Market Data

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description explains the data collection method, notes that some listed jobs may be closed, and includes pricing. It provides behavioral context beyond the bare operation, though it does not explicitly state read-only status 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise: two sentences covering purpose, data source, output format, and pricing. No wasted words, and essential information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given 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 provides adequate context about the output fields and data source. However, it lacks details on error handling or pagination, which could be helpful but are not critical.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% coverage of all 5 parameters, so the baseline is 3. The description does not add parameter-level details, but the schema itself is thorough, making additional description unnecessary for this dimension.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool retrieves job postings from Azerbaijan's boss.az, explaining the data source and output fields. It distinguishes from sibling tools by specifying the geographic and platform focus.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does 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. The description implies its purpose through context, but does not state 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.

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 only mentions 'live' and 'public JSON API' but omits details like rate limits, error handling, data freshness guarantees, or any restrictions. This leaves significant 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences effectively convey purpose, data scope, technical ease, and pricing. 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.

Given 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 query construction, concurrency, and cost. It does not describe return format, which might be important but is absent. Overall adequate for the complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does 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 value by explaining the format of region_v2 and category codes, how to find them, and the behavior when omitting cg. This goes beyond the raw schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool pulls live classified ad listings from Chotot's public JSON API, specifying the resource (listings), verb (pull), and method (by region and category). It also distinguishes from siblings by focusing on Chotot classifieds and mentioning no login needed.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on when to use (pulling listings via API without authentication) and mentions cost per call. However, it does not explicitly state when not to use or suggest alternative tools for different data sources.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description discloses API source, cost, sorting order, and that it's a watch operation (read-only). It does not mention rate limits or pagination details, but still provides good 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the core purpose, followed by output details and cost. No redundant words, every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 4 parameters and no output schema, the description covers what the tool does, what data it returns, and key operational details (cost, API source). It lacks explicit return format but is sufficiently complete for a monitoring tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does 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 output structure (NCT id, status, etc.) which aids understanding but doesn't significantly enhance parameter meaning beyond the schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool watches conditions, drugs, or sponsors for new and updated clinical trials, and lists specific output fields (NCT id, status, phase, sponsor, URL). It distinguishes from sibling monitoring tools by focusing on clinical trials.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Description provides context: uses official ClinicalTrials.gov API v2, free, no API key/login, cost per call. While it doesn't explicitly compare with sibling tools, the domain-specific wording implicitly guides 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.

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 the tool searches and returns public listings (non-destructive), and mentions costing, but lacks details on authentication, rate limits, or caching behavior. More transparency is needed for a tool with zero 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, focused sentence with a pricing note appended. It is front-loaded with the core action and results, with zero wasted words. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is relatively simple with two parameters and no output schema. The description covers the basic functional aspects (what to search, what returns) but omits details like pagination, result limits, or error handling. 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.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, with both parameters having descriptive schema comments. The tool description adds no new parameter details beyond what the schema already provides. 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.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Search' and the specific resource 'Computrabajo' with geographic scope (Mexico, Colombia, Chile, Argentina, Peru). It lists returned fields (title, company, location, URL, posted-when), making the purpose unambiguous and distinct from broader job aggregator siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context on where to use (specific countries) and what to search by (keyword), but it does not explicitly state when to use this tool vs. alternatives like job-postings-aggregator or when not to use it. Price mention is incidental, not a usage guideline.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 pricing ($0.03/call, USDC on base) and that results are returned as structured rows, which adds some behavioral context. However, it does not mention rate limits, error behavior, or that it relies on public search pages, 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two short sentences. The first front-loads the core purpose and output fields, and the second provides pricing in a compact format. Every word earns its place without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given 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 compensate. It lists the return fields, which helps, but it does not specify the exact JSON structure, pagination behavior, or potential failure modes. For a search tool with three parameters, 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.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema descriptions cover 100% of the parameters, including query, max_items, and max_pages. The description adds minimal semantic value for parameters beyond the schema, only implying the 'query' parameter. This matches 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.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action (search Detik news by keyword) and the resource (Detik). It enumerates the returned fields (headlines, excerpts, timestamps, sections, images, URLs), which distinguishes it from sibling scrapers targeting other sites.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context: this tool is for searching Detik news by keyword. It implies the appropriate use case (Indonesian news retrieval) but does not explicitly exclude alternatives or mention when not to use it. Given that siblings are all site-specific scrapers, the usage 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.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must convey behavioral traits. It states 'Pull live listings' suggesting read-only, fresh data, and the absence of login/browser/proxies is positive. But it fails to disclose potential failure modes (e.g., site changes, rate limits), error handling, or any side effects. Minimal disclosure beyond the surface.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise—a single sentence plus a pricing tag—with no filler. It is front-loaded with the core action and source. Every word earns its place; the key information is immediately accessible.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (5 parameters, no output schema), the description should explain what the returned data looks like or what fields are included. It does not. For a listing extraction tool, this is a significant omission, leaving the agent uncertain about the output format.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All five parameters have detailed descriptions in the input schema (100% coverage), so the parameter semantics baseline is 3. The description adds context about the site and pricing, but does not enhance understanding of any parameter beyond what the schema already provides. No additional value for parameter meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Pull live apartment/housing listings'), the data source ('Emlakjet.com'), the geographic scope ('Istanbul'), and the primary filters ('by deal type (sale/rent) and property type'). This distinguishes it from sibling listing scrapers focused on other regions or portals.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions 'No login, no browser, no proxies' implying ease of use, and includes pricing. However, it provides no explicit guidance on when to choose this tool over alternatives (e.g., 'use for Istanbul property data only') or when not to use it. The name and sibling context hint at scope but are not definitive.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 openFDA, is free and requires no login, has a cost per call, and returns application status, sponsor, and recall details. However, it omits details on rate limits, error handling, or behavior on empty results. No contradictions found.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loading the core purpose in the first sentence. Every sentence adds value, with no fluff. It efficiently conveys purpose, data source, cost, and return information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description outlines what information is returned (application status, sponsor, recall details). However, it lacks details on output format, pagination, or error cases. It is adequate but not fully complete for a monitoring tool with 4 parameters.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All 4 parameters have descriptions in the schema (100% coverage), so the description adds minimal extra meaning beyond schema. It mentions pricing and data source but no additional parameter guidance. Baseline for full coverage is 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Watch drugs or companies for new FDA approvals and recalls.' It specifies the verb 'watch' and the resource, effectively distinguishing it from sibling monitoring tools that focus on other domains (e.g., clinical trials, job postings).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context about the data source (official openFDA, free, no API key) and pricing, but does not explicitly guide when to use this tool versus alternatives. It implies usage for FDA-related monitoring, but no when-not-to-use or comparison to siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 the public TED API usage and cost per call, but omits details like pagination, rate limits, 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief (two sentences plus cost) and front-loaded with core functionality. Very little waste, 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.

Given 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 values (title, buyer, country, etc.). Missing pagination or ordering info, but acceptable for a search tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for all 4 parameters. The description adds high-level context (e.g., 'by keyword or CPV code') but does not significantly enhance understanding beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches EU public-sector tenders by keyword or CPV code with optional country filter, and lists the returned fields. This distinguishes it from unrelated sibling tools like job postings or clinical trials.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states that no API key or browser is needed, indicating ease of use. However, it does not mention when to avoid the tool or point to alternatives for other data sources.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description mentions 'No login, no browser, no proxies' and pricing, adding some behavioral context. However, it does not disclose error handling, rate limits, or data freshness. With no annotations, the description partially meets transparency needs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with key details and pricing, but includes promotional fluff. It is reasonably concise and front-loads the purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given 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 the core functionality but omits output format, pagination, and error behavior. Without an output schema, the agent may need to infer returns.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does 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 little extra meaning beyond stating the filtering dimensions. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool pulls live apartment and house listings from Imovirtual.com, specifying the source portal and filtering dimensions (deal type, property type, city). It implicitly distinguishes from siblings by naming the Portuguese platform, but does not explicitly compare.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does 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 real estate tools. The description lacks context about preferred scenarios, prerequisites, or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 data source (SEC EDGAR), cost ($0.01/call), and output (filing counts, activity signal, document links). It does not cover error handling or edge cases, but it adequately sets expectations for typical usage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured paragraph that front-loads the main purpose, includes key details like data source and pricing, and contains no extraneous information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description adequately describes return values (filing counts, activity signal, document links). It provides enough context for an agent to understand what the tool delivers, though additional detail on the structure of the activity signal could improve completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does 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 context about the output but does not elaborate on parameter semantics beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool tracks insider stock trades via SEC Form 3/4/5 filings for a list of tickers, specifying the resource and action. It does not explicitly differentiate from sibling tools like 'sec-edgar-watcher' or 'thirteen-f-tracker', but the purpose 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.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description indicates it uses official SEC EDGAR data, is free, and requires no login, implying ease of use. However, it does not provide explicit when-to-use or when-not-to-use guidance relative to siblings, 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.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must convey behavior. It discloses incremental behavior and baseline creation, but omits details like idempotency, side effects, or state persistence. The pricing info is provided but is not behavioral. Some behavioral context is added, 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two sentences plus a pricing note. It front-loads the core purpose and first-run behavior. Every sentence serves a purpose with no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description lacks information on output format, scheduling, state management, and how to set up the watch name (baseline_key). While the schema covers parameters, the overall tool context (e.g., expected usage pattern, return structure) is insufficiently described.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does 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 beyond the schema's parameter descriptions, which already explain board, filter, max_items, and baseline_key. No additional semantic value is contributed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: watching a job board for a saved filter and returning new postings since the last check. It specifies the incremental monitoring behavior and mentions the first-run baseline creation, distinguishing it from sibling tools that are individual board scrapers or aggregators.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for recurring checks, but it does not explicitly instruct when to use this tool over alternatives like direct board scraping (e.g., jobs-ch-swiss) or the aggregator. No 'when not to use' or alternative tool references are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses positive traits: 'No login, no scraping, no proxies', implying safe, legitimate access, and includes pricing ($0.02/call). However, it does not address error handling, data freshness, or behavior on invalid company slugs, 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that efficiently conveys the main action, output fields, and key behavioral notes. It is front-loaded and avoids fluff, but the pricing at the end could be considered an extra detail rather than essential usage guidance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given 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 output format (one row per posting with specific fields). It also notes the tool's legitimate nature. Lacking are details on error states, result limits, or handling of multiple companies, but overall it provides sufficient context for a simple aggregation tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does 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 repeats ATS names and examples already in the schema, adding no substantial new meaning beyond the input schema's explanation of the 'provider:company' format. It does not explain the 'maxConcurrency' parameter further.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the tool pulls open roles from public ATS systems (Greenhouse, Lever, Ashby) and normalizes each posting into specific fields (title, location, department, URL, posted date). This verb+resource combination is highly specific and distinguishes it from sibling tools, which include other job-related tools but none aggregating across multiple ATS in this manner.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does 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 vs alternatives or when not to use it. While the purpose is clear, there is no guidance on prerequisites, limitations, or comparison to other job-listing 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.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must disclose behavior. It states the tool returns public listings and mentions pricing, but does not clarify it is read-only, whether authentication is required, or any side effects. The schema notes fetch_full_description is slower, but the main description omits this.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the verb and resource. No wasted words, though the second sentence includes cryptic pricing details (x402, USDC). Still concise and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description reasonably enumerates returned fields (title, company, location, etc.). It does not clarify result structure (e.g., array of objects) or pagination behavior, but covers essential output expectations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so each parameter is described. The main description adds minimal extra meaning beyond 'Search by keyword'. Baseline 3 is appropriate as no additional semantic context is provided.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool scrapes jobs.ch for Swiss job listings by keyword and lists returned fields. It distinguishes from regional siblings by specifying Switzerland, but could be more explicit about its unique scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does 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., other job scrapers). The description does not mention prerequisites or exclusions, leaving the agent without decision-making support.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It discloses 'No login, no browser, no proxies' and pricing ($0.02/call). However, it lacks details on rate limits, caching, pagination behavior, or error handling, which are important 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise, delivering key purpose and features in a single sentence with no wasted words. It immediately informs the agent of the tool's value and constraints.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given 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 lacks details about the return format (what fields, structure). It provides enough for basic selection but not full operational context, especially given parameter completeness is high.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does 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 minimal extra meaning, just reiterating the query format. Baseline score of 3 is appropriate as description does not significantly enhance parameter understanding beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it pulls 'apartment and house listings straight from Krisha.kz', specifies deal type, property type, and city. It distinguishes itself from siblings by being the only tool for Kazakhstan's real estate, with a specific verb 'Pull' and resource.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implicitly guides usage by naming the specific source (Krisha.kz) and stating 'No login, no browser, no proxies', suggesting it's easy to use. However, it does not explicitly state when to use vs alternatives or provide exclusions; the sibling tool list fills that gap.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full responsibility. It discloses the data source (DexScreener) and pricing model but does not mention rate limits, error handling, or what happens if a token is not found. The description could be more transparent about limitations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with two main sentences and a pricing note, all front-loaded with purpose. It is not overly verbose, but the inclusion of the pricing as a separate sentence could be more integrated. Overall, efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, yet the description only hints at return fields (24h change, liquidity, volume, best DEX pair) without specifying structure. Error cases and edge conditions are unaddressed. The description is adequate but not fully complete for a tool with 3 parameters and no output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the parameters are already well-documented. The description adds no significant new meaning beyond what the input schema already provides (e.g., 'tokens' param already mentions contract addresses and tickers). Baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool provides 'Current USD price for any token by contract address or ticker' along with additional data points (24h change, liquidity, volume). The verb 'get' is implied, and the resource 'token price' is well-defined. The tool is distinct from siblings like job boards and trackers.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description specifies it uses DexScreener's public API, is keyless, and costs $0.01/call, indicating it's for quick, cheap lookups. However, it does not explicitly compare with the sibling 'pricing_info' tool, which might serve a similar purpose. The guidance is clear but lacks exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description must disclose behavioral traits. It mentions pulling live listings and implies a read-only operation, but does not detail rate limits, pagination behavior, error handling, or data freshness. The focus is on marketing rather than 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise with two sentences that front-load the purpose. It includes useful context about pricing but avoids unnecessary verbosity. Could be slightly tighter by removing the pricing detail, but overall it's efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, and the description fails to explain what the returned listings contain (e.g., titles, prices, URLs). It also omits details on error cases or data limitations. For a tool with five parameters, the description is too thin to fully inform an agent of the tool's capabilities and constraints.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with detailed parameter descriptions (e.g., city path, enum values). The tool description adds no additional meaning beyond what the schema already provides. Therefore, it meets the baseline expectation for high coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it pulls live listings from Otodom.pl, specifying deal type, property type, and city. It distinguishes itself by naming the specific Polish portal and mentioning no login/browser/proxies, which differentiates it from other region-specific real estate tools among siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does 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 is provided. The description only promotes its features and pricing, without any context on when not to use it or what alternatives might be better suited for other regions or use cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It mentions 'Free' and lists data fields, but does not disclose side effects, idempotency, or whether the data is static. Adequate for a simple read operation 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, 24 words, front-loaded with 'Free'. Every sentence adds unique value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given 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. It only lists fields but does not describe the output format (e.g., array, object) or what agents should expect. This is a critical gap for utility.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Tool has 0 parameters; baseline is 4 per rules. Description does not need to add parameter info since none exist.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states verb 'list' and specific resource 'every paid tool in the market-data bundle' with price, payTo address, and network. Differentiates from sibling tools that focus on other data domains.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit context: 'Call this first if you don't have a wallet ready yet.' This tells when to use, but lacks when-not-to-use 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.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses pricing ($0.02/call), no login/browser/proxies needed, and uses sitemap-declared pages (via schema). Good transparency for a web scraping 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, efficient, 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.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Adequate for a data pull tool with good schema, but lacks description of output format or fields returned, which would help agents parse results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema descriptions cover all parameters (100% coverage). The tool description adds no new parameter info; baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it pulls listings from PropertyFinder.ae, specifies property types, deal type, and emirate filtering, and distinguishes from siblings by focusing on UAE real estate.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Describes what the tool does but lacks explicit when-to-use or when-not-to-use guidance relative to siblings. Implicitly for UAE listings, but no direct alternatives or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description must cover behavior. It discloses it is a read-only operation ('pull live...listings') and cost ($0.02/call). However, it omits rate limits, data freshness, or any side effects. 'No login, no browser, no proxies' implies low friction 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is one paragraph with clear structure: action, source, parameters, and constraints. It includes a pricing note which, while useful, is slightly extraneous. Could be trimmed without losing meaning, but is well-organized.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, description should clarify return structure. It does not mention what each listing row contains (e.g., price, location, link). The tool's purpose is clear, but agents might need guidance on parsing results. Adequate but not fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, baseline is 3. Description adds value by explaining deal_type enum meanings (e.g., 'najam' maps to long-term rental), region path format (e.g., 'budva/Crna-Gora'), and numeric parameter purposes. This goes beyond the schema defaults and enum titles.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description explicitly states it pulls live apartment/house listings from Realitica.com, covering Montenegro, Croatia, Serbia, by deal type, property type, and region. This clearly distinguishes it from sibling real estate tools focused on other regions (e.g., Istanbul, Lisbon, Warsaw).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Description explains use case (pull listings without login/browser) and pricing, but does not specify when not to use or suggest alternatives among siblings. The regional focus is implied but not contrasted with other property tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description mentions that the first run creates a baseline and notes the cost ($0.05/call). However, it fails to disclose that the tool is stateful (using baseline_key for memory), that it calls other actors, or that charging scales with new listings. With no annotations, these gaps reduce transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise—two sentences covering core functionality and pricing. Every sentence earns its place, and it is front-loaded with purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (4 parameters, nested objects, no output schema, no annotations), the description is incomplete. It omits that the tool is a meta-actor that uses other portal actors, manages state, and charges per new listing. Parameter descriptions compensate partially but leave behavioral gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, with detailed descriptions for each parameter. The tool description adds some context about 'saved filter' and 'previous check' but does not significantly enhance 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.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it watches a property portal for a saved filter and returns only new listings since the previous check. This is specific and uses strong verbs. However, it does not explicitly differentiate from sibling tools like job-alert, which follow a similar pattern for jobs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does 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 does it mention when not to use it. Siblings like job-alert imply similar use cases, but the description does not clarify unique applicability.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description must cover behavior. Mentions 'No login, no browser, no proxies' and cost, but omits rate limits, error handling, return 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no redundant information. Front-loaded with purpose and scope, then adds key differentiators (cost, no proxies). Every word adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, and description does not mention what fields are returned or if there are pagination limits. Incomplete for a tool with 4 parameters and no output structure.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptive parameter descriptions. Description adds value for location_identifier by explaining how to find codes, but does not enhance max_items or max_pages beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description specifies verb ('Pull'), resource ('property listings'), and scope ('from Rightmove.co.uk' with flexibility for location code). Clearly distinguishes from sibling tools by naming the platform.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool instead of alternatives. Mentions lack of login/browser/proxies but does not compare to other listing tools in siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 heuristic nature, data sources, and constraints, but does not mention destructiveness, rate limits, or other behavioral traits important 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, front-loading the core purpose and key differentiators in a few sentences. No redundant or filler content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given 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 format (e.g., score range, fields). It only says 'heuristic signal' without specifying the output structure, leaving the agent underinformed about what the tool returns.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does 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 three parameters adequately. The description does not add significant parameter-level details beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool scores rug-pull risk for ERC-20/BEP-20 tokens using specific data sources and checks (honeypots, high taxes, liquidity, age). It is distinct from sibling tools like token-launch-radar, 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.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context on what the tool does and does not require (no wallet, no RPC, no browser) and mentions pricing, but lacks explicit guidance on when to use this tool over siblings like token-launch-radar or live-price-oracle.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 uses official SEC EDGAR data, is free with no API key, and costs $0.01/call (USDC on base). It also mentions the rate limit indirectly via maxConcurrency. It does not specify data freshness or whether results are real-time, but for a monitoring 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that front-loads the main action, then adds key details (form types, output, pricing). Every phrase adds value with no redundancy. It efficiently uses dash-separated items for clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple with no output schema. The description explains output ('form, filing date and a direct document URL for every match') and mentions pricing and rate limits. It covers the essential aspects for a monitoring tool, though it omits potential pagination or error handling.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema has 100% description coverage for all 4 parameters, so the baseline is 3. The description adds minimal extra meaning beyond summarizing what the schema already provides ('Filter by form type and lookback window'). It does not provide examples or clarify edge cases.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Watch stock tickers for new SEC filings' and lists example form types (10-K, 10-Q, 8-K, S-1), establishing a specific verb-resource pair. It distinguishes itself from sibling tools, which are in different domains (e.g., job listings, clinical trials, insider trading).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for monitoring SEC filings by ticker, with filtering options. While it doesn't explicitly state when not to use or list alternatives, the sibling tools are sufficiently different in domain that no confusion arises. A mention of when to prefer this over other SEC data tools would improve it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 source, that data is live, currency handling (GEL or USD), and that no login, browser, or proxies are needed. It also includes pricing details ($0.02/call, USDC). Lacks rate limits or error behavior, but overall transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single paragraph that is front-loaded with the primary action and source, followed by key details (currency, no login, pricing) in a compact, efficient manner. Every sentence serves a purpose, with no superfluous text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given 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 compensate by clarifying what the output contains. It mentions 'live real-estate listings' but does not specify fields or structure. The parameter descriptions hint at 'listing rows' but not enough detail. Context for usage is solid, but output expectations are vague.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The tool description adds global context (city, currency, no proxies) but does not provide extra parameter-specific meaning beyond what the schema already offers (e.g., city_id list, deal_type details). Satisfactory but no extra value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool pulls live real-estate listings from SS.ge, Georgia's largest classifieds portal, by city with price in the seller's currency. This is specific and distinguishes it from sibling tools that focus on other regions (e.g., rightmove-london, emlakjet-istanbul).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides contextual usage cues: 'by city' and includes city IDs in parameter descriptions. It mentions 'no login, no browser, no proxies', implying straightforward use. However, it does not explicitly state when to use this tool versus alternatives, though the geographic specificity is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must fully disclose behavioral traits. It indicates a read-only, public data operation and includes pricing. However, it lacks details on rate limits, caching behavior, data freshness, or the structure of returned listings. The pagination parameters are implied but not explained in terms of behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that front-loads the core purpose and resource, followed by key differentiators. Every phrase serves a purpose, and there is no unnecessary verbosity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given 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 hint at the output format, but it only says 'listings' without specifying fields. It covers the input parameters and ease-of-use aspects, but the lack of output documentation leaves a gap. Sibling tools may follow a similar pattern, but for autonomous use, more completeness is desirable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does 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 summarizes key parameters but does not add significant meaning beyond what the schema already provides (e.g., enum descriptions, defaults, ranges). It mentions city, deal type, property type in the overview but no additional semantic context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's action ('Pull live apartment and house listings'), specific resource ('Storia.ro — Romania's biggest real-estate classifieds portal'), and filtering dimensions ('by deal type, property type and city'). This distinguishes it from sibling real estate tools focused on other regions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions ease of use ('No login, no browser, no proxies') and pricing, but does not explicitly state when to use this tool versus alternatives like otodom-warsaw or rightmove-london. The agent can infer from the Romania-specific context, but no direct guidance on exclusions or conditions is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It discloses the tool requires no login, browser, or proxies, and notes that only the 'menziller' category is verified. However, it omits other behavioral details such as rate limits, error handling, or whether the tool handles pagination automatically, 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise, using two sentences and a pricing line to convey the core purpose, value proposition, and a key constraint. Every sentence is informative without redundancy, and the main action verb 'Pull' is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (scraping a live marketplace) and lack of output schema, the description fails to explain what the returned listings contain (e.g., fields like title, price, link, date). Sibling tools are numerous, and additional context on output structure would improve usability.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does 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 minimal parameter-specific context (e.g., 'by real-estate category' aligns with the 'category' parameter), but does not enhance meaning beyond what the input schema already provides. No additional semantics for 'max_items' or 'max_pages' are given.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool pulls live apartment listings from Tap.az, a specific marketplace, by real-estate category. It includes unique selling points (no login, no browser, no proxies) and pricing, making the purpose unambiguous and distinct from sibling tools like 'boss-az' which likely target a different source.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does 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 scenarios where this tool is preferred or when to avoid it, nor does it reference sibling tools. Users must infer usage from the name and description alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Despite no annotations, the description discloses key behavioral traits: incremental updates, first-run baseline, pricing model ($0.05/call, per-tender charge), scoping per user account, and that compute limits are not billed. It does not describe potential auth needs or data freshness, but covers the main safety aspects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two sentences plus a pricing line. Every sentence conveys essential information without redundancy. Front-loaded with the core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (5 parameters, no output schema), the description adequately explains behavior, parameter roles, and constraints. It covers first-run behavior, pricing, and scoping. However, it could briefly mention what the output looks like (e.g., list of tender IDs) given no output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does 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: e.g., clarifies that limit compute is not billed, queries use TED syntax, baseline_key ensures independent watches. This adds value beyond the schema definitions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses specific verbs ('watches', 'returns') and identifies the resource ('public tender feeds'), clearly distinguishing it from siblings like 'gov-tender-radar' which likely performs full searches. The incremental change detection is explicitly stated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for monitoring changes and mentions first-run baseline behavior, but does not explicitly contrast with sibling tools or provide when-not-to-use guidance. The pricing hint is useful but not directive.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

In the absence of annotations, the description discloses behavioral traits: it mentions name resolution behavior (returns shortlist on multiple matches), pricing, and data source. It also indirectly addresses rate limits through the maxConcurrency parameter description. This provides 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences plus a pricing line, highly concise and front-loaded with the core 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.

Given 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 lists what the filings include (form, date, accession number, EDGAR link). All parameters are explained in detail, and the tool's scope is fully captured. No gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema description coverage, the baseline is 3, but the description adds significant meaning: explains CIK format, name resolution with similarity scores, date range behavior, and concurrency rate limit context. This goes well beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool tracks institutional managers by CIK or name and retrieves their 13F-HR filings with specific details. It uses specific verbs like 'track' and 'get', and distinguishes from siblings by focusing on 13F filings, which are distinct from general SEC filings like those from 'sec-edgar-watcher'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides guidance on data source (official SEC, free, no API key) and pricing, implying when to use this tool (for 13F data without authentication). However, it does not explicitly compare to sibling tools or state when not to use it, missing some exclusionary guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 (DexScreener public API), cost ($0.01/call via x402), and a disclaimer. However, it does not mention rate limits, error handling, pagination, or behavior when tokens are not found. The output format is partially described but not fully.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences long, directly front-loading the core purpose. Every sentence adds value: the first sentence states functionality, the second adds technical context (API, no key) and cost. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description lists returned fields but does not explain how filtering parameters (maxAgeHours, minLiquidityUsd) affect results or the output structure (e.g., single vs. multiple pairs per token). Given there is no output schema and moderate tool complexity, the description 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.

Does 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 new parameter-level meanings; it only summarizes the tool's output. The schema already describes each parameter adequately, so the description offers no additional semantic value for parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool looks up token contract addresses or tickers across DEXes and returns liquidity, 24h volume, pair age, quality score, and risk flags. This is a specific verb+resource combination, and it distinguishes itself from sibling tools like rug-pull-scorer or live-price-oracle by offering a bundled data set.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions ease of use ('No key, no wallet, no on-chain node') but provides no explicit guidance on when to prefer this tool over alternatives, nor any conditions for use or exclusions. It does not reference sibling tools or explain trade-offs.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 use of a user-provided Etherscan API key, rate limits via maxConcurrency, and that the score is heuristic. It does not mention any destructive actions, which 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, concise and front-loaded. Every sentence adds essential information about purpose, usage, and limitations. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 4 parameters fully described in schema, the description adds operational context (BYOK, cost, heuristic nature). No output schema exists, but the description explains the score range. Sufficient for a straightforward scoring tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does 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: explains keyless Blockscout vs BYOK, chains supported, and the purpose of maxConcurrency. This adds value beyond the schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool profiles a wallet on-chain and produces a 0-100 airdrop-farming readiness score. It is specific and distinct from sibling tools, which cover unrelated domains like job postings or clinical trials.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions BYOK Etherscan (your key, your quota), notes the score is a heuristic and not a guarantee, and states the cost ($0.01/call). While it doesn't explicitly say when to use vs alternatives, the context makes the purpose clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It clearly states the tool is read-only (no RPC, wallet-connect, browser) and provides output details (balance, flagged transfers, token activity). It also explains the pricing model and optional API key usage, adding 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two sentences and a pricing note. It is front-loaded with the core purpose and key features, 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.

Given 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 hints at the return structure (one row per wallet with balance, flagged transfers, token activity). It also covers prerequisites (Etherscan key optional), rate limit considerations (maxConcurrency), and pricing, making it sufficiently 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.

Does 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 does not add new semantics beyond what the schema provides, meeting the baseline expectation. No extra value is added for parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool tracks large ETH and ERC-20 movements for wallet addresses via Etherscan API. It distinguishes itself from sibling tools like wallet-airdrop-profile and rug-pull-scorer by focusing on transaction tracking and balance retrieval.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when a simple API-based tracking is needed (no RPC, wallet-connect, or browser) and mentions pricing. However, it does not explicitly state when not to use this tool or suggest alternatives among siblings, 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.

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 'No login, no browser, no proxies' and the cost, which are useful. However, it does not address rate limits, data return structure, or limitations beyond Vienna. The schema covers some constraints (e.g., city slug), but the description 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise – a single sentence covering purpose, source, location, ease of use, and cost. Every part adds value, no filler. The critical information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (4 parameters, no output schema), the description covers the core purpose and some behavioral traits. However, it omits details about pagination, data fields returned, and the fact that only 'wien' is guaranteed to work. The schema descriptions fill some gaps, but the overall context is moderately complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does 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 tool description adds no additional parameter-specific information beyond what is already in the schema. It mentions 'apartment rental and sale listings' which aligns with deal_type, but the schema already details this.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('pull'), the resource ('live apartment rental and sale listings'), and the source ('Willhaben.at for Vienna'). It distinguishes from sibling tools by specifying the geographic location, and the tool name reinforces this. The description 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.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for Vienna real estate listings, but it does not explicitly state when to use this tool over siblings (e.g., emlakjet-istanbul, otodom-warsaw). No alternatives or exclusions are mentioned, so the guidance is limited to implicit context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description honestly discloses that a meaningful share of jobs may be withdrawn (HTTP 410) and that extra candidates are attempted to compensate. It also notes that the 'freshness_days' parameter rarely filters due to sitemap freshness. Since no annotations are provided, the description carries the full burden and does well, though it lacks mention of rate limits or potential blocking.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences plus a cost note, front-loaded with the core purpose. It is efficient but includes the cost/payment line which, while relevant, adds slight noise. Overall, no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 5 parameters, all described in schema and enhanced in description. The returned fields are listed (title, company, location, etc.) despite no output schema. The description explains compensation for churn and the rarity of freshness filtering. Missing: guidance on error handling or empty results, but sufficient for a scraper tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema coverage, the description adds significant context: explains that 'max_items' is a target due to churn compensation, that 'keyword_filter' is applied client-side (no server-side search), and that 'fetch_full_description' incurs no extra requests. This far exceeds minimal schema documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool walks xing.com's job sitemap and pulls public job listings from the DACH region, specifying the data fields (title, company, location, etc.). It effectively distinguishes this tool from sibling tools like 'jobs-ch-swiss' or 'job-postings-aggregator' by focusing on a specific platform and region.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions the geographic scope (Germany/Austria/Switzerland) and cost, but does not provide explicit guidance on when to use this tool versus alternatives like 'jobs-ch-swiss' (which covers Switzerland) or 'job-postings-aggregator'. No when-not-to-use indications 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.