page by alias', clearly stating the action and resource. It distinguishes from siblings by explaining how collection links lead to the separate 'playstation_category' tool, avoiding confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides known aliases, explains the purpose of 'cc' and 'l', and describes the output structure with a clear next step (using category_id with playstation_category). However, it lacks explicit when-not-to-use or alternative tool guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. Discloses it is credential-free and public data, and specifies return fields. Lacks details on error handling or missing IDs, but acceptable for a simple lookup.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences front-loaded with purpose. Every sentence adds necessary information without fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, return fields, parameters, and auth. No output schema exists, so description lists return fields adequately. Lacks error handling or rate limits, but sufficient for the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all params (100%), but description adds value by explaining that cc selects store region and currency, and l selects text language. This goes beyond schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it retrieves store details for a single PlayStation product by ID. Lists exact return fields, distinguishing it from sibling tools like playstation_search (list) or playstation_concept.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implicitly suggests use when needing product details by ID. Does not explicitly state alternatives or when not to use, but context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses caching behavior ('responses are cached'), frequency of change ('changes rarely'), authentication needs ('Credential-free'), and data source ('Poshmark's own server-rendered category pages'). This goes beyond basic read/write indication and provides useful operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each earning its place: the first states the purpose and gives examples, the second explains integration with the category endpoint, and the third covers caching, public access, and sourcing. No fluff, front-loaded with the most important information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple zero-parameter, no-output-schema tool, the description is quite complete. It describes what is returned (full taxonomy), gives examples, explains how to use paths, and notes caching and public access. It lacks explicit format details (e.g., whether it's a tree or flat list), but this is a minor gap for a reference-data tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so the schema provides no semantics and the baseline is 4. The description adds no parameter-specific info (there is none), but it does explain the nature and structure of the returned taxonomy, which is what matters for a zero-parameter tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description begins with a clear verb and resource: 'Get the Poshmark department/category browse taxonomy.' It emphasizes 'full department/category browse taxonomy' and provides concrete examples (e.g., Women > Shoes), which distinguishes it from singular tools like poshmark_category. This is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for use: it's reference data, cached, and credential-free, suggesting it's for obtaining the complete taxonomy. It even notes that paths resolve against the category endpoint, implying integration. However, it does not explicitly contrast with sibling tools like poshmark_category or poshmark_brands, so the when-not-to-use guidance is missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It discloses credential-free public access, the source (server-rendered category page and JSON pagination API), and pagination behavior. It does not mention rate limits or error cases, but covers key behavioral aspects for a read-only browse tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences with no filler. The first sentence states the core action, the second adds context, and the third explains pagination and data source.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is sufficient for a paginated browse tool: it covers input, output page concept, pagination cursor, and access model. Without an output schema, it stops short of listing returned fields, but the 'normalized Poshmark listings' phrase gives a reasonable expectation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes both parameters (100% coverage). The description adds value by giving concrete path examples and explaining the max_id flow ('previous response's next_max_id'), reinforcing the schema without redundancy.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Browse Poshmark listings by category' and specifies it returns 'a page of normalized Poshmark listings for a given category path.' Examples like 'Women-Shoes, Men-Shirts' ground the concept, distinguishing it from sibling tools like poshmark_search or poshmark_brand.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives concrete usage context: 'same browsing view as Poshmark's own category pages' and explains pagination via 'Pass a previous response's next_max_id back as max_id to fetch the next page.' It does not explicitly mention alternatives or when-not-to-use, but the browsing semantics are clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It adds valuable context by stating the output is 'normalized public posts' and discloses the 503/Retry-After rate-limiting behavior. While it doesn't detail the return structure or pagination defaults, it goes beyond the raw schema and gives the agent useful expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise sentences. The first states the core purpose, the second provides a clear alternative, and the third gives practical error-handling advice. Every sentence earns its place with no fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with no required parameters and no output schema, the description is quite complete. It covers purpose, scope, alternatives, and rate-limiting behavior. It doesn't detail the exact return object, but 'normalized public posts' gives a reasonable expectation. This is a solid, well-rounded description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% coverage for all parameters (sort, time, after, limit), so the baseline is 3. The description doesn't add additional parameter-level meaning beyond what the schema already explains, so no extra credit is warranted.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb+resource: 'List Reddit trends.' It further clarifies scope as 'broad Reddit hot, new, rising, or top feeds' and explicitly distinguishes itself from subreddit-specific tools by pointing to an alternative endpoint. This makes the purpose unmistakable and differentiates it from sibling Reddit tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool (for broad Reddit trends) and gives a clear alternative: 'For subreddit-specific trends, use `/reddit/subreddit/{subreddit}/posts` with sort=hot, sort=new, sort=rising, or sort=top.' It also provides actionable guidance for handling 503 throttling responses, which helps the agent decide when retrying is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully carries the burden. It clearly discloses what the tool returns (metadata, scorecard, reviews). No hidden side effects or limitations are mentioned, but for a read-only tool, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at two sentences, front-loaded with the tool's purpose. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately covers the return values (metadata, scorecard, reviews). It could specify that it returns a single movie object, but the current level is sufficient for an agent to understand the output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both 'path' and 'url'. The description adds critical semantic detail: 'Pass exactly one of `path` or `url`', indicating mutual exclusivity not captured in the schema. This significantly helps the agent understand parameter constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns 'Rotten Tomatoes movie detail' with specific data types (metadata, scorecard, audience reviews). It effectively distinguishes from siblings like 'rottentomatoes_movie_reviews' and 'rottentomatoes_search' by focusing on a single movie's detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly instructs to 'Pass exactly one of `path` or `url`', which is useful guidance. However, it does not explicitly state when to use this tool over siblings like 'rottentomatoes_movie_reviews' or 'rottentomatoes_browse_movies', though the context implies it's for getting detailed info on a specific movie.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full disclosure burden. It does so well: it explicitly explains that only the trailing id from a URL is used, that unrecognized ids return a genuine zero-result response instead of an error, and that pagination is real and page-based. It also enumerates the normalized product fields returned, giving unusual transparency into what to expect.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences with no filler. The first sentence states the core purpose, the second covers parameter semantics, and the third covers error behavior and output. Each sentence adds distinct, necessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, so the description reasonably compensates by listing the normalized product fields, pagination behavior, and error semantics. It doesn't describe the exact output shape, page size, or maximum page count, but an agent has enough to select and invoke the tool correctly for a category-browsing task.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% coverage of both parameters. The description adds valuable semantics beyond the schema: id accepts both a bare numeric id and a full /browse/{slug}/{id} URL, and only the trailing id is used. This directly helps an agent extract the correct value from ambiguous user input.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Browse a Sam's Club category or collection' and clearly states it returns the product grid. This distinguishes the tool from product-level or search-level siblings like samsclub_product and samsclub_departments without needing to inspect those tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly says when to use this tool: to browse a Sam's Club category or collection page's product grid. It also gives concrete input guidance for how ids can be provided and how pagination works. It does not explicitly name alternative tools or exclusion conditions, but the usage context is unambiguous and complete enough for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing behavior, and it does so well: it states it is a read-only list, identifies the taxonomy source, and discloses the meaningful distinction between 'browse', 'cp', and empty link types. The caveat that content/landing pages do not reliably carry a product grid is a non-obvious behavioral detail that goes beyond a baseline definition. However, it could also mention pagination/count, but it says 'full taxonomy', so completeness is implied.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact overall and the most important info (listing the taxonomy) is front-loaded. The first and second sentences are slightly redundant ('List' vs 'Returns' the taxonomy), but the second adds specificity about the 'All Departments' page and top-level/subcategory structure. The link-type detail is essential and efficiently packed into one sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, so the description must completely define what the agent will receive, and it does: the full department/category taxonomy with subcategory lists and explicit link-type semantics. It even explains what each link type means and how 'browse' pairs with a downstream category endpoint. With zero parameters, there is no other contextual segment missing for an agent to correctly invoke this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters and 100% coverage, so there is nothing for the description to compensate for. The zero-parameter baseline is 4, and the description adds no misleading parameter guidance. There are no enums or required fields to explain.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'List' with the resource 'Sam's Club departments and categories', and then elaborates that it returns the full department/category taxonomy with top-level departments and subcategories. It also ties the link types to sibling endpoints, so the agent knows this tool is for taxonomy enumeration rather than category browsing or product retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states this tool returns the full Sam's Club taxonomy as shown on the 'All Departments' page, which implicitly tells the agent when to call it (when a complete department/category list is needed). It doesn't explicitly name alternatives or exclusions, but the note that 'browse' links pair directly with GET /samsclub/category helps an agent understand how the output feeds into sibling tools. No contradictory or misleading guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses the read-only nature, returned fields, and authentication-free access. It does not mention rate limits or pagination, but for a simple list endpoint, it is sufficiently transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with purpose, followed by return fields and usage hints. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given six parameters and no output schema, the description covers purpose, return fields, and identification. It lacks default limit info and pagination details but is adequate for agent decision-making and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with all parameters described. The description adds value by emphasizing that cik or ticker is needed (implied mutual exclusivity) and that form/date parameters are for filtering, enhancing understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List a company's EDGAR filings' with specific return fields (form, dates, URL) and company profile fields. It distinguishes from sibling tools like sec_filing (single filing) and sec_company_search (company lookup) by targeting a company's submissions list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear usage: 'Provide cik or ticker' and mentions filtering by form type and date range via parameters. It notes 'Credential-free public SEC data' but lacks explicit when-not-to-use or comparisons with siblings for specific use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the transparency burden and handles it well. It reveals that the data comes from Sephora's credential-free public JSON-LD, that only the full page slug resolves (not an arbitrary or partial slug), and that the product detail includes only a sample of recent reviews. These are behaviors beyond what the schema alone can convey.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description has no wasted words. The main resource/issue action is in the first sentence, followed by a compact list of what the full detail includes, then a practical example that disambiguates the parameter. All this in four sentences, and each sentence carries unique, necessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with a single parameter and no output schema, the description is nearly complete. A full list of distinct output fields (variants, price, availability, rating, review count, sample reviews) and the slug-resolution warning tell the agent enough to invoke it successfully. A clear error-handling note for invalid slugs would be the last minor missing piece.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema description of the product_id parameter ('Full Sephora product-page slug') is high-confidence, but the tool description adds substantial value with a concrete example, a copy-it-from-the-URL instruction segment, and a caveat about partial slugs. That transforms a generic parameter name into an unambiguous, operational instruction.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states a specific verb—'Returns'—and a specific resource: one Sephora product's full detail. It enumerates the exact content fields (every color/shade variant with price, availability, rating, review count, and a sample of recent reviews), making it unmistakably distinct from search, reviews, and other Sephora siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context on when to invoke the tool: whenever an agent needs a single product's complete detail by its full product-page slug. It also explains which identifier format works and warns against partial slugs. It does not explicitly list alternative tools or exclusions, but the scope is precise enough for an agent to choose it correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes source (store typeahead JSON), return fields, and approximate result count; no annotations provided but description covers essential behavior for a search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Concise, two-sentence description with all key information front-loaded; no superfluous text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Complete for a simple search tool: explains source, result fields, alternatives; no output schema needed as return is described.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage and description adds no additional meaning beyond what schema already provides for parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches the Steam store by title and is best for title-to-appid lookup, distinguishing it from the faceted search sibling tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states best use case and points to an alternative tool for faceted/paginated search, also notes it's credential-free.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does well: it discloses that the data is credential-free, public, and sourced from StockX's own navigation API, which is valuable behavioral context. It stops short of specifying response format or pagination, but for a no-parameter taxonomy endpoint, this is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three dense sentences: the first states the action and resource, the second details the return with a concrete example, the third covers access and provenance. No wasted words, and key information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple zero-parameter taxonomy tool, the description is complete: it explains what the data is, provides an example structure, and notes it's the backing for StockX's site menu. The only minor gap is the exact response format, but the example and return description mitigate this.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the description correctly adds no param details. The baseline for 0 params is 4; the description adds context about the data being the exact taxonomy used by the search endpoint, which is more than the empty schema conveys.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb+resource ('Get StockX category/subcategory taxonomy') and clearly states what is returned: the full category/subcategory reference with 7 top-level categories. It also distinguishes from siblings by explicitly linking to GET /stockx/search's category parameter, making its role as the taxonomy source for search unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly tells when to use this tool: when you need valid category/subcategory values for the StockX search tool's category parameter. It also notes it is credential-free public data, which helps the agent avoid unnecessary auth setup. However, it does not explicitly state when not to use it or mention alternatives that might be better suited.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite having no annotations, the description discloses meaningful behavioral details: the output includes 'current' top-level menu, a grouped shop-all directory, category IDs, and canonical URLs. This tells the user what information to expect and implies a read-only listing operation. It does not mention rate limits or data freshness, but for a zero-parameter catalog tool, the transparency is strong.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no filler. The first sentence states the action, and the second provides necessary detail about the returned content. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, zero-parameter listing tool with no output schema, this description is sufficiently complete. It explains what is returned (top-level menu, grouped shop-all directory, IDs, URLs) and the scope ('all categories'). Minor gaps like update frequency could be added, but overall the context is solid.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so there is nothing to explain. The baseline for 0-param tools is 4, and the description appropriately focuses on output rather than parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List all Target categories' uses a clear verb and resource, and further specifies the output: 'top-level category menu and the complete grouped shop-all directory, including category ids and canonical URLs.' This clearly distinguishes it from siblings like target_category_products or target_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use this tool: whenever you need the full Target category structure. It describes the scope ('all categories') and what to expect, but does not explicitly mention alternatives or exclusion criteria. This provides clear context without explicit when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full transparency burden. It discloses pagination, the inclusion of all dynamic filter groups/options in each response, and the exact sort enum values, which is substantive behavioral information. It doesn't mention authorization or rate limits, but for a browse operation these are less critical.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four tightly-focused sentences: purpose, pagination, filter behavior, and sort values. Every sentence adds distinct information; no repetition or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description covers the essential browsing flow: input category, pagination, filters, and sort. It contextually links to target-categories for valid ids. It could be improved by noting the optional store_id effect on pricing, but schema already covers that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the baseline is 3. The description adds value by enumerating the allowed sort values and clarifying that filter_ids is a comma-separated list of option ids, and that category ids come from target-categories. This goes a step beyond the schema's terse descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Browse Target category products' – a specific verb and resource. It distinguishes from sibling tools by specifying it returns paginated products keyed by category id (from target-categories), which contrasts with target_product (single product) and target_search (search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It clearly implies the tool is used when you have a category id from target-categories and want to browse products in that category. It also explains how to use filter_ids for further refinement. However, it doesn't explicitly name alternative tools or state when not to use it, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden, and it delivers meaningful behavioral context: what is returned (normalized products + all filter groups/options), the round-trip filter_ids interaction, the no-results semantics, and the accepted sort enum values. It does not mention authentication, rate limits, or potential side effects, but for a search tool these are less critical and the provided details go beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four sentences, all dense with useful information and no filler. It front-loads the core purpose, then progressively details the filter mechanism, no-results behavior, and sort options. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema, the description reasonably communicates the high-level response shape (products, total, filter groups/options) and the key invocation details (filter_ids, sort values). It does not exhaustively describe product fields or filter group structure, but for a search tool with five parameters this is a practical level of completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds value by enumerating the valid sort values ('relevance', 'featured', 'price-low', 'price-high', 'rating', 'bestselling', 'newest') that the schema only vaguely describes as 'Result order'. It also clarifies how filter_ids interacts with the returned filter groups, which adds semantic meaning beyond the schema's generic 'Comma-separated Target filter option ids'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a clear verb-resource pair ('Search Target products') and immediately specifies the key differentiator from sibling tools: it returns normalized products plus every filter group and option for the result set. This distinguishes it from target_product, target_categories, and target_filter_options by describing its combined search+filter-faceting behavior.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear operational guidance: how to use filter_ids (pass option ids back as a comma-separated list), and that a zero total with an empty products list is a valid no-results response. It implies when to use this tool (for search with filter faceting) but does not explicitly name alternatives or state when not to use it, so it misses the top criterion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It accurately describes a read-only retrieval of metadata with no side effects. It does not mention caching or rate limits, but for a simple metadata endpoint, the behavior is sufficiently disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only two sentences, front-loaded with the verb, and contains no redundant information. Every word is necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no parameters, the description explains what the metadata contains (country and industry) and its purpose. However, it could add more detail about the structure or format of the returned data.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema is empty with 100% coverage. Per guidelines, 0 parameters warrants a baseline of 4. No additional parameter semantics are needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves TikTok popular-trend country and industry metadata, using the specific verb 'retrieve' and identifying the resource as metadata for popular-trend endpoints. It distinguishes itself from sibling tools like tiktok_popular_trend_creator and tiktok_trending by specifying the metadata nature.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context—it returns metadata used by popular-trend endpoints, indicating it should be called before those endpoints. However, it does not explicitly state when to use or not use it, nor mention alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It discloses the data source (Trip.com's server-rendered hotel-list page), the credential-free nature of the data, and the return format (normalized hotel summaries with specific fields). It does not cover edge cases like invalid URL pairs or pagination, but for a read-only extraction tool, it provides above-average behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: it opens with the purpose, lists the return fields, explains the required input format, and states the data source. Every sentence adds value without repetition, and the most critical information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema, the description provides a reasonably complete picture: it specifies the input parameters, the output structure, and the limitation of no free-text search. It does not detail error handling or response size, but for a simple list-extraction tool, the description gives sufficient context for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes both parameters fully, and the description adds meaningful context by explaining that city_slug and city_id must come together as a pair from a specific URL format. This goes beyond the schema's individual field descriptions, making the parameter semantics clearer for an agent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches Trip.com hotels by city and explicitly lists the returned data fields (name, location, star rating, etc.). It distinguishes itself from other tools by noting it returns Trip.com's own featured hotels page and requires a specific city_slug/city_id pair, which is a unique operational constraint.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use the tool: when you have the exact city_slug and city_id from a known Trip.com URL. It also explains that Trip.com does not expose a free-text city search, informing the agent not to attempt that with this tool. However, it does not explicitly name alternative tools for free-text search, so it falls short of the highest bar for when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the source page, returned metrics, and data verification source, which is transparent for a read-only listing tool. However, it does not mention side effects, rate limits, or authorization needs, though these are less critical for a simple get operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences with no wasted words. It front-loads the core purpose and follows with relevant details about metrics and data verification.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and no output schema, the description sufficiently explains what the tool returns, its source, and key metrics. It is complete for an agent to understand and invoke the tool appropriately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no parameters, so the description provides all semantic value. It explains that the tool returns all for-sale startups on the acquire page without any filtering, which is clear and complete.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves TrustMRR acquisition listings from the public /acquire marketplace page, specifying deal metrics (asking price, revenue, multiple, growth) and noting verified revenue from payment providers. This distinct verb and resource set it apart from sibling tools like trustmrr_startups or trustmrr_marketplace.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for fetching acquisition listings but does not provide explicit guidance on when to use this tool versus alternatives (e.g., trustmrr_marketplace or trustmrr_startups). No exclusion criteria or context-specific recommendations are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since annotations are absent, the description carries the full behavioral disclosure burden. It explicitly states that the tool is for reading public data, defines the returned segment content, and covers the important edge case where empty segments list is returned rather than an error. This is exceptionally transparent for a read-only tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and to the point, with each sentence adding new context. There is slight redundancy between the first and second sentences, but overall the structure is efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description adequately compensates for the absence of an output schema by describing what the returned segments will contain, and it also covers a special case. Combined with the schema's parameter documentation, no critical gaps remain at the expected decision and invocation level.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides comprehensive descriptions for both parameters, including channel login format and weeks default/max, so parameter semantics are fully covered by the schema. The tool description itself adds no parameter-specific guidance, which matches the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Get a Twitch channel's broadcast schedule,' with enough detail to know it covers planned segments and their fields. This clearly distinguishes it from other Twitch-related siblings like stream, video, or clip retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly communicates that this tool is for fetching a Twitch channel's upcoming scheduled segments starting today. It does not explicitly name alternatives or exclusions, but the scheduling context is strong enough for an agent to infer when it is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden, and it delivers: it discloses the authoritative data source, the corpus scope (granted patents and published applications), the normalization behavior of bibliographic output, the public nature of the data, and the advanced query syntax capabilities. It does not explicitly discuss pagination limits or error behavior, but the described behavior goes well beyond what the input schema provides.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Every sentence earns its place: the first establishes scope, the second the output shape, the third the crucial query-parameter semantics with examples, and the fourth adds provenance. The core action is front-loaded, and the density is appropriate for a tool with a complex query syntax.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This four-parameter search tool has no output schema and no annotations, and the description compensates exceptionally well by enumerating returned fields, scoping the corpus, and detailing query capabilities. The only gaps are that the full field-code table is delegated externally and the relationship to usptoppubs_detail (when to fetch single-patent details) is left implicit. Doesn't explain the output schema boundaries, but also doesn't need to.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes all four parameters (100% coverage), so the baseline is 3. The description adds meaningful value beyond the schema by giving concrete query syntax examples (battery.ti., Microsoft.as, date-range patterns) and directing the agent to the markdown doc for the full field-code table, which materially improves the chance of constructing a valid query.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description states a specific verb and resource: searches USPTO Patent Public Search full-text index for granted patents and published applications, returning normalized bibliographic results with a concrete field list. The phrase USPTO's own distinguishes it from the googlepatents_* siblings, and the emphasis on bibliographic results separates it from usptoppubs_detail. No ambiguity about what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Clear context is provided: this is for querying USPTO's official full-text patent index, with the qualifier USPTO's own contrasting with Google-based patent search alternatives. However, it does not explicitly name alternatives like googlepatents_search or state when not to use this tool versus usptoppubs_detail.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the behavioral burden. It does so by specifying the exact output shape (title, description, author, publish/update time, section, image, keywords, body paragraphs) and the input constraint of a canonical URL. It does not mention error cases or read-only status, but for a simple fetch tool the behavioral disclosure is adequate and well beyond a bare verb phrase.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no filler. The first sentence delivers the core purpose and output details, while the second provides necessary input context. Every sentence earns its place and the most important information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no output schema and no annotations, the description supplies the essential return fields and the input domain, which is largely complete. It could add error/edge-case expectations or an explicit 'this is a read-only operation,' but those are minor gaps for a simple article-retrieval tool with the purpose this clearly stated.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds value by clarifying what kind of URL is expected — 'canonical shopping.yahoo.com article URL, such as one returned by the home or category story streams.' This helps the agent infer the correct URL format and provenance, providing meaning beyond the schema's short 'Canonical article URL' description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Returns a single Yahoo Shopping article's full content.' It also enumerates the exact fields returned (title, description, author, etc.), so an agent knows precisely what the tool does. The mention of 'one returned by the home or category story streams' differentiates it from sibling list/stream tools like yahoo_shopping_home and yahoo_shopping_category.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: use this tool to fetch full article content given a canonical shopping.yahoo.com URL. It implicitly tells the agent that article URLs come from the home or category story streams. It does not explicitly name alternatives or exclusion criteria, but the 'when you already have a URL' context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosure. It states the data source is Yahoo Shopping's own server-rendered homepage and that it returns an editorial feed with specific fields. This gives an agent a clear model of the data, avoids implying search behavior, and implicitly signals a read-only fetch.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-organized and front-loaded, beginning with what the tool returns. Every sentence adds value, including the explicit non-search qualification, with no redundant repetition of schema annotations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, simple homepage feed, the description is mostly complete: it specifies what is returned and why it is not a product search API. It could mention pagination or the ordering of the feed, but that is minor for a homepage feed's usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters, and the schema is completely empty with 100% coverage. The description confirms that no search query or catalog is available, which supports the fact that the tool expects no input. Baseline for zero-parameter tools is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns Yahoo Shopping's homepage editorial story feed, listing the exact fields (title, destination URL, category, thumbnail). It differentiates its scope as editorial/deals content vs a product-search API, providing clear distinction for an agent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly notes what this tool is not, a product-search API, and clarifies that shopping.yahoo.com has no searchable catalog. This helps an agent avoid misusing it for product search. It does not explicitly name sibling alternatives like yahoo_shopping_category, but the exclusion is strong enough to guide basic usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the disclosure burden. It communicates that the tool is read-only ('Returns') and specifies the item fields and scope ('each retailer with a dedicated store page'), which covers the main behavioral expectations for a zero-parameter directory tool. It omits notes on pagination, rate limits, or auth, but those are less critical for this simple listing endpoint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and puts the meaningful content in the second sentence, including the output fields and the follow-up usage of a slug. The opening phrase 'Yahoo Shopping retailer store directory' is a mild repetition of the tool name, but the overall length is well controlled and front-loaded enough for an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema, the description is complete: it says what the endpoint returns, which retailers are included, the exact fields, and how the returned slugs are consumed by another tool. An agent can invoke this tool without needing any additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so the rubric baseline is 4. The description adds no parameter information, but none is needed; it instead explains the output and the downstream use of a returned slug, which is the only 'parameter-like' concept here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Returns') and a well-defined resource ('Yahoo Shopping's retailer store directory'), and enumerates the exact output fields: slug, display name, and logo image. It distinguishes itself from the sibling yahoo_shopping_store by indicating that this is the directory while the other endpoint consumes a slug for store deals.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies this is used to fetch the store directory and obtain slugs, then explicitly directs the agent to use GET /yahoo-shopping/store with a slug to read current deals. It does not explicitly state 'use this for listing stores and not for deal lookup', but the cross-reference makes the intended workflow clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It discloses the data source (sports.yahoo.com's server-rendered page), the return sections (bio/overview plus current-season stats), and the ID derivation path. It stops short of describing the result format or failure modes, but the primary behavior is clearly conveyed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The first sentence is front-loaded with the tool's purpose and contents, and the league list, though long, is necessary because the schema does not define an enum. The description is compact relative to its domain knowledge, though the league enumeration makes it lengthy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter, no-output-schema tool, the description covers the essential invocation: league selection, player ID derivation, and the resulting data. It would be more complete with an explicit note on return shape or edge cases, but the core call is well specified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only says 'League key' and 'Numeric Yahoo Sports player id', but the description goes far beyond that by enumerating all 24 supported league values and specifying exactly how to extract the numeric player ID from a roster's URL path. This is directly actionable and reduces parameter errors.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Opens with a specific verb and resource: 'Returns one player's bio/overview' and lists concrete content (position, jersey, status, injury, physicals, college, draft position, current-season stats). This is clearly the single-player Yahoo detail endpoint, distinguishing it from siblings like yahoo_sports_team_roster or yahoo_sports_team.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Clear context is provided for when to use this tool: when you need a specific Yahoo Sports player's full profile/stats. It also gives the mounting valuable usage detail that the player ID is the last path segment of a roster response's player URL. No explicit alternatives are named or excluded, but the source and purpose are unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It explicitly says results come from sports.yahoo.com's own server-rendered roster page, which suggests a stable read-only HTML page source. It also lists exactly which player attributes are included. It neither overpromises nor contradicts the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficient: it opens with the core purpose, then enumerates the returned fields, then gives the league enum and the input guidance. The long league list is necessary because the schema lacks enums, so it is not wasteful. The key instructions are front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter read-only roster tool, the description covers all essential information: the exact data returned, the source, the legal league values, and how to find a team slug. No output schema is present, but the caller can infer the response will contain the listed roster fields. There is no missing information that would prevent correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only gives the bare labels 'Yahoo Sports team slug' and 'League key', but the description augments this considerably by enumerating all accepted league values and explaining how to obtain a valid team slug from the scoreboard/standings response with examples. The parameter guidance is comprehensive and directly actionable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'Returns a team's full roster' and lists the exact fields (position, jersey number, status, injury, physicals, college, and experience), giving an agent a clear idea of what it will get. The reference to the Yahoo Sports server-rendered roster page distinguishes it from sibling roster tools like espn_team_roster or mlb_team_roster.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives actionable usage context: to get the required team param, use the scoreboard or standings response, with concrete examples such as 'green-bay' and 'la-lakers'. It does not explicitly explain when to choose this tool over a sibling roster provider, but the Yahoo Sports framing and schema make the appropriate scenario clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations and no output schema, the description carries the behavioral burden effectively by disclosing that it takes no parameters, is a fixed snapshot, is not date-queryable, and comes from a server-rendered Yahoo Sports page. It could mention staleness or empty-snapshot behavior, but core behavior is clear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Each sentence is informative: what it returns, what fields to expect, and the key disambiguation that it is not a query endpoint. The description is front-loaded with the primary purpose and has minimal redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter snapshot tool with no output schema, the description covers the main facts an agent needs: source, scope, result fields, and absence of parameters. It does not fully define 'fixed-size' or edge cases like empty data, but these are not blockers for invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and an empty schema, so the baseline is 4. The description reinforces this by explicitly stating there is nothing to parameterize and explicitly warning against by-date usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource ('Returns ... tennis matches') and lists the included payload fields (tournament, round, players, per-set scores, winner, status). It clearly identifies the tool as a snapshot and differentiates it from by-date and schedule-style tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit guidance on when to use it: current/recently-completed tennis matches, no parameters, fixed-size right-now snapshot. It explicitly excludes by-date queries, though it does not name a specific alternative tool like the tennis schedule endpoint.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly states the data is static, credential-free, and makes no upstream request, and it notes the return includes each market's domain. This is solid but does not mention output shape or any failure modes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the primary purpose, and each sentence adds meaningful context: what it lists, how it relates to sibling tools, and its static credential-free nature. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter static metadata tool with no output schema, the description is nearly complete. It states the returned data (storefronts and domains) and names the tools it supports. It could specify the exact response format or potential edge cases, but the low complexity makes this a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and an empty schema, so there are no parameter semantics to explain. The baseline of 4 applies because the description does not need to compensate for undocumented parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'List' and resource 'supported Zalando country storefronts', and explicitly references the market parameter on zalando-search, zalando-category, and zalando-product. This clearly distinguishes it from sibling Zalando tools and other unrelated tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It identifies the context of use: to see which storefronts are currently supported by the required market parameter on the Zalando search/category/product tools. It does not explicitly name alternatives or state when not to use it, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and discloses meaningful behavior: returns normalized result cards (price, brand, image), includes upstream total_count, limits results to the first page, and requires market with no default as one of 25 storefronts. This sets agent expectations for output and limitations beyond the basic search function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Four concise sentences, each earning its place: purpose, return format, pagination limitation, and market requirement with reference. The description is front-loaded with the core action and avoids filler, making it efficient and scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and no annotations, the description covers essential context: what is searched, key output fields (price, brand, image), the pagination limit, total_count, and parameter requirements. It stops short of fully specifying result structure or sort order, but provides enough for an agent to invoke the tool and interpret typical results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% description coverage, so baseline is 3. The description adds crucial meaning for `market` — it is required, has no default, accepts 25 country storefronts, and the full list is available via zalando-markets — going well beyond the schema's vague 'Zalando country storefront' label.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description opens with 'Search Zalando products' and elaborates with 'Searches a Zalando country storefront by keyword', clearly specifying verb, resource, and scope. It distinguishes itself from siblings like zalando_suggest, zalando_category, and zalando_product by focusing on keyword search and returning normalized result cards, and explicitly references zalando-markets for the market list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context for use: keyword search on a country storefront, market is required with no default, only the first page is returned (pagination not supported), and points to zalando-markets for accepted storefronts. It lacks explicit 'when not to use' statements for alternatives, but the stated constraints and sibling reference give practical guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the return type ('query completions') and a key behavioral constraint (market has no default, must be specified). It also warns that the market list is dynamic by referencing zalando-markets. This is helpful, though it does not mention rate limits, response size, or other potential quirks.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured. It front-loads the purpose, then provides an illustrative example, then states the market requirement and points to a reference tool. Each sentence adds meaningful information without redundancy, making it easy to read and parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter suggest tool with no output schema, the description is quite complete. It covers purpose, example, and parameter constraints, and it cross-references zalando-markets for dynamic data. It could be slightly more detailed about the response structure or any limits, but given the simplicity, this is mostly sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers both parameters fully (100% coverage). The description adds value by giving a concrete example for 'q' ("running sho" -> "running shoes") and clarifying that 'market' accepts 25 country storefronts. However, it stops short of specifying the exact format or allowed values, leaving some ambiguity for the market parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Autocomplete a Zalando search query' and specifically notes it returns 'Zalando's own search-box query completions'. It provides a concrete example ("running sho" -> "running shoes") and distinguishes itself from other Zalando tools by focusing on autocomplete rather than full search results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: for partial keyword autocomplete. It also highlights an important usage constraint: 'market is required (there is no default storefront)', and points to zalando-markets for the list of allowed values. However, it does not explicitly mention exclusions or alternative tools for similar tasks, such as zalando_search for full search.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses non-obvious behavior such as real page-based pagination, per-field filter facets, accepted URL/id input forms, and a 404 for unrecognized brands. The main omitted details are the exact response fields, but the core behavioral contract is well covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short, front-loaded, and contains no filler. The first sentence states the purpose, the second describes the return content, and the third clarifies input forms and error behavior. Every sentence contributes something the agent needs.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is no output schema, the description still tells the caller enough to select the tool and understand the result: a product grid with pagination and filter facets, plus the 404 error contract. It could be more complete with exact response fields, but for a browse tool this is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents both parameters at 100% coverage, so the baseline is met. The description adds genuine value by distinguishing accepted brand formats: a full brand URL, the slug/id.zso path, or the opaque id returned by GET /zappos/brands. This materially reduces ambiguity around the main parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific operation: browsing a Zappos brand page and retrieving its product grid. It also differentiates the return shape—real page-based pagination and per-field filter facets—which clearly separates this from sibling tools like zappos_brands or zappos_search. The resource and behavior are unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use the tool: when an agent wants a Zappos brand page's product grid. It also tells the caller where the brand identifier can come from, including GET /zappos/brands, which is useful practical guidance. It does not name exclusionary alternatives or explicitly say when not to use it, but the context is strong enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations to fall back on, the description does a solid job: it discloses the 'real' pagination, enumerates returned product fields, describes filterable facets with live counts and drill-down URLs, and calls out the out-of-range-page edge case. It doesn't cover authentication or rate limits, but for a search tool the description is well above baseline transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense, useful, and only three sentences long. A slight redundancy exists in the first two statements ('Search Zappos products' followed by 'Searches Zappos's product catalog by keyword'), but each subsequent sentence adds significant detail, so the overall structure is still efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema, the description is remarkably complete: it enumerates the returned product attributes and the enriched facet objects with live counts and URLs, and it covers the pagination edge case. The only thing an agent might need beyond this is knowing the default result count per page, which is not essential to invoking the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents both parameters at 100% coverage, so the baseline is 3. The description adds meaningful behavioral meaning to page handling by explaining that requesting a page beyond results yields an empty result rather than an error, and it reinforces that pagination is 1-based and real. That extra depth justifies a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a clear verb and resource ('Search Zappos products') and goes on to specify that it searches by keyword, uses page-based pagination, and returns a defined product set. This makes it unambiguous and distinguishes it from sibling detail tools like zappos_product and from brand-only or suggest tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly states that the tool is for keyword searching of the Zappos catalog, which gives the agent a clear condition for use. It does not explicitly name alternative tools or say when not to use it, but the keyword-search context is strong enough to select it among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the data source (Zara's own category navigation data), the scope (US storefront), the return nature (full category/subcategory navigation tree), and that no query parameters are taken. While it does not describe output format or pagination, there are no hidden effects or parameters to disclose for a simple taxonomy list.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three purposeful sentences, front-loaded with the action and resource, followed by scope, source, and downstream usage. Every sentence adds useful information, and there is no padding or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity, no-parameter tool, the description covers what is returned, the scope, the source, and how to use the resulting ids. There is no output schema, so a bit more detail on exact entry fields would have been helpful, but the core information an agent needs to call it correctly is present.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema already reflects this with an empty properties object. The description reinforces this by stating 'Takes no query parameters,' which is useful for an agent deciding whether it needs to provide inputs. With no parameters to describe, the baseline is appropriately high.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description begins with a clear verb and resource: 'List Zara's category and subcategory taxonomy.' It further specifies the US storefront and top-level sections, distinguishing it from related tools like zara_category_products and zara_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains that the returned ids are meant to be passed as categoryId to zara-category-products, giving downstream guidance. It does not explicitly state when not to use alternatives, but the no-parameter and taxonomy-only scope is clear. Minor issue: it references 'zara-category-products' with hyphens while the sibling tool is named 'zara_category_products', which could cause confusion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully carries the transparency burden. It discloses the credential-free/public nature, the city_id precedence rule, the pre-filter limit semantics, the data source relationship to hotel search, and the promise of 'full listing detail' for each result. This goes well beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each earning its place: the core purpose, the filtering/data-source behavior, and the input selection semantics. It is front-loaded and free of filler, being appropriately dense for a tool with no annotations and a non-trivial filtering mechanism.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema, the description provides a thorough mental model: what is returned, how results are filtered, how inputs interact, and what authentication is required. Combined with the fully documented schema parameters, the tool is well-specified for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the schema descriptions already document the precedence rule, the free-text resolution, the 1-indexed page, and the limit semantics. The description paraphrases these without adding new parameter-specific meaning, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Search') plus a clear resource ('Agoda Homes & Apartments by city'). It distinguishes from sibling agoda_hotels_search by explicitly stating results are 'filtered to non-hotel accommodation types' and drawn from the same city search as hotel search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear usage context: it is the apartment/homes-focused counterpart to hotel search and explains the two input modes (city_id vs free-text city). It implies when to use this tool (when you need non-hotel listings) but does not explicitly name the alternative tool or state exclusion conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for behavioral disclosure. It lists valid device enum values, explains the section enum, and warns about the 400 error for watch+arcade. It also references the source content (apps.apple.com device switcher). While it omits output shape or pagination, it covers the most important behavioral traits for this simple retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, each contributing unique value: the first identifies the action, the second gives an external reference, and the third details the enums and edge case. It is front-loaded and contains no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description captures the tool's core behavior, parameter enums, and an error scenario. It doesn't discuss lang/country defaults, but the schema descriptions for those are adequate. For the tool's complexity, the description is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides generic descriptions like 'Apple device catalog' and 'Editorial section within the device.' The description enriches these by enumerating exact values, defining what each section means, and flagging an invalid combination. This is essential guidance for an agent to choose correct parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description begins with a clear action and target: 'Retrieve an App Store device or Arcade editorial landing page.' It specifies the output as curated editorial shelves and differentiates itself from sibling tools like appstore_search or appstore_list by focusing on per-device landing pages.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context on when to use: for per-device App Store editorial pages, matching apps.apple.com's device switcher. It details device and section choices but does not explicitly name alternatives or exclusion cases, though the specificity makes the usage obvious.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full transparency burden. It discloses the response content (fields included), clarifies optionality ('with answers, when present'), and explicitly handles the edge case of no questions (returns an empty list, not an error). It does not mention network/API or other hidden behaviors, but for a read-style retrieval tool the disclosed details are strong.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, each earning its place: first states the main action, second details the returned content, and third explains the SKU source and the empty-list behavior. It is compact, readable, and front-loads the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no output schema and no annotations, the description is fully sufficient: purpose, exact parameter meaning, how to find SKUs, response content, and an important edge case are all documented. There is no missing information that would prevent an agent from selecting and invoking the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single sku parameter, so the baseline is 3. The description adds value by explaining where to find the sku (numeric SKU shown on bestbuy.com product pages and URLs) and clarifying the no-questions behavior, going beyond the schema's basic 'Numeric Best Buy SKU' definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get'), names the exact resource ('Best Buy product's customer questions and answers'), and details the returned fields (question text, answer text, who answered, when). This clearly distinguishes it from sibling tools like bestbuy_product_reviews and bestbuy_product without needing to open their definitions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes its scope and use context explicit: it returns customer Q&A embedded on Best Buy product pages, with no questions yielding an empty list. While it doesn't name alternatives or provide when-not-to-use guidance, the functionality is presented clearly enough that an agent can infer when to choose this tool over the related bestbuy_product/reviews siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It explicitly states the data is credential-free public data sourced from CarMax's mobile-app API, which tells the agent no authentication is needed and gives the data's provenance. It also discloses the output's contents and ordering, though it does not mention rate limits or pagination.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise sentences, front-loaded with the action and resource. Each sentence adds value: first states what it gets, second details the returned fields, and third provides sourcing and auth context. No filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema, the description is complete enough: it states what the tool returns, includes the specific fields (make, image, display order), and clarifies that the data is public and requires no credentials. An agent can confidently invoke this tool without additional information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the schema is empty, so there is no parameter burden to carry. The description reinforces this by calling it a complete 'full make taxonomy' with no inputs needed, matching the baseline for a no-parameter tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and clearly names the resource: CarMax's 'shop by brand' make taxonomy. It further distinguishes the tool by listing exact returned contents (every make, display image, display order), making it distinct from sibling search and vehicle tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly states the tool returns CarMax's full make taxonomy for browsing by brand, providing clear context for when to use it. It does not explicitly name alternatives or exclusions relative to sibling tools, but the purpose is specific enough that confusion is unlikely.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It clarifies it's a read operation returning the related-items shelf and documents defaults for country and lang, providing sufficient behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the main purpose, and includes defaults. Every sentence is necessary and no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description explains the return value (related-items shelf). The tool is simple and complete, with enough context for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter descriptions. The description adds value by stating defaults for country and lang (`country=us`, `lang=en`), which is not in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves related Chrome Web Store items, specifically the related-items shelf from an item's detail page. It distinguishes from siblings like chromewebstore_item (single item) and chromewebstore_search (search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly tells when to use this tool: when you want to see the related items shelf for a given Chrome Web Store item. It does not explicitly mention when not to use or alternatives, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully carries the transparency burden. It discloses the 404 error case, the conditional lca_sponsorship enrichment and its limitations, plus the tech_stack hint when a domain is known. This goes well beyond basic read-only behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the main purpose, and each sentence provides essential context (enrichments and error handling). No fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description covers the base return (company board), conditional enrichments, and failure mode (404). This is sufficient for a simple one-parameter lookup tool, especially given the clarity of the response structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description reinforces that 'id' refers to a board id but doesn't add new details like format, examples, or the source of the id. It meets the minimum bar but doesn't exceed it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get a single company by board id' with a specific verb and resource. It immediately distinguishes itself from related tools like datasets_jobs_companies (list) or datasets_jobs_search by specifying the retrieval-by-ID nature.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context: when you have a board id and want company-level details. It does not explicitly name alternatives or exclusions, but it clearly communicates that this is for a single lookup, differentiating it from search/list tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description discloses key behaviors: output is aggregate per category-over-time cell, thin cells are suppressed, and the returned fields (launch count, upvotes, rating, top product). It does not mention rate limits or authentication, but covers the essential behavioral aspects for correct usage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise yet comprehensive, with clear front-loading of the main purpose. Each sentence adds value: dataset identification, aggregate nature, row structure, suppression behavior, and parameter enums. No unnecessary repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description fully explains the tool's output (aggregate cells with specific metrics) despite no output schema. It covers the dataset, suppression, grouping, sorting, and parameter effects. For a search tool with 9 parameters, it provides sufficient context for accurate use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds value by explaining the meaning of enums (group_by, sort) and the effect of parameters like min_launches (raises suppression floor). It goes beyond the schema by clarifying the aggregate cell dimensions and sort options.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches the Product Hunt trends dataset, specifying the dataset ID and that it returns aggregate launch trends (counts, upvotes, rating, top product) rather than individual products. It distinguishes itself from sibling producthunt tools (e.g., datasets_producthunt_products_search) by emphasizing aggregate-only data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states 'Aggregate-only' and that it never returns individual product records, guiding the AI to use it for trend analysis. It explains grouping and sorting enums. However, it does not explicitly contrast with siblings like datasets_producthunt_trends_facets or provide when-not-to-use, missing some contextual guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It adds valuable context about the data shape ('one document per appid × day; integer cents') and the default sort ('date_desc (default)'). It also explains the intended query patterns. However, it doesn't disclose response format, rate limits, or any edge-case behavior, so it's not a 5.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three tightly packed sentences. The first states the core purpose, the second gives concrete usage patterns, and the third enumerates sort options. No filler or repetition; it earns every word.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Even without an output schema, the description fully prepares an agent to use the tool. It explains the dataset structure, provides two common query recipes, and lists all sort options. The pagination constraints are already in the schema, so the description doesn't need to repeat them. This is complete for a search tool of this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers all five parameters with descriptions (100% coverage), so the baseline is 3. The description adds extra meaning by showing how to combine app_id with sort=date_desc for a price history and how to use date for a snapshot, enriching the schema's plain parameter definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search the steam-prices dataset' and explains it 'Searches the daily price time series for priced games (one document per appid × day; integer cents).' This specifies the exact resource and data granularity, distinguishing it from sibling steam tools like datasets_steam_playercounts_search or datasets_steam_games_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage patterns: 'Pair app_id with sort=date_desc for a game's price history, or pass date for one day's snapshot.' This gives clear context for when to use different parameter combinations, though it doesn't explicitly mention alternatives or when not to use this tool. That stops it from scoring a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral burden. It discloses an important non-obvious behavior: it tries a live refresh first and falls back to a static snapshot on any failure, guaranteeing it never errors. It could elaborate on output structure or data freshness, but the reliability guarantee is meaningful context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two well-structured sentences with no wasted words. The primary action is front-loaded, followed by what is returned, how it is used, and how the tool behaves on failure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, no-output-schema utility, the description is sufficiently complete: it defines the return content, names the consumer endpoints that use it, and explains the failure mode. An agent can decide whether and when to call this tool without ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters and schema coverage is 100%, so there are no parameter semantics to document. The description adds value by explaining what the returned data represents and how it can be used downstream, which exceeds what the empty schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: 'Get Depop's category taxonomy.' It precisely defines what is returned (full department, category, and subcategory taxonomy) and explicitly ties it to the filters of /depop/search and /depop/shop/{username}, making it easy to distinguish from sibling tools like depop_sizes and depop_brands.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly conveys the integration purpose: the returned values are 'every value usable with' the category/subcategory filters on /depop/search and /depop/shop/{username}. It implies when to use the tool, though it does not explicitly list exclusions or alternative sibling tools beyond that context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry behavioral disclosure on its own. It does this well by noting it comes from DraftKings' credential-free public JSON, implying an unauthenticated read operation with no credentials required. It also tells agents what to expect in the response (metadata only, no odds). It stops short of mentioning rate limits, errors, or other runtime caveats, but for a simple read call the disclosed traits are sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four sentences, each earning its place: the standalone story, the return payload, the parameter sourcing, and the odds exclusion. There is no wasted text, and the structure front-loads the core purpose before reaching the caveat.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no output schema, this description covers virtually everything an agent could need: parameter provenance, the expected return payload, the credential profile, and a clear endpoint boundary. It even enables chaining by noting which downstream endpoint accepts the league_id. No critical gap remains.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema confirms 100% parameter coverage (event_id as a 'Numeric DraftKings event id'). The description adds meaning beyond that label: it tells the agent how to find the event_id, that it can come from an event's odds response, and how the returned league_id can be reused with other endpoints. This is clear added value rather than a repeat of the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Returns one event's metadata' and explicitly lists the fields (league id, sport id, teams, status, start time), so the verb, resource, and scope are crystal clear. It also sets boundaries against odds-focused siblings by explicitly stating this endpoint does not include betting markets/odds, making it easy to differentiate from draftkings_odds, draftkings_event_markets, and similar tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides strong context: it tells where to obtain event_id (from a DraftKings Sportsbook page or the odds response) and explains that the returned league_id can be used with /draftkings/sportsbook/odds and /draftkings/sportsbook/futures. The ending note ('does not include betting markets/odds') implies a when-not-to-use condition, but it does not explicitly say 'use another endpoint when you need odds' or name the exact alternative tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description shoulders the transparency burden. It discloses that the data comes from a credential-free public JSON source and that an empty markets list is valid, which are meaningful behavioral details. It stops short of describing error cases or rate limits, but the core behavior is transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is tightly structured: summary, parameter sourcing, then valid edge case. Backticked field names improve scannability, and every sentence earns its place. No redundant filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description names the returned concepts (markets and selections) and explicitly covers the empty-markets valid response. It is slightly short on the internal shape of market/selection objects, but for selection and invocation it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Though schema coverage is 100%, the description adds real discovery value: how to locate event_id via the id field of an odds result and subcategory_id via subcategory_id on a market, plus examples of category types. An agent can correctly resolve both parameters from this guidance alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: it returns one event's betting markets and selections for a specific market category. This exactly distinguishes it from sibling tools like draftkings_odds, draftkings_event, and draftkings_futures.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly indicates when this tool is useful: with an event_id and subcategory_id, obtainable from /draftkings/sportsbook/odds or event network traffic. It does not explicitly name alternatives or exclusions, but the context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It is honest about scope ('public', 'currently marked as featured') and clearly implies a read-only listing by 'Returns ... leagues.' It also describes output content at the item level. It could more explicitly state that the call is a zero-parameter read operation and how the list is ordered/paginated, but for this simple endpoint the disclosure is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three compact sentences with no filler. The first sentence serves as an immediate identifier, the second specifies the return content and scope, and the third gives concrete downstream usage. Every sentence adds practical value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameter-free listing tool with no output schema, the description equips an agent to call it correctly, understand each item's fields, and know how to wire the `id` into downstream endpoints. The missing bits, such as explicit list-format details, are minors in a tool this simple. It is complete enough for reliable invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters and 100% schema description coverage of meaningful property documentation. Because there are no parameters to explain, the description does not need to compensate for anything. The baseline for a zero-parameter tool is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Returns') and names an exact, narrow resource: 'public DraftKings Sportsbook leagues currently marked as featured in its sport navigation.' It enumerates what each item contains (id, tags, live-offer status, featured ordering), which clearly distinguishes it from a general league-list tool like draftkings_leagues.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives actionable downstream guidance: 'Use the `id` as `league_id` with /draftkings/sportsbook/odds and /draftkings/sportsbook/futures.' It clearly conveys the intended role of this tool in a multi-step workflow. It does not explicitly name when to prefer draftkings_leagues over this tool, so it stops just short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It clearly discloses two major limitations: no destination URL due to ad-click-tracking redirects, and only the first page is supported due to opaque pagination tokens. It also reveals the ad-funded nature of the results. This is exceptional transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long, front-loaded with the core purpose, and every sentence adds value: purpose, return fields, and critical limitations. There is no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description fully explains what is returned (title, brand, merchant, description, price, rating, review count, total page count) and any caveats (no URL, first page only). This is complete for a search tool with no schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides clear descriptions for both parameters ('Search query' and 'DuckDuckGo market code, e.g. us-en, uk-en') with 100% coverage. The description does not add any additional parameter semantics, so it remains at the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Search DuckDuckGo shopping results,' which is a clear verb+resource statement. It distinguishes this tool from sibling search tools (duckduckgo_search, duckduckgo_image, etc.) by explicitly naming the shopping vertical and listing the normalized fields returned.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use this tool: when shopping results are needed. It also implicitly differentiates from organic search by stating that the shopping vertical is 'ad-funded, syndicated product listings, not organic content.' However, it does not explicitly name an alternative tool for organic results or state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that data comes from ESPN's credential-free public JSON, implying a read-only, publicly accessible operation. It does not mention rate limits, authentication, or side effects, but for a simple data retrieval tool, this level of disclosure is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: three sentences. First sentence states purpose, second lists sport options, third lists league options. No unnecessary words. Information is front-loaded and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (returns a list) and no output schema, the description is fairly complete. However, it does not describe the output format or fields (e.g., team IDs, names). While the tool is straightforward, describing the output would enhance completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides only vague parameter descriptions ('Sport key', 'League key'). The description adds significant value by explicitly listing all valid enum values for both sport and league, and indicating the league must be valid for the chosen sport. This is crucial for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it returns the full team list for a sport and league from ESPN's public JSON. It specifies the verb (returns), resource (team list), and scope (full list for given sport/league), distinguishing it from sibling tools like espn_team (single team) and espn_team_roster (roster).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description makes it clear when to use this tool: to get a full team list for a specified sport and league. It does not explicitly state when not to use it or mention alternative tools, but the context (sibling tools) implies that for individual team details, other tools exist. This is a minor gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure and does so thoroughly. It reveals the source of imagery, entry contents (URL plus pixel dimensions), how to resize via URL suffix, exclusions, lack of pagination, and the 1 request/second rate limit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact yet information-dense: every sentence adds value, from purpose to file format details, exclusions, pagination status, and rate limiting. The main clause appears first, giving immediate clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking annotations and an output schema, the description provides enough context for an agent to invoke the tool correctly: required place_id, optional limit semantics, return entry contents, URL transformation behavior, exclusions, and rate limit. This is a complete picture for a 2-parameter read tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents both parameters with 100% coverage, so the baseline applies. The description reinforces that place_id identifies the place and mentions output URL sizing, but it does not add materially new meaning to the parameters themselves.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Returns the photos Google publishes for a specified place_id' and clearly scopes it to the place page's image set. It differentiates from sibling tools by explicitly excluding contributor avatars and review-attached photos, and from archive-type feeds by noting it is 'not a paginated archive feed.'
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes the intended use clear: retrieve place photos for a Google Maps place_id. It also gives context around what is excluded and the one-request-per-second rate limit. However, it does not explicitly name alternative sibling tools or state 'use X instead when...', so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral disclosure. It reveals the typical 8 most relevant reviews, the empty text for photo-only reviews, the first-page limit, and the 1 request per second rate limit, all of which go beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four sentences and front-loaded with the core purpose. Each subsequent sentence adds useful detail—returned fields, an edge case, scope limitation, and rate limit—without unnecessary fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Even without an output schema, the description enumerates the expected review fields and key edge cases (photo-only reviews, first-page scope, rate limit). This is sufficiently complete for a straightforward read-only list tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% coverage for both parameters (place_id and limit). The description adds minimal extra meaning beyond reiterating the place_id's role, so it meets the baseline but does not significantly improve parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns Google Maps reviews for a specified place_id, enumerates the fields (rating, text, reviewer, timestamp, photos), and distinguishes itself by noting it returns only the first page of reviews, not the full archive. This separates it from sibling tools like google_map_place and google_map_place_photos.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides a clear scope boundary (first page of reviews, not full archive) and a rate limit, which implies when it is appropriate to use. However, it does not explicitly name alternative tools or state when not to use this tool, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It discloses the data source (Google Patents server-rendered pages), states the data is public, and clarifies the output is a normalized single-patent object. It stops short of describing failure behavior or rate limits, but for a straightforward read-only detail lookup, the behavioral context is solid.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the resource and main action, then lists returns, then finishes with the alternative tool reference. Every sentence adds distinct value, and the enumeration of fields is purposeful rather than filler, especially given the lack of an output schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Since there is no output schema, the description adequately enumerates the returned fields, including title, inventors, assignees, dates, legal status, classifications, claims, citations, family, and similar documents. It also covers input expectations with number format examples and points to the correct search tool for different use cases, making it complete for an agent to invoke.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds a small amount beyond the schema by giving non-US publication number examples (EP/WO) and clarifying that `number` is a publication number, but this does not materially expand the schema's existing meaning, especially since the schema already provides the same primary example.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs and a clear resource: it returns a single patent's normalized detail, enumerating fields like title, claims, citations, and family. It also explicitly distinguishes itself from googlepatents_search by stating search is for keyword/inventor/assignee queries rather than a known publication number.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly tells the agent when to use this tool (with a known publication number) and names the alternative: 'To search or browse by keyword, inventor, or assignee instead of a known publication number, use /googlepatents/search.' This provides clear routing without leaving inference to the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description fully carries the burden. It discloses the partial-fetch behavior (missing sections reported in `missing_sections` with `partial=true`), the error condition when no section can be fetched, and the caveat that this is not viewing advice. This goes well beyond basic read/write expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four sentences long, front-loaded with the purpose, then adding behavioral details. Each sentence provides distinct information without filler. The phrase 'This endpoint is not viewing advice' is compact but somewhat cryptic, slightly reducing clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (six independent sources, partial-failure handling) and no output schema, the description explains return semantics, missing_sections, the partial flag, and error behavior. It names the six sections but does not elaborate on what 'summary metrics' specifically contain, leaving some ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema descriptions cover both parameters (id and url). The description adds a critical constraint absent from the schema: 'Pass exactly one of `id` or `url`.' This clarifies they are alternative identifiers, adding meaning beyond the bare schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'derived public-page summary metrics' for six named IMDb sections (trivia, goofs, quotes, keywords, filming locations, company credits). This specific verb+resource+scope distinguishes it from sibling per-section tools like imdb_title_trivia or imdb_title_goofs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context: pass exactly one of `id` or `url`, and check `partial` for complete analysis. It warns 'This endpoint is not viewing advice', which is an exclusion. However, it does not explicitly name alternative tools or compare when to use this aggregate vs the individual IMDb section tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the endpoint is credential-free and GraphQL-only, and that there is no page-based fallback. This is valuable behavioral context. It does not mention rate limits or response format, but for a simple autocomplete endpoint, the provided details are sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences and highly efficient. The first sentence provides a succinct title-like summary, and the second delivers the operational detail. Every word earns its place, and the most important action is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking annotations and an output schema, the description is remarkably complete for a simple suggestion tool. It covers what the tool returns, why to use it, and a critical caveat (no fallback). Both parameters are documented in the schema, and the description provides the integration context. The agent can confidently invoke this tool and use the results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (both q and limit are described). The description adds meaning beyond the schema by explaining that `q` is a partial location string used to generate suggestions that feed into the `l` parameter for search. This contextualizes the parameter's role, going beyond the bare schema description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Returns Indeed's own location-search autocomplete suggestions') and the resource (partial location string), with a clear purpose ('for building a valid `l` value for search'). It distinguishes itself from siblings by focusing on location suggestions for Indeed, and mentions the unique GraphQL-only nature.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: use this tool when you need location suggestions to construct a valid `l` value for Indeed search. It also notes there is no page-based fallback, implying when to rely on it exclusively. However, it does not explicitly name alternative tools or state when not to use it, so it lacks the explicit exclusions for a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description notes that the tool is 'credential-free', indicating no authentication is needed. It does not disclose rate limits or other constraints, but for a read-only public API, it is sufficiently transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose. Every sentence provides essential information without redundancy. It is efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with no output schema, the description adequately conveys what is returned (full description with fields), how to get the id (from a board listing), and that it is credential-free. No critical information is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage for all three parameters. The description adds context by linking id to a board listing and host/site to the board endpoint, reinforcing the schema descriptions and adding value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a single Oracle Recruiting requisition and specifies the returned content (full HTML/text description with description, responsibilities, qualifications). It distinguishes from sibling tools like jobs_oracle_board by focusing on a single item.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains that the id comes from a board listing and host/site are as in the board endpoint, providing context for use. However, it does not explicitly mention when not to use this tool or name alternatives, though the sibling list includes many job tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the transparency burden and does well by disclosing the operation is public, credential-free, and returns JSON. It also describes the inline detail fields, giving a clear picture of what the agent will receive. It does not discuss rate limits or failure modes, but for a simple read-only public API, this is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no fluff. The first states the action, the second explains the parameter and adds the credential-free/public JSON note. Every word earns its place, and the structure is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter, read-only tool with no output schema, the description is complete. It explains what the tool lists, what fields are included, how to identify the tenant, and the auth requirements. No gaps are apparent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes 'company' as 'Pinpoint tenant subdomain (careers URL),' and the description adds the exact URL template https://{company}.pinpointhq.com/, which clarifies how to construct the parameter. This goes beyond the schema's baseline and helps an agent correctly invoke the tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'List a tenant's Pinpoint job board,' a specific verb+resource that immediately identifies the tool's function. It further distinguishes from sibling tools by explicitly naming 'Pinpoint' (pinpointhq.com) and detailing the returned data (full HTML description, responsibilities, skills, benefits, compensation).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context by stating the tool accesses 'public' and 'credential-free' postings, and it explains how to derive the 'company' parameter from the careers URL format. However, it does not explicitly mention alternative tools or exclusions, so it lacks the 'when-not-to-use' guidance that would earn a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, and it does this well: it says the response only includes page 1, enumerates the normalized product fields, and precisely explains the difference between a 404 for an unknown category and a 404 for a zero-result response. It could add rate-limit or authentication notes, but the core behavior is fully predictable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with a clear, concise first sentence. The remaining sentences are dense but purposeful — encoding rules, facet follow-up usage, and error semantics are all in. There is minor redundancy in repeating 'Kohl's category or curated campaign page,' but every sentence yields real working knowledge an agent needs.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter category browser with no output schema, the description covers the full call surface: purpose, return fields, category-string syntax, percent-encoding, follow-up discovery via facets, and error/corner-case semantics. An agent has enough to invoke it correctly and to decide whether results are useful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description for 'category' is present but minimal (100% coverage), while the tool description adds substantial meaning: concrete examples like 'Room:Dorm' and 'Department:Kitchen & Dining', the '+ / %2B' encoding rule, how to combine multiple dimensions, and the fact that facet values can be used directly as follow-up categories. This goes far beyond the redundant schema text.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb-resource pair: 'Browse a Kohl's category or curated campaign page.' It then defines the concrete return value: a page-1 product grid with normalized product data and facets for further navigation. This makes it clearly distinct from sibling tools like kohls_product_reviews, kohls_stores, and kohls_suggest, even without naming them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives strong context for when to use this tool: to browse Kohl's category or campaign pages and to discover the taxonomy via returned facet values. It also provides practical guidance such as following facets from a known category and handling 404 vs. zero-result responses. However, it never explicitly names sibling tools or states when not to use it, stopping just short of clear exclusion guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that results follow the upstream's own relevance order, that an empty list is a normal outcome for obscure input, and that the data is credential-free from an anonymous, login-free session. This goes well beyond a basic function statement and addresses auth and expected-result behaviors.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four concise sentences, each providing distinct value: purpose, ordering behavior, empty-result normalcy, and data source/credentials. No redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter autocomplete tool with no output schema or annotations, the description covers purpose, behavior, edge cases, and access requirements. It is complete for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'query' is fully described in the schema as 'Partial keyword to get suggestions for'. The description reiterates 'partial keyword' but does not add significant detail beyond the schema, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Mercari search autocomplete' and clearly states it returns Mercari's own search-suggestion list for a partial keyword in the upstream's relevance order. This specific verb-resource pair ('returns... list') distinguishes it from sibling tools like mercari_search or mercari_item.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies usage for autocomplete/suggestion scenarios via 'partial keyword' and explicitly notes empty lists are a normal outcome, setting expectations. However, it does not name alternative tools or explicitly state when not to use it, so it provides clear context but no exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations available, the description carries the transparency burden. It proactively discloses that the data is public, that it returns only top-level categories, and that category ids feed into the ideas endpoint. It does not cover all potential behavioral traits (e.g., caching, ordering, exhaustive coverage), but for a simple categorical list, it is reasonably transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences with no wasted words. It front-loads the action, provides confirming examples, and adds a useful pointer to the related endpoint. Every sentence contributes value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless tool with no output schema, the description fully covers the essentials: what is returned, example categories, how ids are used downstream, and the data source. It is sufficient for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the schema is empty, so there is no parameter semantics to explain. Following the baseline for 0-param tools, the description does not need to provide parameter-level detail; it focuses instead on the output, which is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'Get Pinterest's 'Ideas' category list' and describes the return value as a top-level taxonomy with concrete examples. It distinguishes itself from sibling tools like pinterest_idea by focusing on the category list itself, and even shows how the returned ids relate to the idea-fetching endpoint.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It implies usage by stating that each entry's id is usable with GET /pinterest/ideas/{id}, effectively directing users to the corresponding idea endpoint. However, it does not explicitly name a sibling tool or give clear 'when not to use' exclusions, leaving some guidance implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It clearly discloses that numeric figures are gated behind a paid subscription and appear as empty cells, and that the returned content is a teaser. This provides essential behavioral context beyond schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, well-structured, and front-loaded with the core purpose. Each sentence adds value, and there is no redundancy. It efficiently conveys purpose, limitations, and parameter usage in a few lines.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description thoroughly explains what data is returned (overview, description, contact, funding-round history without dollar amounts, preview of investors, etc.) and what is missing (gated figures). This is sufficient for an agent to understand the tool's output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema describes each parameter individually with 100% coverage, but the description adds the crucial constraint of mutual exclusivity ('Pass exactly one of `id` or `url`'), which is not in the schema. This addition helps the agent avoid invalid parameter combinations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns the free/teaser content of a PitchBook company profile page and lists specific sections (overview, description, contact, funding-round history without dollar amounts, etc.). It differentiates from sibling tools like pitchbook_fund and pitchbook_investor by focusing on company profiles.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states to pass exactly one of `id` or `url`, offering clear parameter usage. It explains the free vs. gated data, setting expectations for when this tool is appropriate. However, it does not directly compare to sibling tools or provide when-not-to-use scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden. It transparently states the tool is "Credential-free public data" and identifies the source as Poshmark's server-rendered brand directory page. It also explains the scope (full directory vs. active listings) and the return fields (name, slug, logo, aliases), which provides meaningful behavioral context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences that are each purposeful and front-loaded with the primary action. It efficiently covers what, why, and data source without redundancy or unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, read-only directory tool with no output schema, the description is sufficiently complete. It explains the data scope, the target use case, the source, and the fields returned, giving an agent everything needed to decide to call it and interpret the result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description appropriately focuses on what is returned rather than parameter usage, and no additional parameter semantics are needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action and resource: "Get the full Poshmark brand directory." It further distinguishes itself from brand-resolution or search-filter tools by noting it returns "every brand Poshmark recognizes," not just those with active listings, and explicitly lists the fields returned.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool: "Useful for resolving a brand name to the exact value the brand/search filters expect." It does not explicitly name alternative tools or state when-not-to-use, but the guidance is sufficient for an agent to select it appropriately among the Poshmark family.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It explicitly states that data is 'credential-free public data', describes the exact return payload (normalized listing summaries with fields, total count, opaque pagination cursor), explains how pagination works, and names the data sources (server-rendered page and JSON API). This is comprehensive transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long, front-loaded with the core action, and every sentence adds value: scope, return payload, pagination, and data source. No redundancy or filler, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description effectively explains the return values (normalized fields, total count, cursor). It also covers pagination, optional department filtering (implied via schema), and the public/credential-free nature. This is complete for a search tool with a moderate parameter set.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with each parameter having its own description. The description adds pagination context ('Pass a previous response's next_max_id back as max_id') but this largely mirrors the schema's max_id description ('Opaque pagination cursor from a previous response's next_max_id'). No significant new parameter-level meaning is added beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with the specific verb 'Search' and identifies the resource as 'Poshmark listings', thus clearly stating its function. It further specifies the scope ('clothing, shoes, and accessory listings'), which distinguishes it from sibling tools like poshmark_listing (likely single listing) and other marketplace search tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly establishes that this tool is for searching Poshmark listings and explains the pagination flow. It gives context on what the tool is used for but does not explicitly mention alternatives or when not to use it, so it misses the 'exclusions' part of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that the tool accesses a 'credential-free public episode page', implying no authentication needed. Lists the types of data returned. No annotations provided, so description carries burden; it covers read-only behavior but omits details like rate limits or error scenarios.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: first describes the tool's output, second provides parameter guidance. No fluff, front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequately covers purpose, output, and parameter usage. Lacks specifics on path format (e.g., relative vs absolute) and prerequisites, but overall sufficient for a simple two-parameter tool with high schema coverage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Adds significant value beyond the input schema by specifying the 'exactly one' constraint and the absolute URL format. Schema coverage is 100%, but the description clarifies usage condition that the schema alone does not enforce.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool returns 'Rotten Tomatoes TV episode metadata, scorecard data, parent series/season metadata, and public video metadata'. Distinguishes from sibling tools like rottentomatoes_season and rottentomatoes_series by focusing on the episode level.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit instruction to pass exactly one of `path` or `url`, and specifies the URL must be absolute from rottentomatoes.com. However, does not explicitly mention when to use this tool versus siblings (e.g., rottentomatoes_season for season-level data).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries burden. Describes data sources (public Person JSON-LD, credential-free filmography module) and normalization. Could mention caching or real-time nature, but overall good transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded key action and output, no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but describes return types (metadata and filmography rows) and sources. Could mention error handling or rate limits, but sufficient for most agents.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds critical constraint 'Pass exactly one of path or url' that is not in schema (both optional, no required). This clarifies mutual exclusivity, adding significant value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns person detail and filmography, distinguishing it from sibling tools like rottentomatoes_movie or rottentomatoes_tv. Specific outputs (normalized metadata and filmography rows) are named.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs to pass exactly one of `path` or `url`. However, it does not explicitly state when to choose this tool over siblings, though the name and context imply it is for person queries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description covers key behavioral aspects: it uses Steam's keyless IStoreQueryService (credential-free), lists the response fields, explains slug case-insensitivity, and mentions default relevance ordering. It could be more explicit about pagination behavior, but overall provides significant transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is 4 sentences, front-loaded with the main action, and each sentence adds unique value. It is fairly concise, though could be slightly more compact without losing information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema is provided, so the description compensates by describing the return fields (WEIGHTED community tags, review-score, developer/publisher, etc.). It mentions pagination implicitly ('catalog slice') and ordering. For an 8-parameter tool, this is reasonably complete, though error conditions and response format are omitted.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers all parameters with descriptions (100% coverage). The description adds value beyond the schema by explaining the slug parameter in detail (numeric id or name, case- and separator-insensitive, id resolution). This exceeds the baseline of 3 for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Browse a store category (tag) with weighted community tags.' It specifies that it returns a catalog slice with detailed fields, and distinguishes itself from sibling tools like steam_tags by noting that for sorted or faceted browsing one should use /steam/tags.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use this tool vs alternatives: 'for sorted or os/price-faceted browse use /steam/tags' and 'resolve ids via /steam/tags/list.' It also notes that it is credential-free, helping agents decide on authorization needs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that results are app IDs only (not name-enriched), that lists are large, and that it is credential-free and public. No annotations provided, so description carries the burden well. Could mention pagination or if it returns all months at once but it's adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences that efficiently cover purpose, output details, caveats, and authentication. No unnecessary text, well-structured and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no parameters and no output schema, the description explains the return format, notes the need for name resolution, and confirms public access. Fully adequate for an agent to understand usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist in the schema, baseline is 4. Description adds no parameter semantics since none are needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it retrieves Steam's monthly best-new-releases index. Differentiates from sibling chart tools like steam_charts_most_played or steam_charts_concurrent by specifying it returns monthly top-releases with app IDs, month labels, and start dates.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implicitly advises when to use by describing the output (app IDs only) and suggests resolving names via /steam/items. Lacks explicit comparison with similar Steam chart tools but provides enough context for appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It adds valuable context about credential-free public data and the source API being the same one backing StockX's site menu, which communicates read-only access and data provenance. It doesn't mention pagination or rate limits, but for a zero-parameter catalog fetch this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with a clear front-loaded opening and no filler. Every sentence contributes useful information: what is returned, what fields are included, how it should be used, and its public/credential-free nature.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity, empty input schema, and absence of an output schema, the description sufficiently explains the return contents (name and URL slug for every brand) and the practical integration with search parameters. Nothing essential is missing for an agent to select and invoke this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description appropriately focuses on output and usage rather than parameter semantics, which are unnecessary here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the verb ('Get'), the resource ('StockX brand catalog'), and the exact scope ('full brand catalog name and URL slug for every brand'). It differentiates from siblings by explicitly targeting the brand domain and connecting it to the search tool's brand/model parameters.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives an explicit use context: building the brand parameter for GET /stockx/search or providing the single-brand context for the model parameter. It does not name alternatives or state when not to use it, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states 'Public data, sourced from Strava's own challenge gallery,' which conveys a read-only, no-auth operation. It does not address rate limits or errors, but for a simple read endpoint this is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences with no redundancy. The description is front-loaded with the core purpose, then specifies the return structure, then adds source provenance. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no parameters, no output schema, and no annotations, the description thoroughly covers what is returned (promoted challenge, sections, goal/duration/cover art) and data provenance. No significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters (empty schema, 100% coverage), so the description has no parameter semantics to explain. Per the rubric, 0 params = baseline 4. The description appropriately focuses on return content instead.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Returns') and resource ('Strava's public challenge gallery'), and clearly enumerates the content: the promoted challenge, gallery sections per sport, and each challenge's goal, duration, and cover art. This distinguishes it from sibling tools like strava_routes or strava_club.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context by explicitly stating what the tool returns and that it is public data. However, it does not name alternatives or explicitly state when not to use other Strava tools, missing the 'explicit alternatives' bar for a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses key traits: returns a snapshot rather than full feed, empty list for stores without reviews, and credential-free public data. This goes beyond minimal requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, each adding distinct value: purpose, return contents, limitation, edge case, and auth status. No redundant text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description fully explains return values (rating, count, sample reviews including fields) and handles edge cases. For a single-parameter tool, this is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a descriptive store_id field that explains source and format. Description adds no additional parameter detail, but none is needed given the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
States 'Get UberEats store reviews' with specific contents (aggregate rating, review count, sample of recent reviews with reviewer name/text/date). Clearly distinguishable from sibling tools like ubereats_store and ubereats_feed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides context on scope (single on-page snapshot, not a full paginated feed), implying when not to use it, and notes credential-free access. Doesn't explicitly name alternative tools but the limitation is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears the full behavioral burden, and it discloses the important traits: only one page is returned, questions are normalized, and products with zero questions or well-formed but unrecognized IDs return a normal empty result rather than an error. It is informative about the correctness, but does not cover the output shape or whether any rate-limit/auth constraints exist, keeping it a step below the top.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The three sentences are front-loaded with the purpose, then cover return shape and the critical edge cases, with zero redundancy. Each sentence earns its place and nothing is buried under preamble language.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity — two parameters, one required, no output schema — the description is fully sufficient: what it returns, where the key parameter comes from, the pagination behavior, and the empty-result edge case. An agent can pick and correctly invoke this tool without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% so the baseline is 3, and the description adds genuine value on top of what the schema says about product_id: that the ID can be harvested from a search result's product_id field or a product page URL, and that a well-formed but unknown ID triggers empty behavior. The page parameter's semantics (1-based, default 1) are already fully captured in the schema, so the description doesn't need to repeat it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description names the exact action and resource: it gets an Ulta Beauty product's customer questions, 'each with every answer it received.' It goes beyond a bare label by specifying the output shape ('one page... normalized') and implicitly differentiates the tool from siblings because nothing else in the ulta_/product space handles questions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives actionable guidance for how to use the tool: product_id should come from a search result's product_id field or the product page URL, which tells an agent exactly where to source the required argument. It also clarifies that an unrecognized ID yields an empty result, not an error, so an agent knows how to interpret outcomes. It does not explicitly call out alternatives like ulta_product_reviews or sephora_product_questions, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so full burden on description. It explains data source (proxied browser renderers), credential-free nature, and edge cases (empty reviews return zero counts).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, front-loaded with main action, no redundant information, every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description fully explains output contents (average rating, breakdowns, sample reviews) and edge cases. Covers all needed context for this simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameter with clear description. Description adds no extra meaning beyond schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and specific resource 'Walmart product reviews', listing exact data returned (average rating, breakdown, etc.) and distinguishing from a full paginated feed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states this is a single on-page snapshot, not a full feed, and describes behavior for no reviews. However, it lacks explicit comparison to sibling tools like walmart_product that might also contain review data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden. It discloses pagination behavior, output normalization, the returned fields, and that only the trailing category id from a URL is used. This gives the agent a realistic expectation of how input is normalized and what the response contains.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences cover what the tool does, its input flexibility, output shape, and pagination model. Every sentence is functional and there is no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter read tool with no output schema, the description supplies the essential return values, all input formats, and pagination context. An agent has enough information to decide when to call the tool and how to construct a request.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents both parameters at 100% coverage, but the description adds meaningful nuance: accepted forms for category (bare id, 'c'-prefixed id, slug, URL), the trailing-id rule, and the confirmation of real page-based pagination for the page parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a precise verb-resource pairing: 'Browse a Wayfair category' and 'Returns a Wayfair category page's product grid.' It clearly differentiates from siblings like wayfair_categories and wayfair_product by describing the product-grid scope, the accepted category inputs, and pagination.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes usage obvious: provide a Wayfair category in any of several acceptable forms and receive a paginated product grid. It does not explicitly name alternatives or exclusions, but the context is clear enough for an agent to select this tool versus category-listing or product-detail tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It discloses that results are directional and not exhaustive, explains the render strategies and their implications, and describes the output fields. It lacks mention of potential errors or rate limits, but covers key behavioral aspects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with purpose and then provides extensive lists of covered technologies. While verbose, every sentence adds value and it is well-structured. A slight trim could improve conciseness, but it remains clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (no output schema, nested objects), the description comprehensively covers inputs, outputs, and behavior. It describes the output structure (technologies with categories, confidence, version, evidence) and explains the fetch strategies. No critical gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% but the description adds substantial meaning beyond the schema. It explains the `render` field's three options (browser, auto, http) with details on when each is appropriate, and clarifies the default. The description transforms a simple parameter into a well-understood choice.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: detect what a website is built with, like BuiltWith/Wappalyzer. It specifies the verb 'detect' and resource 'website tech stack', and distinguishes from any sibling tools (none are similar). The long list of covered technologies reinforces its scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says only public pages are supported and to respect terms and robots directives. It explains the render strategy options and defaults, but doesn't contrast with alternatives (no direct sibling). The guidance is clear for correct use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the data is public and sourced from Whatnot's own GraphQL API, and clarifies that it returns only top-level categories. It does not describe the response format or potential pagination, but for a simple list tool this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise, front-loaded sentences: the first states the action, the second provides examples and scope, and the third ties to a sibling tool and data source. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema, the description fully covers what it returns (full category list), gives examples, specifies how to use the data with /whatnot/browse, and notes the data provenance. This is sufficient for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description correctly adds no parameter-specific details since none exist, and the schema already provides complete coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action: 'Get Whatnot's category list.' It further specifies it returns the 'full top-level category list' with examples like 'Trading Card Games' and 'Sneakers & Streetwear', distinguishing it from sibling tools like whatnot_browse and whatnot_live.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly states that each entry's slug is usable with /whatnot/browse's category filter, giving a clear integration point and when to use this tool. However, it does not mention alternative tools or when not to use it, so it lacks exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden and handles it well: it states that the tool takes no input, returns a static site-wide taxonomy, and does not vary by search term or category. It could go further by explicitly confirming no side effects, but the read-only nature is strongly implied by 'Get' and 'Returns.'
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three efficient sentences. The key information is front-loaded, and the negative constraints (no input, static, non-varying) are explained without unnecessary detail. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, parameterless tool, the description is complete: it defines what is returned, gives examples of the tree structure, notes nested filter groups, and clarifies the static site-wide nature. Without an output schema, this is sufficient for an agent to select and invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, and the schema already reflects this with required: []. The description reinforces it by stating it 'takes no input,' which is sufficient. No additional parameter-level documentation is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Get Wish's category and filter navigation tree.' Concrete examples of categories ('Popular', 'Deals Hub', 'Fashion', 'Gadgets') and filter groups ('Color', 'Rating') make the purpose unmistakable, and the Wish-scoped wording distinguishes it from other taxonomy tools in a large sibling list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly frames when this tool is appropriate: it is a 'static, site-wide taxonomy' whose result 'does not vary by search term or category.' This implies the agent should use it for global navigation rather than context-specific queries, though it does not explicitly name sibling alternatives to exclude.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the explanatory burden. It discloses that the tool fetches a single article, not a list, and discloses the content shape by enumerating headline, body, author, publish time, keywords, etc. It doesn't cover edge-case errors or rate limits, but for a simple read-only article retrieval, this is solid transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded. The first sentence identifies the domain and primary capability; the second adds a focused field inventory and input guidance. No wasted or redundant phrasing, and it reads quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter retrieval tool, this is complete. There is no output schema, so the description adequately substitutes by enumerating the returned article components. It also explains the URL source pattern, making it easy for an agent to know how to obtain an appropriate canonical URL before invoking.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents the URL parameter. The description adds useful nuance by emphasizing a canonical yahoo.com/news URL and by explaining where such URLs can be obtained, which helps the agent construct a valid argument.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a clear noun phrase and then a specific verb-resource statement: 'Returns a single Yahoo News article's full content.' It enumerates the exact fields returned, making it unmistakable what this tool does and distinguishing it from the related category/home/search siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly sets the expected input condition: a canonical yahoo.com/news article URL, and brings in context by noting that such URLs are typically returned by the home or category story streams. It doesn't explicitly name alternatives to avoid, but the stream-coupling is an effective use cue for the intended call pattern.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It clearly explains the location-resolution behavior, the source (Yahoo's server-rendered local-search page), and the return payload fields. It doesn't note auth requirements, pagination, or rate limits, which are common gaps, so it loses a point.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized for a single-parameter tool and front-loads the core result ('Yahoo local business results') before explaining source and the return fields. Every sentence contributes meaningful information and no redundant restating of the name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter search tool, the description fully explains how to construct the query, what to expect back, and where the data comes from. There is no output schema but the return fields are enumerated in the text. Nothing essential is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers the single parameter q with its description, and the tool description reinforces that q must include location intent. With 100% schema coverage and one parameter, the description adds meaningful usage context but doesn't need to add more. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the search verb and resource explicitly, and distinguishes this tool from the sibling yahoo_search (its generic counterpart) by specifying local-business-search results and the specific return fields (name, category, price range, address, phone, open status, rating, review count). The scope is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says location is resolved from the query text itself, with an example, rather than a coordinate parameter, and clarifies that queries should be formed like a user typing into Yahoo's local search box. This differentiates it from coordinate-based or separately-parameterized local search tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral disclosure burden, and it meets it well. It reveals that results come from Yahoo's server-rendered news-search page rather than the portal, and it discloses the important click-tracking redirect behavior, including that URLs are decoded. These are exactly the kinds of hidden behaviors an agent would not know without this description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is economical: four sentences, each adding a distinct piece of information. The purpose is front-loaded, the return fields support it, and the disambiguation and redirect behavior are kept at the end without flooding the main intent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter search tool with no output schema, the description is complete. It tells the agent everything it needs to invoke the tool, states what the result items contain, and explains the URL transformation behavior. No pagination or rate-limit details are essential for a basic query tool, and no critical behavior is omitted.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of the single parameter, q, as a search query. The description adds little beyond that, only restating the notion of a query. Since the schema already fully documents the one parameter, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Search Yahoo news results.' It then enumerates the exact return fields, making the tool's function unambiguous. It also explicitly distinguishes itself from the yahoo-news family, so an agent can separate this tool from related siblings without needing to infer.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly identifies the intended context: searching Yahoo's news-search product rather than the Yahoo News portal. It names the yahoo-news family as a distinct product, giving the agent a meaningful comparison point. It stops short of explicitly stating all conditions and when-not-to-use cases, so a small gap remains.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral disclosure burden. It states the data is pulled from Yahoo's public tournament-leaderboard JSON API, that a single golf tournament's results are returned, and it spells out the complete 'fixed stat set.' This makes the read-only, external nature of the call clear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, no filler. The first sentence names the tool's purpose, the second lists the full return contract, and the third explains where to source the required parameter. Every sentence contributes indispensable information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description fully compensates: it lists the returned fields, the upstream dependency for the id, and the external source API. The season parameter's semantics are already in the schema, so nothing necessary for a correct invocation is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents both parameters with 100% coverage, so the baseline is 3. The description adds extra meaning by giving a concrete example of the tournament id (`golf.e.23`) and explaining that the id originates from the golf-schedule endpoint, which helps the agent construct valid calls.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Returns one golf tournament's full leaderboard' and enumerates exactly what data is included (rank, to-par, status, etc.). This clearly distinguishes the tool from schedule or scoreboard siblings, and the concrete field list removes ambiguity about its scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a direct chaining instruction: 'Get the tournament id from a golf-schedule response's id field.' This tells the agent where the required parameter comes from and how to proceed. It doesn't name the sibling tool or state any exclusions, but the guidance is already actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden, and it does so well. It discloses that calls take no parameters, that the endpoint is non-configurable and always returns the currently featured event, that the data comes from Yahoo Sports' server-rendered MMA schedule page, and that it returns typical UFC fight-card data. This is good coverage of behavior without any structured annotation to lean on.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences with zero waste. The opening sentence establishes the tool and its payload, the second identifies the data source, and the third concludes with the critical constraint. The behavioral limitation is placed at the end for natural reading flow, and every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, the absence of an output schema, and a zero-parameter surface, the description is complete: it specifies the resource, the payload fields, the data source, and the single caveat of caller flexibility. There is nothing an agent needs to know about the endpoint that is missing from the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With zero parameters, the baseline is 4. The description goes further and explains why there are no parameters — the endpoint intentionally always returns the current/next event, so callers do not need to pass or select an event ID. This adds meaning beyond the empty schema, which simply defines no properties.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description begins with a direct, specific statement: 'Returns the current/next UFC event's full fight card', and then enumerates the exact fields included (fighters, records, rankings, weight class, card position). It distinguishes the resource from a schedule tool by clearly stating this is about a fight card, and the final sentence clarifies it is event-fixed rather than caller-selected, sets it apart from any event-selection sibling.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly states the context of when this endpoint should be used: when the current/next featured UFC event's card is needed. The closing sentence 'whichever event Yahoo currently features as next, not a caller-selected one' effectively excludes use cases requiring a specific user-chosen event, though it does not explicitly name an alternative sibling tool to switch to for that case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations were provided, so the description carries the full burden. It discloses that the endpoint takes no parameters, always reflects whichever games Yahoo currently has data for, and comes from Yahoo's own server-rendered page. It does not describe the unavailable state, but for such a simple fetch this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with the most important fact: the tool returns the current Olympics medal count. There is slight repetition of Yahoo Sports and current Olympic games, but each sentence still adds necessary information, so it remains concise overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema and no annotations, the description covers all essential information: return content, fields, ranking, source, current-edition behavior, and the absence of selection parameters. Nothing else is required to invoke it with confidence.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has zero parameters, and the description adds valuable clarification by stating that no parameter can select a prior edition. This prevents the agent from trying to pass a games or year argument, which is a real risk without that explanation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a clear verb and object: it returns the current Olympic games' full medal count by country, with exact fields and ranking. It also explains the current-edition scope, which differentiates it from the other sports and scoreboard tools in the sibling list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states when to use the tool: whenever the current Olympic medal table from Yahoo Sports is needed. It explicitly excludes historical or prior-edition selection, although it does not name an alternative tool; that is understandable given no direct alternative seems to exist.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are present, the description carries the behavioral disclosure burden. It reveals the data source ('sports.yahoo.com's own server-rendered standings page'), supported league enum, the exclusion of college-womens-basketball, and how soccer leagues differ structurally. This goes beyond a simple assertion that standings are returned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is long but every sentence is informative. It front-loads the core purpose and return structure, then enumerates supported leagues and edge cases. The enum list is lengthy but necessary because the schema lacks an explicit enum constraint.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no output schema, the description covers all essential aspects: what is returned, what fields are included, how it is grouped for different leagues, which leagues are unsupported, and the unusual soccer behavior. An agent has everything needed to decide whether and how to call it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description only says 'League key', but the description supplies the full accepted league enum, including variants like 'ligamx-apertura' and 'champions-league'. It also explains league-specific semantics, such as soccer leagues returning ungrouped tables with `record.points` populated. This adds substantial meaning beyond the minimal schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it returns league standings with specific fields (record, streak, games back, clinch status), grouped by conference/division. This distinguishes it from sibling tools like yahoo_sports_scoreboard and yahoo_sports_team by naming the exact resource and structure returned.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit context on when this tool is appropriate: when retrieving Yahoo Sports standings for a supported league. It also provides when-not-to-use guidance by listing the exclusion of college-womens-basketball and describing soccer-specific behavior. It does not explicitly name alternative tools, but the accepted leagues and behavioral conditions are clearly delineated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the read/retrieval nature, the scope ('single article'), and the concrete return payload. It does not discuss failure modes or edge cases, but for a simple fetch-by-URL tool this is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose, and every part earns its place: the resource, the returned fields, and the URL acceptance criteria are all useful and non-redundant.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter fetch tool with no output schema, the description is fully adequate: it identifies the input format, states the restriction to canonical article URLs, and enumerates the output fields. An agent has enough information to invoke it correctly and know what to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the schema already describes the url as a 'Canonical tech.yahoo.com article URL.' The description adds value by specifying the source of valid URLs (home or category story streams), which helps an agent know what kind of input is expected.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb and resource: it 'returns a single Yahoo Tech article's full content' and enumerates the exact fields returned (title, description, author, timestamps, section, image, keywords, publisher, body). This distinguishes it from yahoo_tech_home, yahoo_tech_category, and other article-type siblings by name and subject.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives practical guidance by saying it accepts a canonical tech.yahoo.com article URL 'such as one returned by the home or category story streams.' This implies the natural workflow without explicitly naming alternatives or stating when not to use it, so it falls just short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations available, the description carries the full transparency burden, and it rises to the occasion. It discloses best-effort relevance, fallback to broader results for obscure queries, the lack of a reliable field to detect fallback, and the non-error empty result for out-of-range offsets. There is no annotation contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded and dense, avoiding fluff apart from one slight opening repetition. Each of the remaining sentences contributes meaningful caveats or return details that help the agent predict tool behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the moderate tool complexity, the description covers pagination, edge cases, fallback semantics, and the result contents. Without an output schema, the description still gives enough behavioral detail for correct invocation, though exact section value examples or error responses are not described.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Parameter descriptions already cover all four parameters at 100%, so the baseline is 3. The description adds meaningful offset behavior and clarifies that searching is scoped to one department section, adding practical context beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly identifies a specific action and resource: searching Zara product listings by keyword within a single department section. It further distinguishes itself from potential siblings like zara_suggest or zara_category_products by framing itself as keyword search with product results, pricing, availability, and facets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives strong context: this is the correct tool when an agent needs keyword-based product search inside one department. It doesn't explicitly name alternatives or exclusion cases, but the content makes the usage scope clear enough to avoid obvious misuse.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, and it delivers: it lists the returned fields, states that both lat/lng must be provided, and specifies that a no-store response returns an empty array rather than an error. This covers an important edge case and gives the agent a clear behavioral model of the endpoint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and well-structured: purpose, return fields, and key usage constraints are all included in three sentences with no filler. Every sentence contributes distinct information, and the critical behaviors are front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple store-locator endpoint with no output schema, the description is complete: it names the domain (Zara physical stores), the requirements, the returned fields, and the empty-response behavior. The schema covers the radius and filter semantics, so nothing an agent needs to call this correctly is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds value by explicitly stating 'lat and lng are both required' and emphasizing that the endpoint does not accept free-text zip/city searches, which reinforces the coordinate-based parameter semantics and prevents a common misuse. The filters are not expanded, but the schema already covers them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Find nearby Zara physical stores.' It clearly distinguishes this tool from Zara product/category siblings by focusing on physical store locations and enumerating the returned store data (name, address, phone, etc.). It leaves no ambiguity about what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use the tool: when a location-based Zara store lookup is needed. It also states a critical constraint — lat and lng are both required and free-text zip/city search is not accepted — which prevents misuse. It does not explicitly name alternatives among siblings, but the context is strong enough for correct selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses the data structure (one document per subreddit × snapshot × rank), that history accumulates, and importantly states there is no score or comment-count field because the scraper does not expose vote counts, explaining that rank reflects Reddit's hot-feed order. This is rich, honest context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the purpose, and every sentence contributes: dataset structure, usage patterns, and a caveat about missing fields. There is no redundancy or fluff; it is appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description provides a solid overview of the dataset, default behavior, and key limitations. It does not enumerate return fields, but that is not required since no output schema exists and the schema covers query parameters. The description is complete enough for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining the default behavior of the date parameter (latest snapshot), the combination of subreddit and sort=date_desc for history, and the meaning of rank. This goes beyond the schema's per-parameter descriptions, particularly by clarifying the semantics of rank.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Search the reddit-trending dataset,' a specific verb+resource pair. It further clarifies the tool's unique scope by explaining it searches daily snapshots of subreddit hot-feed post order, distinguishing it from live Reddit tools like reddit_search and reddit_post. This is a clear, specific purpose statement.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides concrete usage guidance: with no date, the latest snapshot is returned; pairing subreddit with sort=date_desc retrieves historical trends. It does not name alternative tools explicitly, but the context of snapshots and history implies when this tool is appropriate. The guidance is actionable and helpful.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It discloses that only the first page is available, that further pagination requires a logged-in session and is out of scope, that most filters are ignored on the plain browse feed (except property_rentals), and that the endpoint may take up to a minute due to retries. These are non-obvious operational details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense but well-organized, covering purpose, pagination limits, filter behavior, and latency in a logical flow. Each sentence adds distinct value, though the length is substantial. It could be trimmed slightly without losing critical details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 8 parameters, no output schema, and no annotations, this description covers all essential aspects: return fields, pagination limitations, parameter interactions, and performance expectations. The browse vs. search distinction is fully explained. The description leaves no major gaps for an agent to select and invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All 8 parameters have schema descriptions (100% coverage), so a baseline of 3 is warranted. The description adds meaningful interaction semantics: minPrice/maxPrice/sortBy/daysSinceListed/condition are ignored on the browse feed except for property_rentals, which is not fully captured in the schema. This extra context elevates the score above baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Search Facebook Marketplace' and specifies the resource (Marketplace search/browse results) and the data returned (listing id, title, price, city/state, thumbnail). It distinguishes itself from facebook_marketplace_item by focusing on search/browse result lists, not individual item details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It clearly explains the browse vs. search modes ('Omit both query and category to get the location's browse feed'), details filter constraints ('only take effect alongside a query or category'), and warns about latency ('can take noticeably longer than other search endpoints'). Though it doesn't name alternative tools explicitly, the guidance is unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden—and it handles this thoroughly. It discloses that the data mirrors the live storefront, that category_id is only included for verified entries, that omitting rather than guessing is deliberate, and that visible labels are unreliable for deriving listing IDs. This is exactly the kind of behavioral honesty that prevents confident but wrong agent calls.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is longer than the minimum, but every sentence adds meaningful context: scoping, return contents, identity verification, and data limitations. The statement could be tightened on the repeated 'H&M's own storefront navigation' phrase, but the extra length earns its place by preventing a common misunderstanding about category_id reliability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one optional parameter and no output schema, the description fully equips an agent to decide and call it correctly: it knows what it will get, what might be missing and why, and how the department filter behaves. No critical gap exists.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter, department, has 100% schema description coverage, so the baseline is 3. The tool description adds functional meaning: department filters the result to one storefront department. It doesn't enumerate valid department values, but for a free-form optional string, the functional role is the most useful semantic addition. That lifts it to a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb ('Browse'), a specific resource (H&M's storefront category navigation), and clearly states what is returned: direct nav items and subcategories with display names and storefront URLs. It also distinguishes itself from related tools by explaining when category_id is included and why it's sometimes omitted. This goes far beyond a generic 'browse categories' description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives practical context on when to use this tool: to browse H&M's own storefront navigation, with the optional department filter. It also conveys a key usage caveat—category_id is only included when verified and should not be derived from visible labels. It doesn't explicitly name alternatives or when not to use it, but the behavior note effectively guides the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full disclosure burden. It states the tool is credential-free, returns public data, and is paged. It mentions the listing includes a short description, but does not elaborate on rate limits or response format structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long, each sentence adds unique and necessary information. No wasted words; the most critical details (purpose, parameters, access, alternative) are front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description provides a reasonable overview: returns a paged listing with short descriptions. It could be more specific about response fields or error scenarios, but the core behavior is sufficiently covered for an agent to select and use the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds valuable context beyond parameter names: it explains how host and site are derived from the careers URL, and notes that limit/offset control paging. The search parameter semantics are left to the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (List), the resource (Oracle Recruiting tenant's job board), and key features (paged via limit/offset, credential-free). It differentiates from the sibling jobs_oracle_job by noting the single-job endpoint provides full detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says to use the single-job endpoint for full detail, providing clear guidance on when to use an alternative. It also establishes context (public, credential-free) that helps determine appropriateness.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure and does so thoroughly. It reveals the data source (lululemon's app-backend category data), the return content (normalized products with pricing, sale detection, sizes, colors, style numbers), and importantly documents edge-case behavior: pages beyond the real last page return an empty products array, and unrecognized category/cdp_hash pairs return 404.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The three-sentence description is dense and mostly non-redundant, with the first sentence serving as an effective opening statement. There is slight repetition between 'Browse a... listing' and 'Returns one... listing page,' but overall each sentence earns its place and important details are surfaced without burying them.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema, the description covers request prerequisites, URL construction, parameter sourcing, response content, pagination semantics, and error behavior. It is complete enough for an agent to select, parameterize, and invoke the tool correctly in realistic contexts, including how to discover valid category identifiers.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3, and the description adds meaningful context beyond the schema. It explains that category and cdp_hash are the two path segments of a lululemon URL, provides a concrete example, and tells the agent they can come from lululemon-categories' fields. This materially helps parameter construction; page and page_size are already fully described by the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the resource ('a lululemon category's product listing') and the specific verb ('Browse/Returns'), making the tool's purpose unmistakable. It distinguishes itself from sibling tools like lululemon_categories by emphasizing a single category's listing page with normalized product details, and from lululemon_product by targeting category-level listing rather than individual product detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for invoking the tool: it requires a lululemon category URL's path segments and explicitly points to lululemon_categories as the source for obtaining valid category/cdp_hash values. While it doesn't explicitly enumerate when not to use it versus direct product-detail tools, the listing-vs-detail distinction is strongly implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully discloses behavioral traits: the data is large (tens of thousands of brand entries), effectively static, credential-free, and sourced from an anonymous, login-free session. It also includes caching guidance, which is valuable for an AI agent deciding how to invoke and use the tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long, front-loaded with the core purpose. Every sentence earns its place: the first states what it does, the second elaborates on the contents, and the third provides scale, stability, and auth context. No fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple no-parameter, no-output-schema tool, the description is highly complete. It covers purpose, response contents, scale, stability, and authentication requirements. The only minor gap is that it doesn't speficy the exact JSON response structure or field names, but the description is still more than adequate for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and an empty input schema, so there are no parameter semantics to clarify. The description adds context by detailing what the response contains (categories with parent linkage, every recognized brand, clothing/shoe/apparel sizes), which helps the agent understand the output scope.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Get Mercari full taxonomy (categories, brands, sizes)', which is a specific verb+resource that clearly states what the tool does. It distinguishes itself from sibling tools like mercari_search or mercari_item by focusing on taxonomy retrieval, not individual listings or items.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: it returns the full reference taxonomy in one call, and explicitly advises caching because the data is large and static. It implies usage for one-time taxonomy retrieval, but does not explicitly name alternative tools or state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure — and it does so thoroughly: keyword search is best-effort relevance with Nike's fallback to recommended results and no reliable signal to distinguish that fallback; only a structurally empty keyword yields a genuine empty result; navigation data appears only on the first page of a category listing; and paging beyond results returns a not-found error. These are exactly the hidden quirks an agent cannot infer from schema alone.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a dense block of roughly 200 words with no filler. Every sentence carries a distinct operational claim: return shape, dual-mode constraint, navigation data asymmetry, fallback semantics, and error cases. The structure is reasonable — purpose and the central constraint are front-loaded — and feels slightly long, which is justified by the dual-mode complexity and the edge-case-heavy behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description is the sole source of contextual risk knowledge, and it is complete: normalized product groups with pricing and variants, facet_nav and breadcrumb presence per mode, filter groups, keyword fallback and empty-result semantics, category value provenance, and pagination errors. An agent has everything necessary to select the right mode and interpret unexpected outcomes.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for all three parameters, so the baseline is 3. The description adds real value beyond the schema: the category sourcing rule (strip leading /w/), the page beyond range behavior, and the notion that a searched keyword must not be structurally empty to get a meaningful verdict all attach to parameters and are not expressed in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Starts with a specific verb and resource: 'Search or browse Nike products. Searches Nike.com product listings by keyword, or browses a category/subcategory listing by slug'. It names the two distinct modes of the tool and its target resource (Nike.com product listings), which makes it clearly distinguishable from the dozens of sibling search and product tools in the catalog.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on how to invoke each mode: 'Exactly one of keyword or category is required', plus concrete instructions on sourcing category values from nike-categories slug fields or from a prior facet_nav path with the leading /w/ stripped. The only gap is that it does not explicitly state when NOT to use this tool, e.g., that nike_product should be used for a single product page.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully carries the behavioral burden. It discloses the output format (name/cid pairs), ordering semantics, the section-level-not-unique caveat, and the brand limitation with a concrete technical reason (client-side JavaScript for other brands).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The core purpose is front-loaded and every sentence carries substantive information. However, the text is dense and would benefit from shorter sentences or a slight restructuring, though it contains no truly redundant content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There are no annotations and no output schema, yet the description gives the full invocation contract: return format, parameter behavior, ordering semantics, uniqueness caveat, and unsupported brands. Nothing an agent needs to select and call the tool correctly is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already has 100% parameter descriptions, so the baseline is 3. The description adds meaningful context beyond the schema: example top-level divisions, that a deeper cid is also valid, that the listing is section-scoped, and that brand=on is the only supported value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: "List Old Navy storefront categories" and describes the deliverable as name/cid pairs. It distinguishes itself from sibling tools such as oldnavy_search, oldnavy_product, and oldnavy_category by explaining it resolves the cid-discovery gap those tools document.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context for when the tool should be used: before other Old Navy tools that need cids. It also gives behavior-based guidance for omitting vs passing a cid, but does not explicitly state when-not-to-use or name alternative storefront-category tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations or output schema exist, so the description carries the full disclosure burden — and it meets it. It discloses a page-limiting behavior (one page, 10 reviews per page), the exact response fields, the default brand value ('on'), and the important edge case that an empty review set returns a well-formed empty result rather than an error. The only omissions are minor (sort order, exact failure mode on brand mismatch).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Four dense sentences, each carrying a distinct payload: scope, return shape, pid semantics and then brand semantics plus empty-result behavior. The purpose is front-loaded and there is no filler, though the brand sentence's parenthetical closures make it longer than strictly necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 3-parameter tool with no annotations and no output schema, the description is unusually complete: it covers parameter provenance, brand-value enumeration, defaulting behavior, pagination semantics, response structure, and the empty-reviews edge case. An agent can call this tool safely and interpret the result correctly without opening any other resource.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3, but the description adds real value. The schema only says 'Storefront the pid belongs to' for brand, while the description enumerates the allowed codes (`on`, `gap`, `br`, `at`) plus the default and the requirement that it match the pid's origin. It also reinforces the pid nuance with an explicit 'not the bare base product id', which is more precise than the schema's phrasing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Opens with a specific verb and resource ('Get reviews for an Old Navy, Gap, Banana Republic, or Athleta product') and surfaces the multi-brand scope that the tool name hides. It further enumerates exactly what is returned — six review fields plus a rating summary with average, count, per-star histogram, and recommended ratio — making it unmistakable against sibling review tools like nike_product_reviews or walmart_product_reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides concrete sourcing guidance: pid must come from oldnavy-search's colors[].id field, is the same pid oldnavy-product accepts, and the description warns that brand must match the storefront the pid was found under. It orients the agent to the correct inputs across the web, but stops short of an explicit when-not-to-use statement or named alternative review tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and excels: it discloses the underlying data source (RSS vs anonymous HTML), availability of metrics (net score, award count), limitations (large thread subset, no per-comment ratios), and precise HTTP status codes for empty, missing, and blocked scenarios.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is succinct yet information-dense, starting with a clear purpose and then systematically covering modes, limitations, and error codes. No redundant sentences or filler; each sentence contributes unique operational knowledge.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, but the description describes both the standard return (post with comments) and the metrics-mode return (server-rendered comments with net score/award count plus engagement metrics), along with edge-case responses. Minor gap: no guidance on retrieving additional comments when large threads are truncated, but overall it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds meaning by explaining the behavioral impact of include_metrics (switching source, credit cost, return fields) and the consequence of large threads on limit/depth. This goes beyond the schema definitions, justifying a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb ('Get') and resource ('Reddit post comments'), and clarifies the return as a Reddit post with its public comments. This distinguishes it from sibling tools like reddit_post, reddit_user_comments, and reddit_subreddit_comments, which target different Reddit data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on the two operation modes (default RSS 1-credit vs include_metrics=true 3-credit HTML), including the trade-offs (credit cost, subset exposure). It also gives error handling instructions (503 retryable vs 404). However, it does not directly state when to prefer this tool over sibling Reddit comment tools, so it leans on the tool name for that context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses that the tool returns data from a credential-free public JSON, indicating it is a safe read operation. No mention of rate limits or pagination, but the behavioral trait is clear. The description adds value beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, no wasted words. Each sentence adds unique value: purpose, enum details, parameter sourcing. The structure is efficient and front-loaded with the main purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with three required parameters and no output schema or nested objects, the description is complete. It explains what the tool returns (league table), how to use parameters, and data source. An agent can successfully invoke this tool with the given information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides descriptions for all three parameters (100% coverage). The description adds significant meaning by listing the enum values for 'type' (total, home, away) and explaining how to obtain 'id' and 'season' from other tools, which the schema does not cover.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns a league table (standings) for a competition season from SofaScore's public JSON. It differentiates from sibling tools like sofascore_event, sofascore_team, etc., by being specifically for standings. The source and credential-free access are noted, providing clear purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description tells when to use (to get standings) and provides specific guidance on obtaining parameters ('Get id from search and season from tournament-seasons'). However, it does not explicitly compare against alternatives or state when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It clearly discloses the key edge-case behavior: an unresolvable location or a radius with no stores returns a well-formed empty result rather than an error. It doesn't describe pagination or output structure, but for a store locator this is strong coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, zero waste. The purpose is conveyed in the first sentence including the return fields, then the required inputs, the optional radius, and the empty-result behavior each earn their sentence. The description is front-loaded and every clause adds distinct information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the purpose, the input constraints and relationship between the two modes, the radius default and bounds, and edge-case empty results. Almost everything an agent needs to call it is present. The only minor gap is that it doesn't state what happens if both search and lat/lng are provided simultaneously, but the 'Either search, or both lat and lng' wording implies mutual exclusivity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% so the baseline is 3. The description adds meaningful behavioral meaning beyond the schema: search is first resolved to coordinates, lat/lng skip that step, the two modes are mutually exclusive, and empty-result behavior. This justifies a score higher than baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Find') and resource (Ulta Beauty physical retail store locations) and lists exactly what is returned: name, phone, full address, hours, services, and coordinates. It clearly distinguishes this tool from the many nearby retail/product/search siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states the two input modes: 'Either search, or both lat and lng, is required.' It explains that search is resolved to coordinates while lat/lng skip that resolution, and specifies radius bounds and default. This is explicit when-to-use guidance for the main usage decision.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It adds useful context: the data is public, sourced from Vinted's server-rendered catalog navigation, and it explicitly notes the limitation that only the root level is included. Minor gaps exist, such as not specifying the exact return shape (array vs. object) or sorting, but for a simple, parameterless listing tool, this is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, using three sentences to cover purpose, scope limitation, and data source. Every sentence contributes valuable information without redundancy or fluff, and the key information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with no parameters and no output schema, the description covers the essential points: what it returns (with examples), the root-level scope limitation, how to access deeper levels via the `id`, and data source. It does not describe the exact response format (e.g., array of objects), but the mention of 'each entry' implies a list structure, and the description is sufficiently complete for basic usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description adds extra value by explaining that each entry's `id` from the response is directly usable as the `id` query parameter to /vinted/category, which aids in tool chaining. This goes beyond the empty schema and provides meaningful semantic guidance for the output.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'Returns Vinted's top-level catalog categories' and provides examples (Women, Men, Kids, Home, Electronics, Sports, Entertainment, Hobbies & collectibles). It explicitly distinguishes itself from sibling tools by noting it only covers the root level, with deeper levels not server-rendered, and points to the related vinted_category endpoint for deeper navigation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear usage context: it is the root-level categories tool, and it explains that deeper levels are not covered because they aren't server-rendered. It also provides a direct alternative path, stating that each entry's `id` can be used as the `id` query parameter to /vinted/category, which tells the agent when to use a different tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the data source (server-rendered race page), output contents, and accepted series values. It doesn't discuss error behaviors or dynamic data nuances, but it provides a reasonable behavioral picture.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Every sentence is dense and useful: returns, output fields, source, accepted series, and how to obtain the slug. The example is included efficiently without bloat.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter tool with no output schema, the description is nearly complete. Missing edge cases (e.g., what happens if the race slug is invalid) are minor and typical runtime concerns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining that `race` is the last path segment of a schedule URL and providing a concrete example, turning a vague slug into an instruction the agent can execute.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Returns') and resource ('one race's full driver-by-driver results') and enumerates the fields included, making it immediately clear what the tool does. It clearly distinguishes itself from the sibling yahoo_sports_motorsports_schedule by focusing on single-race results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs the agent to obtain the race slug from a motorsports-schedule response's race url, with a concrete example. Though it doesn't name exclusion scenarios, the linkage to the schedule tool gives a clear invocation path.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the behavioral burden well by disclosing that this endpoint always returns the current full-season snapshot and performs no server-side filtering. It also identifies the underlying source as Yahoo's server-rendered tournaments page. It could add more detail about freshness, response shape, or external constraints, but it is already unusually transparent for a zero-parameter read-only fetch.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded: the first sentence names the resource, the second details the response contents, and the third addresses invocation constraints. Every sentence earns its place and there is no filler or unnecessary context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema, the description is complete: it explains what data is returned, where it comes from, and what limitations exist. The most likely agent errors, such as adding season/gender parameters or expecting a filtered result, are proactively prevented. No relevant invocation detail is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Even though the input schema is empty, the description adds valuable meaning by explicitly stating that the endpoint takes no parameters and why: filtering happens client-side, not server-side. This prevents an agent from inventing parameters or expecting season/gender arguments. The current-full-snapshot framing clarifies what the response represents.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb/resource (returns the full-season tennis tournament calendar) and lists the concrete fields an agent can expect. It is explicit that this is tennis-specific and schedule-related, which distinguishes it from the Yahoo_F tennis rankings, scoreboard, team schedule, and other sports schedules among siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly conveys when this tool is appropriate: for a full-season tennis tournament schedule, and it explicitly warns that season/gender/match filtering cannot be done via this endpoint because filtering is client-side. It does not explicitly name alternative tools like rankings or scoreboard, but the context is strong enough for correct selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses key behaviors: the sku-to-canonical-page resolution, the requirement that market must match the originating storefront, and the absence of a default market. It also notes that a sku is typically only listed on markets that carry it. This goes beyond basic schema info, though it does not cover error scenarios or authentication needs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact (three sentences) and front-loaded with the core purpose. Each sentence earns its place, covering the return contents, sku provenance, and market constraint without fluff. Excellent structure for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 2-parameter tool with no output schema, the description is highly complete. It explains what the tool returns, how to source the sku, and the critical market matching rule. It could optionally mention error handling, but the absence is not a significant gap given the low complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds meaningful context by explaining that sku comes from sibling search/category tools and that market must correspond to the storefront where the sku was found, with no default. This enriches the bare schema descriptions and helps the agent construct correct parameter values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a single Zalando product with normalized details including brand, description, images, and per-size price/availability/GTIN. It uses a specific verb ('Get') and resource ('Zalando product'), and the specificity of the returned fields distinguishes it from sibling search and category tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly instructs the agent to pass the sku returned by zalando-search or zalando-category, and explains the market must match the storefront where the sku was found. It points to zalando-markets for the full reference list, providing clear guidance on when to use this tool versus alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully carries the burden of behavioral disclosure. It reveals the data source mechanism (server-rendered page embedded data), the fixed page size, the limited metadata-only result payload, and explicitly points to the job endpoint for full content. This is rich, honest disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences with no fluff. The purpose is front-loaded, followed by technical context, pagination behavior, and a pointer to the sibling tool. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 3-parameter search tool with no output schema, the description is complete: it explains what results contain (metadata only), the pagination limit, and where to get full descriptions. It sufficiently sets expectations for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% coverage with descriptive parameter names and examples (e.g., location slug format). The description adds the page size constraint, which is behavioral rather than semantic, but doesn't materially enhance parameter understanding beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it 'Searches Apple's public careers site (jobs.apple.com)' via a specific technical method. It differentiates itself from the sibling apple_jobs_job tool by noting that search results carry only metadata and directing users to the job endpoint for full details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance: use this tool to search Apple's careers site, and use the job endpoint for full descriptions and qualifications. It also notes the fixed page size of 20 results, which informs how to paginate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral burden. It discloses that certain accepted collection values return empty results (Mac collections), explains the category workaround for Games, and mentions optional expansion via full_detail. This goes beyond the schema and anticipates common agent confusion, which is excellent transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense but every sentence earns its place. It front-loads the main purpose, then enumerates valid values, highlights known issues, and gives a category workaround. The structure moves from general to specific, and the length is justified by the amount of necessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 free-form parameters and no output schema, the description covers purpose, valid inputs, and behavioral quirks thoroughly. The main gap is that it does not describe the return structure beyond 'ranked apps', which could matter for an agent parsing results. However, it provides enough context for a list tool, and the endpoint markdown reference offers an escape hatch. Slightly more detail on the response format would make it complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds substantial semantic value: it enumerates all collection values, notes which are currently broken, and explains how to use category for Games. This extra context is essential for parameter selection and is not fully captured by the schema descriptions alone. The description essentially acts as the reference for the collection enum.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Retrieve App Store collection rankings.' It clearly distinguishes from sibling tools like appstore_search and appstore_app by focusing on rankings from a collection. The scope is unambiguous and matches the tool name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context on when to use the tool (for collection rankings) and includes critical usage caveats: which Mac collections work, how to simulate Games rankings via category. It does not explicitly name alternative tools for different use cases, but the purpose is clear enough that an agent can differentiate from siblings. The pointer to endpoint markdown for full category IDs also supports correct usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden, and it does so thoroughly. It discloses the one-page limit of up to 24 items, the normalized fields returned, the default page behavior, and that requesting a page beyond the last returns an empty list rather than an error.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well organized and front-loaded: purpose and output shape first, then category_id, then page. Every sentence contributes actionable information without repeating schema details or adding fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter, no-output-schema tool, this description is complete. It defines the expected behavior, output fields, page size, default page, and edge-case behavior, giving an agent everything needed to confidently call and interpret the result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema already documents both parameters (100% coverage), so the baseline is 3. The description adds meaningful context by giving a concrete category_id example, explaining where to find that ID in the URL, and clarifying pagination behavior beyond the schema's simple name and type.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The first sentence states a specific verb and resource: it gets a Best Buy category's product listing. It also distinguishes this from sibling tools like bestbuy_categories or bestbuy_product by focusing on a paginated, normalized product listing with specific fields.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly conveys that this tool is for retrieving product listings for a known Best Buy category ID, and even explains how to locate the ID in a category page URL. However, it does not explicitly name sibling tools such as bestbuy_search or bestbuy_product or state when not to use this tool, so it stops short of a perfect score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations at all, the description fully assumes the burden of disclosing behavior, and it does so exceptionally. It declares the return payload (sku, name, url, image, price), clarifies the response is organic/non-sponsored, and defines the sku parameter. Most importantly, it preempts a likely error case by stating that pages without a comparison table yield an empty list rather than an exception.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Everything is front-loaded and tightly worded. The first sentence names the action and resource, the second sentence details the return format, and the third handles the edge case. No filler, no force- background, no repetition of schema fields.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one scalar parameter and no output schema, this description is complete. It covers input semantics, output contents, output shape, and the empty-case behavior. An agent has everything needed to decide whether to call it and to understand the results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has a single parameter with 100% description coverage, so the baseline is 3. The description still adds value by explaining that 'sku' is the numeric Best Buy SKU shown on bestbuy.com product pages and URLs, giving the agent a concrete way to locate the correct value. This empirical detail goes beyond the schema's 'Numeric Best Buy SKU'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Get a Best Buy product's related products') and identifies the exact resource and data source ('product page's own comparison table'). It goes further by clarifying it returns only organic, non-sponsored items and lists the returned fields, making the tool's purpose unmistakable and distinguishable from sibling Best Buy tools like bestbuy_product, bestbuy_product_reviews, or bestbuy_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context about when to use this tool: when you need the organic related products from a product page's comparison table. It also implies an exception via 'A product page with no comparison table returns an empty list.' It doesn't explicitly name alternative tools, but the source is described precisely enough that an agent can reason about when to call this versus other Best Buy tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full disclosure burden. It does a strong job by revealing a fallback of behavior: served from a live popular-lists source when available, falling back to a curated catalog otherwise. It also discloses that the endpoint does not search all user-created lists. This goes beyond a simple catalog description and sets honest expectations about the source and completeness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Each of the four sentences earns its place: the purpose, the return shape and source limitation, the fallback behavior, and the onward route to the list detail tool. All information is high-signal with no filler. The most important positioning is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, no-annotation, no-output-schema tool, the description is complete. It covers what is returned (id, name, category), the category enum values, the source and fallback, and provides the follow-up endpoint for the actual list contents. An agent has everything it needs to invoke and consume this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema is empty, so there are zero parameters to document. Per the baseline for a zero-parameter tool, this receives a 4. The description additionally lists the category enum, which clarifies output values rather than inputs, but it adds useful semantic context to the catalog's returned data.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'List curated Goodreads Listopia lists.' It also explicitly states what is returned (a catalog with id, name, category), which separates this catalog tool from the sibling goodreads_list that fetches a single list's contents. There is no ambiguity about the tool's purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear guidance: Goodreads has no directory/search endpoint, so this tool provides a catalog, and then explicitly instructs to pass the returned id to the goodreads_list endpoint for the ranked book contents. This routes an agent to the correct sibling tool and explains why this catalog exists.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does so exceptionally well. It discloses the credential-free backend, the behavior difference between query and no-query modes, the emptiness of phrase/content results in trending mode, and the non-session-scoped nature of search_history, which is far beyond a basic tool summary.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three information-dense sentences with no filler. The primary purpose is front-loaded, the mode distinction follows immediately, and the search_history caveat is an earned inclusion that prevents a likely agent misunderstanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-optional-parameter tool with no annotations and no output schema, the description covers all critical contexts: source, mode behavior, what is returned in each mode, and the misleading nature of one field. There is no meaningful gap that would prevent correct invocation or interpretation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents the query parameter at 100% coverage, so the baseline is 3. The description adds meaningful interpretation beyond the schema by explaining that query yields spelling-complete phrases and merchandised content, while omitting/empty yields trending searches and popular shortcuts, giving the agent more semantic grounding for the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a precise verb and resource: 'Get H&M search-box suggestions,' immediately distinguishing this from related tools like hm_search and hm_listing by naming the specific feature (typeahead suggestions) and upstream source. It also explains two distinct output modes depending on whether query is provided, which fully clarifies what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly defines when to use it: provide a query for phrase/merchandised suggestions, omit it for trending/popular searches. While it references hm-listing/hm-search as sharing a backend, it does not explicitly state when to choose those tools instead, leaving that inference to the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully discloses critical behaviors: credential-free access, pagination limits (first page only, no cursor), limit clamping to 50, include-only list semantics, and specific unsupported values. This is exceptional transparency for a complex tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a dense but efficient single paragraph. Every sentence conveys a constraint or behavioral detail; there is no filler or redundant repetition of schema information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a highly complex tool with 28 optional parameters, the description covers the most critical operational constraints: required filters, pagination behavior, list semantics, and unsupported features. It also hints at return fields (`total`/`has_more`), providing a complete operational picture.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers all 28 parameters with descriptions, but the description adds important semantics beyond the schema: which parameters are include-only, that limit defaults to 25 and clamps to 50, and that certain groups values are unsupported. This adds meaningful context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs IMDb advanced title search and returns normalized results from the specific imdb.com/search/title/ page. It distinguishes from sibling search tools like imdb_search by specifying 'advanced' and the exact URL, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: at least one filter is required, sort/limit alone are insufficient, and unsupported features are listed. However, it does not explicitly name alternative tools for unsupported cases, so it stops short of explicit when/when-not guidance relative to siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description takes full responsibility for transparency. It discloses the exact nature of the response (individual SKUs, prices, sale status, availability, rating, reviews), the input-derived 404 behavior ('An unrecognized product_id returns 404'), and clarifies that the slug is not needed. It doesn't mention authentication or rate limits, but for a simple read-only product detail fetch those are not obvious missing facts. The 'Get' verb itself communicates the read-only nature, and the 404 note adds useful edge-case behavior beyond schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is informative and front-loads the core action, then defines the specific content, parameter source, and error case. It is not overly long for the information conveyed. A small redundancy exists ('Full detail' appears in the first and second sentence), and the parameter section could be slightly tighter, but each sentence contributes substantive guidance, so it earns a 4.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema, this description does a thorough job of describing the return values: per-color/per-size SKU prices, sale status, live availability, aggregate rating, and full reviews, including the caveat that ratings/reviews appear only if any exist. It also covers the input source, an example URL structure, and the failure mode. An agent has everything needed to decide when and how to call this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite the schema having full coverage of the single product_id parameter, the description adds genuinely useful semantic detail not present in the schema: product_id can be sourced from a lululemon-category result's id OR the trailing path segment of a product URL, the slug can be omitted, and an unknown id returns 404. This helps an agent correctly extract the value from different contexts and reduces parsing ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb-resource pair ('Get a lululemon product's full detail') and immediately follows with a concrete enumeration of the returned content (per-SKU pricing, sale status, availability, ratings, reviews). It also explicitly differentiates this tool from lululemon-category, which only exposes a representative color/price. An agent can tell exactly what this tool does and how it differs from the sibling.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It clearly states the alternative (lululemon-category), explains the gap that this tool fills ('none of which lululemon-category exposes'), and gives the practical implication: use this tool when full SKU/rating/review detail is needed. It also provides concrete guidance on where product_id comes from, including both the category-result id field and the URL path segment, and notes that the slug is irrelevant. This is explicit when-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and excels: it discloses credential-free access, public data sourcing (server-rendered page and JSON API), the pagination behavior (profile omitted on subsequent pages), and the normalized output shape. This goes well beyond a typical tool description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four sentences, front-loaded with the core purpose, then pagination, then data source. Every sentence is informative with no fluff or repetition; it's efficiently structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given two parameters, no output schema, and no annotations, the description covers all critical aspects: return contents, pagination mechanics, first-page vs subsequent-page behavior, and data provenance. It is complete enough for an agent to invoke and interpret results correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already covers both parameters at 100%, and the description adds valuable context: it explains that max_id is an opaque pagination cursor and gives the exact flow (fetch without max_id first to get seller fields). This enriches the schema's terse descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Get Poshmark seller closet (storefront).' It clearly delineates what is returned (profile, reputation stats, listings, total count), distinguishing it from sibling tools like poshmark_listing or poshmark_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides strong usage context: it explains how to fetch the first page (without max_id) and subsequent pages (pass next_max_id back). It implies when to use this tool (when you need a seller's storefront), but doesn't explicitly name alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does so admirably. It discloses that the default mode uses RSS, the enhanced mode uses the anonymous HTML page, credit costs, that Reddit fuzzes voting data, and that share/repost/view counts are not exposed anonymously.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences deliver the essential information with no wasted words. The description is front-loaded with the primary purpose, followed by mode-specific details and limitations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description provides sufficient detail about both modes, the returned metrics, and known limitations. It covers the tool's complexity and gives the agent enough context to invoke it correctly and set expectations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds meaningful semantics beyond the schema by explaining that include_metrics=true triggers a different content source and returns specific metrics (net score, upvote ratio, comment count, award count, estimated upvote/downvote totals) for 3 credits.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets a Reddit post and returns a normalized public Reddit post. It distinguishes itself from related sibling tools like reddit_comments and reddit_search by focusing on fetching a single post by ID.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the default 1-credit RSS mode versus setting include_metrics=true for richer metrics. It does not explicitly mention alternatives or exclusions, but the context of two distinct modes provides clear usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and handles it exceptionally well. It discloses non-obvious upstream behavior: nonsense keywords still produce fallback results, one-sided price ranges are rejected because upstream silently ignores them, and facet combinations behave with specific OR/AND semantics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with purpose and return behavior, then transitions to critical edge cases and parameter combination semantics. Every sentence contributes essential guidance, and the length is justified by the 10-parameter, no-output-schema context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description covers the essential decision points: what products are returned, pagination behavior, the no-zero-result caveat, price pairing requirements, and facet combination rules. There are no serious gaps that would leave an agent guessing how to invoke this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents all 10 parameters at 100% coverage, so the baseline is 3. The description adds meaningful extra value by clarifying that prices are in whole dollars, that one-sided price ranges are invalid, and that brand/filter arrays are OR'd within a facet and AND'd across facets.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb ('Searches') and a precise resource ('Sephora's product catalog by keyword'), then specifies what is returned: normalized products with brand, pricing, rating, and review count. This clearly distinguishes it from sibling tools like sephora_category, sephora_product, or sephora_suggest.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly frames the tool as the keyword-search entry point into Sephora's catalog and gives detailed usage rules for filters, price ranges, and pagination. It stops short of explicitly naming when not to use it relative to alternatives like sephora_suggest or sephora_category.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It reveals that Tesla's endpoint always returns the entire dataset, that this tool filters and paginates server-side, and that results contain only metadata. This gives agents accurate expectations about results and performance.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four sentences, each conveying necessary information: purpose, endpoint source, upstream behavior, and return limitation. It is front-loaded with 'Tesla Jobs listing' and contains no filler or redundancy, earning every sentence its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking annotations and an output schema, the description adequately explains the tool's scope, return contents (metadata only), and relationship to the job detail endpoint. This covers everything an agent needs to select and invoke the tool appropriately for listing and filtering tasks.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All four parameters are already described in the input schema with 100% coverage. The description mentions filtering and pagination generically but adds no parameter-specific semantics beyond what the schema already provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states this tool lists and searches Tesla jobs from the public careers site, with the specific verb 'Searches' and a well-defined resource. It distinguishes itself from the job detail tool by noting listings carry metadata only and pointing to the job endpoint for full details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly instructs agents to call the job endpoint for full description/responsibilities when needed, establishing clear when-to-use guidance versus the detail tool. It also explains the search/filter/pagination behavior that is unique to this tool, making it easy to choose it for listing and filtering scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral disclosure burden—and it does well. It reveals that results are grouped into rails, gives concrete examples of rail types, and discloses the non-obvious edge behavior that a faster-shipping rail with no eligible items or a nonexistent id returns an empty normal result rather than an error.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, no filler: the purpose statement is front-loaded, the return shape is clarified immediately, and the edge-case behavior is placed at the end. Every sentence adds information the agent needs.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a simple two-parameter tool with no annotations and no output schema, the description is complete enough to use correctly: it covers the id source, the grouping/return concept, examples of rail types, and the fallback behavior for invalid or empty inputs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both id and count fully, which sets the baseline at 3. The description adds extra value beyond the schema by confirming id can be taken from a product page's URL, not only from a search result's product_id field.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a concrete verb and resource, 'Get a Wish product's related items,' and expands immediately into the specific return shape: related-item rails grouped by category. This clearly distinguishes it from Wish siblings like wish_product, wish_search, and wish_product_reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended usage is clear: use this when you have a Wish product id and want shelves of similar products. The description also explains where id comes from (search result's product_id field or a product page URL). It does not explicitly name sibling tools as alternatives or state when not to use them, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description accurately discloses the read-only behavior of listing keys. With no annotations, it carries the full burden and adequately conveys a non-destructive, informational action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences with no wasted words. It front-loads the purpose and is well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters, no output schema, and is a simple listing operation, the description is complete. It informs the agent that it returns sector keys usable with the sector endpoint.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters in the input schema, so the description has no need to add parameter information. Baseline score of 4 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists Yahoo Finance sector keys, specifying the verb 'lists' and the resource 'sector keys'. It distinguishes from sibling tools like yahoo_finance_sector by indicating these keys are for querying the sector endpoint.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by noting the keys can be used with the sector endpoint, suggesting a predecessor relationship to yahoo_finance_sector. However, it lacks explicit when-to-use or when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does so well: it specifies the data source (the category page's 'Category' filter facet), the return contents (name, id, url), and the empty-case behavior ('returns an empty list, not an error'). No side effects or hidden behavior are left ambiguous.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact while touching all essential points—scope, output fields, input format, data source, and edge case—without redundant or speculative text. Front-loading the main action supports fast agent routing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one parameter, no output schema, and no annotations, the description is complete: it explains what you get, where it comes from, how the input relates to the output, and what happens for leaf categories. No critical operational facts are missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although the schema already documents category_id, the description adds substantial extra meaning: it gives a concrete example ID, explains where to find the ID in a category page URL's trailing <id> segment, and explicitly states that each returned ID can be passed directly to bestbuy_category's category_id input. This greatly reduces the chance of misuse.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Get a Best Buy category's own sibling/child categories.' It clearly distinguishes this tool from bestbuy_category by emphasizing that the output is the sibling/child category set and that returned IDs feed directly into bestbuy_category's category_id input.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes clear the intended use case—retrieving a Best Buy category's sibling/child categories—and explains how the returned IDs can be reused by bestbuy_category. It does not explicitly name alternatives or state when not to use this tool, but the context is unambiguous given the sibling-tools list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations to rely on, the description carries the full burden and does so thoroughly. It discloses how salary is parsed, that min/max salary comparisons require a common currency, that location filters match parsed fields rather than substrings, that job_family excludes unclassified postings, and that employment_type and posted_at are never populated for certain providers. These are critical behavioral details beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense but well-organized, starting with purpose, then scope, defaults, and detailed filtering semantics. Each sentence adds value, and the enum lists and provider caveats are clearly delineated. Despite its length, the structure makes it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 19 parameters, no annotations, and no output schema, the description is remarkably complete. It covers default behavior, filtering semantics, salary and location edge cases, job_family classification, provider-specific gaps, and enum values, giving an agent everything needed to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although the schema already describes each parameter, the description adds significant semantic meaning: min_salary/max_salary operate on parsed salary and require salary_currency, city/state/country are exact-match on parsed components, include_closed defaults to false to include open roles, and the provider enum is listed with limitations for specific providers. This goes well beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as 'Search the jobs dataset (all companies' live postings)' with a specific verb and resource, and distinguishes it from sibling tools by noting it covers 'every job posting crawled from every discovered company ATS board' plus major tech career platforms. This sets it apart from provider-specific job board tools and other dataset search tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides strong usage context: open roles are the default, include_closed can be set for historical roles, salary filters require salary_currency, and location filters use exact parsed components. It does not explicitly name alternative tools for when this one should not be used, but the scope ('all companies') implies the distinction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden and excels: it discloses the 50-book limit, lack of pagination, credential-free nature, and the folksonomy/taxonomy structure. It also details exact return fields, which is comprehensive for a one-parameter tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single dense paragraph with no redundancy. Each sentence adds value: main action, output specification, tag format guidance, and limit disclosure. Front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a simple single-parameter schema and no output schema, the description is exceptionally complete. It covers return fields, volume limits, tag taxonomy pitfalls, and credential requirements, leaving no significant gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema provides only 'Goodreads genre/shelf tag'; description enriches this with examples (fantasy, romance, science-fiction), clarifies slug format, and explains how to source valid tags (from book's genres[] field or goodreads.com). This far exceeds schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Get a Goodreads genre shelf', clearly stating the verb and resource. It specifies what the tool returns (up to 50 books with fields) and distinguishes it from sibling tools like goodreads_author_books or goodreads_search by focusing on the genre/shelf tag page.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear guidance on when to use the tool: when you have a known genre/shelf tag. It explicitly states there's no directory endpoint and tells users to pass any known tag slug, giving concrete sourcing examples. It doesn't explicitly name alternative tools, but the context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does so thoroughly: it discloses normalized JSON output, omission of empty blocks, locale defaults, Chrome-impersonated fetching, 503 on challenge/unusable/unrelated responses, and 400 for site: queries. This gives the agent an accurate picture of success and failure modes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is information-dense with no fluff. Every sentence earns its place: result contents, optional-block behavior, defaults, error semantics, and an alternative for unsupported queries. It is front-loaded with the core purpose and adds detail only where needed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and no annotations, the description fully covers what the agent needs: return types and pagination, filter behavior, error/status codes, unsupported operators, and locale handling. It is complete for a search tool of this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds meaningful context beyond the schema by explicitly stating country/lang defaults and explaining that site: queries in q are rejected. It reinforces pagination and count behavior without adding syntax, but still provides useful operational detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Search Bing web results' — a specific verb plus resource — and enumerates the return types (organic results, context panel, related queries, PAA, news, video, pagination). This clearly distinguishes it from sibling tools like bing_news or bing_videos and from google_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when not to use the tool: queries with the site: operator are unsupported and rejected with 400. It also names an explicit alternative: 'Use the Google search endpoint (/api/v1/google/search) for domain-restricted searches.' This is clear when/when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the full behavioral disclosure burden and does so thoroughly: it reveals there is no pagination, that shelves are a fixed hand-curated set, that only the trailing id from a URL is used, and that unknown ids return a 404 instead of an empty result. These are meaningful behaviors beyond what the input schema could convey.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Every sentence contributes useful, non-redundant information: what the resource is, examples, distinction from the sibling, accepted id formats, response contents, pagination semantics, and error behavior. The main verb is front-loaded, and the text is dense without being bloated.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema and no annotations, so this description correctly fills both gaps: it enumerates the return payload (title, breadcrumb, named shelves, category-navigation tile grid), explains the no-pagination behavior, and specifies failure behavior. For a single-parameter read tool, nothing necessary is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although schema coverage is 100%, the description adds significant value beyond the schema by explaining that id can be either a bare numeric id or a full /cp/{slug}/{id} URL, and that only the trailing id is used. This directly improves the chance the agent constructs a valid request.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource ('Get a Sam's Club curated content or landing page') and gives concrete examples like a seasonal savings hub or 'New Arrivals' page. It also explicitly distinguishes the tool from GET /samsclub/category's flat, paginated product grid, so an agent can separate it from samsclub_category.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly positions this tool as the one for curated content/landing pages, and explicitly contrasts it with the flat, paginated product-grid behavior of GET /samsclub/category. It also gives usable guidance about input formats and the 404 vs zero-result difference, which helps the agent choose and use the tool vs. its sibling.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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