Cryptocompare

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

Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds no further behavioral context (e.g., no info on rate limits, data completeness, or response format). With annotations present, the description adds negligible value beyond them.

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?

Extremely concise (two words), which is acceptable for a parameterless tool. However, could be slightly expanded for clarity (e.g., 'Returns a list of all supported coins'). Adequate but not optimally informative.

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 list tool with no output schema, the description is minimally complete. However, it does not describe the structure of returned data (e.g., coin IDs, names), which leaves the agent guessing 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?

The input schema has no parameters (0 params), so the baseline is 4. The description adds nothing about parameters, but none are needed.

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 'Full coin list' clearly indicates the tool returns all coins. It distinguishes from siblings like 'top_market_cap' and 'top_pairs' by implying a comprehensive, unfiltered list, but does not explicitly contrast them.

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

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 alternatives. The agent must infer that 'full' means unconstrained, but no explicit when-to-use or when-not-to-use instructions 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?

Annotations already declare readOnly=true, destructiveHint=false, openWorldHint=true. The description adds no behavioral context beyond what annotations provide, which is adequate but not additive.

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?

Extremely concise at two words, but it is a phrase rather than a complete sentence. Still communicates purpose efficiently without waste.

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 and minimal description, the tool's return type or structure is not hinted. A simple list could be interpretable, but more context would help, especially for an open-world 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?

No parameters exist in the input schema. The description does not need to explain parameters, and the baseline score for 0 params is 4.

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 'Exchange list' clearly indicates the tool returns a list of exchanges, but lacks a verb or explanation of scope. It distinguishes from sibling 'all_coins' but not from other list-oriented tools.

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 alternatives. Context signals show many sibling tools, but the description offers no selection criteria 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?

The description complements the annotations (readOnlyHint, openWorldHint, destructiveHint) by explaining that the tool routes questions to other tools, fills arguments, and returns structured answers with stable citation URIs. It discloses the behavior without contradiction.

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 comprehensive but could be slightly more concise. It front-loads the key directive ('PREFER OVER WEB SEARCH'), provides rationale, usage cues, and examples in a well-structured manner. Every sentence adds value, though some repetition exists.

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 role as a meta-routing tool with a single parameter, the description adequately explains its behavior, output format (structured data with citations), and supported domains. No output schema is provided, which is acceptable as the description clarifies what to expect. Minor gaps remain regarding error handling or unsupported queries.

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 schema already provides 100% coverage for the single 'question' parameter, so the description adds minimal extra semantics. It does not specify any additional constraints or formatting requirements beyond natural language. A score of 3 is appropriate as the description provides context but no deeper parameter details.

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 answers factual questions about real-world entities using authoritative structured data. It distinguishes itself from sibling tools by explicitly saying 'PREFER OVER WEB SEARCH' and explaining that it routes to thousands of tools. The purpose is specific and actionable.

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

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

The description provides explicit guidance on when to use this tool (for factual questions about current or historical data, regarding SEC filings, FDA data, etc.) and when not to (implicitly, as an alternative to web search). It gives concrete examples of questions and specific 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?

Annotations (readOnlyHint, openWorldHint) already indicate safe, non-destructive behavior. The description adds behavioral context: it resolves the market, classifies the bet, fans out to data packs, and returns an evidence packet with comparison. This goes beyond annotations without contradicting them.

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 of about 4 sentences. It is front-loaded with the core action and use cases, making it efficient. Minor redundancy could be trimmed, but overall it is concise and well-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?

The description explains the tool's function and output at a high level, but lacks details on the evidence packet's format or structure. Given no output schema, agents might need more specifics to interpret results. The description is adequate but not exhaustive for a complex fan-out 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?

Input schema has 100% description coverage, baseline is 3. The description adds high-level context about fan-out but does not elaborate on parameters beyond what the schema already provides (e.g., 'market' and 'depth' are well-described in the schema). Minimal added value 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's purpose: researching Polymarket bets by pulling relevant Pipeworx data in one call. It specifies inputs (slug, URL, question text) and outputs (evidence packet + comparison). It distinguishes from sibling tools by being a one-stop shop for bet research, while siblings are individual data fetchers.

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 lists use cases ('should I bet on X?', 'what does the data say?', 'is there edge?'), which helps agents decide when to use it. However, it does not mention when NOT to use it or suggest alternative tools for specific needs, missing some guidance for exclusion.

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?

Annotations already indicate readOnlyHint, openWorldHint, and destructiveHint. The description adds context: it returns 'paired data + pipeworx:// citation URIs' and mentions it replaces 8–15 sequential calls. This goes beyond annotations without contradiction.

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 paragraph with a clear front-loaded purpose: 'Compare 2-5 companies side by side'. Every sentence adds value—use cases, data sources, return format, efficiency claim. 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?

Without an output schema, the description covers return format ('paired data + citation URIs') and data sources for both types. It could detail the structure of paired data more, but given the tool's broad scope and the clarity of use, it is sufficiently complete for an agent.

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 both parameters. The description enriches by specifying that 'type=company' pulls financial data from SEC EDGAR and 'type=drug' pulls adverse events etc. It also clarifies the format for 'values' (tickers/CIKs for company, drug names for drug), adding value 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 compares 2–5 companies or drugs side by side, with specific use cases like 'compare X and Y' or 'X vs Y'. It distinguishes from sibling tools like entity_profile by focusing on side-by-side comparison rather than individual profiles.

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 explicit when-to-use patterns (e.g., 'compare X and Y', 'how do X, Y, Z stack up') and explains the data pulled for each type. It lacks explicit 'when not to use' or alternative tools, but the context is clear enough for an AI agent to decide.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false, establishing safety. The description adds value by disclosing that the tool returns a list of relevant tools with names and descriptions, and that it should be called first for discovery. This complements the annotations without contradiction.

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 just two sentences, both front-loaded with key information. The first sentence states the core purpose, and the second provides context and examples. No 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?

Given the tool's simplicity (search/discovery), the description adequately covers its behavior: it returns top-N tools based on a query. Annotations cover safety. No output schema is needed as the tool's output is self-explanatory. The description is complete for its context.

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 both parameters (query, limit). The description adds the default and max for limit (20, max 50), which is helpful but does not significantly extend beyond the schema. Parameter semantics are adequate but not enriched beyond schema baseline.

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 'Find tools by describing the data or task' and lists numerous example domains such as SEC filings, financials, FDA drugs, etc. It also specifies that it returns the top-N most relevant tools with names and descriptions, which distinguishes it from sibling tools that are domain-specific.

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 advises to use this tool when needing to browse or discover tools, and instructs to call it FIRST when many tools are available. This provides clear when-to-use guidance and contrasts with alternatives (sibling tools) that are more specific.

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?

Annotations already declare read-only and non-destructive. The description adds valuable context: returns pipeworx:// citation URIs and lists specific data sources (SEC, USPTO, etc.). It covers what the tool returns, though could mention data freshness or rate limits. No contradiction with annotations.

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

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

The description is well-structured: purpose first, then usage triggers, then output summary, then parameter details. Every sentence adds value. No 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 description covers the tool's inputs, outputs, and use cases comprehensively for an aggregator tool with no output schema. It lists the main data categories. Missing details like whether data is real-time or historical, but overall complete for the complexity level.

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% but description adds critical nuance: explains that 'type' only supports 'company' for now, and that 'value' must be ticker or CIK, not names, with a reference to resolve_entity. This goes 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 purpose as an aggregator for all company data in one call, listing specific data categories. It distinguishes itself from siblings by explicitly stating it replaces calling 10+ pack tools. The verb 'Get' and resource 'everything about a company' are specific and unambiguous.

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

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

The description provides explicit usage examples (user queries like 'tell me about X') and clear input instructions (ticker or CIK). It also tells when not to use (if only a name, resolve first). This fully guides the agent on appropriate invocation.

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?

Annotations already include destructiveHint=true, so the description's mention of deletion adds minimal extra value. No additional behavioral details are provided beyond what annotations cover.

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?

Very concise: two sentences covering action, usage context, and relationship to siblings. No redundant 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?

For a simple tool with one parameter and no output schema, the description fully covers purpose, when to use, and how it interacts with sibling tools. No gaps remain.

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%, and the description mentions 'by key' which aligns with the required parameter. However, it does not add new meaning beyond the schema's description of the key.

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 'Delete a previously stored memory by key,' providing a specific verb and resource. It distinguishes itself from sibling tools 'remember' and 'recall' through context.

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?

Explicitly states when to use: 'when context is stale, the task is done, or you want to clear sensitive data.' Also advises pairing with 'remember' and 'recall,' guiding appropriate usage.

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?

Annotations already indicate readOnlyHint=true, openWorldHint=true, and destructiveHint=false. The description adds no behavioral context beyond this. It does not contradict annotations.

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

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

The description is extremely concise but under-specified. It lacks necessary detail for an agent to understand the tool's purpose and usage.

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 6 parameters, no output schema, and no parameter descriptions, the description is woefully incomplete. It provides no guidance on input requirements or 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?

Schema description coverage is 0%, and the description does not explain any of the 6 parameters (e.g., fsym, tsym, limit). The description fails to add meaning 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 'Daily OHLC' implies the tool retrieves daily open-high-low-close data, which is specific. However, it lacks a verb like 'get' or 'retrieve' and does not differentiate from sibling tools like 'histo_hour' and 'histo_minute'.

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?

There is no guidance on when to use this tool versus alternatives. No mention of prerequisites, exclusions, or context for usage.

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?

Annotations already mark the tool as read-only and non-destructive. The description adds no behavioral context beyond what annotations provide, such as potential data volume or response format.

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

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

The description is extremely concise but at the expense of completeness. While short, it lacks important structural elements like parameter details or usage context.

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 6 parameters, no output schema, and minimal annotations, the description is severely incomplete. It fails to provide enough context for an agent to correctly invoke the 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 0% and the description provides no explanation for any of the 6 parameters (e.g., fsym, tsym, e, toTs, limit, aggregate). The agent gets no parameter semantics from the description.

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 'Hourly OHLC' states the tool provides hourly open-high-low-close data, which is clear but merely restates the tool name. It does not differentiate from sibling tools like histo_day or histo_minute.

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 alternatives like histo_minute or histo_day. No mention of 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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description adds no additional behavioral context such as data source, rate limits, or authentication needs, though it does not contradict annotations.

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

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

The description is extremely short but under-specified; it lacks necessary detail for a tool with 6 parameters, so brevity here is conciseness at the cost of completeness.

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 6 parameters, no output schema, and 0% schema description coverage, the one-word description is wholly inadequate; it does not explain return values, parameter usage, or how it fits with sibling tools.

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 0% schema description coverage, the description must compensate but only says 'Minute OHLC', providing no explanation of parameters like e, toTs, limit, or aggregate, leaving their semantics entirely unclear.

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 'Minute OHLC' indicates it provides minute-level open, high, low, close data, but it is essentially a restatement of the tool name and does not differentiate it from sibling tools like histo_day or histo_hour, making it somewhat vague.

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; there is no mention of contexts or exclusions, leaving the agent without direction on selection.

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?

Annotations already provide readOnlyHint=true, openWorldHint=true, and destructiveHint=false. Description adds no behavioral context beyond a generic label, failing to explain output format, filtering behavior, or response structure.

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

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

Extremely short but underspecified; not true conciseness. Every sentence should add value, but here the only sentence adds none.

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 6 parameters, no output schema, and siblings providing more specific options, the description is completely inadequate. Should explain return structure, filtering, and usage context.

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 0%, and description provides zero details on any of the 6 parameters. The agent gets no help understanding what lTs, lang, feeds, etc., do.

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 'News feed.' is a tautology, restating the tool name without specifying the action (list, search, etc.). It fails to distinguish from sibling tools like news_categories and news_feeds.

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 siblings. Lacks context for when it is appropriate or 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?

Annotations already indicate readOnlyHint=true and destructiveHint=false, so the description adds no behavioral context. It does not mention any specific outcomes, side effects, or constraints beyond what annotations imply.

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 only two words, which is not conciseness but under-specification. It lacks any informative content, making it unhelpful for an AI agent.

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 and no parameters, the description should fully explain the tool's purpose and output. It fails to do so, providing no actionable information about what 'news categories' means or how to interpret the result.

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 zero parameters, the baseline is 4, but the description fails to add meaning about what the tool returns. It does not explain how results are structured, filtered, or categorized, leaving the agent guessing about output semantics.

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 'News categories' is a noun phrase without a verb, leaving the tool's action unclear. It fails to specify whether it lists, retrieves, or manages categories, and does not distinguish it from sibling tools like 'news' or 'news_feeds'.

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. There are no hints about typical use cases or exclusions, leaving the agent without context for selection.

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

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

Annotations indicate readOnlyHint=true and destructiveHint=false, but description adds no behavioral context (e.g., what data is returned, scope). Relies entirely on 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?

Extremely concise but lacks structure and substantial content. Could be longer without being verbose.

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 and no parameters, the description should clarify the tool's purpose and return values. 'News feeds' is insufficient for an agent to decide usage.

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?

No parameters, so schema coverage is 100%. With zero params, description need not add meaning; baseline 4 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?

Description 'News feeds.' merely restates the tool name without specifying actions (e.g., list, fetch). Among siblings like 'news' and 'news_categories', it provides no distinction.

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 alternatives like 'news' or 'news_categories'. Agent cannot determine appropriate 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?

Beyond annotations (readOnlyHint=false, destructiveHint=false), the description reveals rate limits (5 per identifier per day), that feedback is free and doesn't count against tool-call quota, and that the team reads digests daily. This adds significant 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?

The description is concise yet comprehensive, using five sentences to cover purpose, usage, constraints, and behavior. Front-loaded with the core action, each sentence 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?

Given the tool's simplicity (3 params, no output schema), the description is complete: it covers all use cases, parameter hints, rate limits, and behavioral implications. No additional context is necessary for proper usage.

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% and descriptions are detailed, but the tool description adds value by specifying typical message length (1-2 sentences, 2000 char max) and reinforcing the context structure. This exceeds the baseline 3 for high-coverage schemas.

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: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It enumerates specific categories (bug, feature/data_gap, praise) and distinguishes itself from sibling tools (e.g., price, news) by focusing on feedback rather than data 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 provides explicit when-to-use guidance: for bugs (wrong/stale data), feature/data gaps, or praise. It also warns against including end-user prompts, offering clear instructions. Alternatives are implied (e.g., using discovery or ask tools for other intents).

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?

Annotations already indicate a read-only, non-destructive, open-world tool. The description adds significant behavioral context: it performs web searches, groups related markets, checks monotonicity, and returns ranked opportunities with reasoning. This aligns with and enriches the annotation hints.

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 fairly long but well-structured with bolded mode names and clear examples. Every sentence adds value, though a slight reduction in length could improve conciseness without losing 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?

Given the absence of an output schema, the description adequately mentions the output format: 'ranked opportunities with suggested trade direction + reasoning'. It covers the main workflow (two modes, monotonicity check) but does not detail grouping logic or potential errors, which is acceptable for a moderate-complexity 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% and both parameters are described in the schema. The description further explains the two modes corresponding to each parameter, provides example values, and clarifies the difference between event and topic. This goes well beyond the schema's 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's purpose: finding arbitrage opportunities on Polymarket via monotonicity violations. It distinctly names two modes (event and topic) and explains how they differ, making it easy to distinguish from siblings like 'polymarket_edges'.

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 guidance on when to use each mode: event mode for a single Polymarket event slug, and topic mode for cross-event searches. It explains why topic mode catches cases that event mode misses. However, it does not explicitly state when not to use the tool or mention any prerequisites or limitations.

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

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

Description adds details beyond annotations: V1 scope, model (lognormal, FRED, coinpaprika), grouping, caching, and ranking logic. Annotations already declare read-only and non-destructive.

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?

Four sentences packed with useful detail. Front-loaded with purpose. Slightly verbose but not excessive.

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, description explains return structure and internal behavior well. Covers model, caching, ranking, and trade direction.

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 with defaults. Description repeats defaults but adds no new meaning. Schema coverage is 100%, so baseline 3 applies.

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 it scans top Polymarket markets, identifies discrepancies with Pipeworx data, and returns ranked edges with trade direction. Distinct from siblings like polymarket_arbitrage.

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?

Explicitly states it's for 'what should I bet on today' and discovers opportunities without manual paging. Does not specify when to avoid or compare with alternatives, but context 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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the tool is clearly a read operation. The description adds 'Current price' but does not disclose additional behavioral traits such as data freshness, rate limits, or response format. With annotations, the bar is lower, and the description provides minimal extra value.

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 short (11 words), which is concise but lacks structured information. It is front-loaded with the main purpose, but no further detail is provided, making it feel incomplete rather than efficiently concise.

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 moderate complexity (5 parameters, no output schema, no parameter descriptions), the description is not complete. It does not cover what the tool returns, how to use parameters, or any examples. The context signals highlight low coverage, and the description fails to compensate.

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 5 parameters with 0% description coverage. The description does not explain any parameter (e.g., fsym, tsyms, e, sign, extraParams), leaving the agent without guidance on their meaning or usage. The description's 'one coin → many fiat' hints at fsym and tsyms but is insufficient.

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 'Current price (one coin → many fiat)' clearly identifies the tool's function as retrieving a single cryptocurrency price converted to multiple fiat currencies. It distinguishes from siblings like price_multi and price_full by implying a one-to-many mapping, but lacks explicit mention of what data is returned.

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 usage guidance is provided. There is no indication of when to use this tool versus alternatives (e.g., price_multi, price_full), nor are there any prerequisites or filters mentioned.

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?

While annotations declare readOnlyHint=true and openWorldHint=true, the description adds no behavioral context beyond what is already in annotations. It does not explain what 'full snapshot' entails in terms of data scope or 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 only two words, which is overly terse. It sacrifices informativeness for brevity, making it under-specified rather than concise.

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 three parameters and no output schema, the description provides insufficient context. It fails to explain the return format, data scope, or how to use the tool effectively.

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 0%, and the description does not explain any parameter. Terms like 'fsyms' and 'tsyms' are left undefined, requiring the agent to infer meaning without support.

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 'Full snapshot' is vague and does not specify what the tool does. It fails to indicate that it likely provides cryptocurrency price data, and it does not distinguish itself from sibling tools like 'price' or 'price_multi'.

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 such as 'price' or 'histo_day'. The description lacks context for decision-making.

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

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

The description does not add any behavioral context beyond what annotations provide. It does not disclose rate limits, data source, or any side effects. However, it does not contradict the readOnlyHint and destructiveHint. Minimal value added.

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 short (3 words), which is concise but at the expense of clarity. It is too sparse to be truly useful. Front-loading is not applicable because there is almost no 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 5 parameters, no output schema, and many sibling tools, the description is severely incomplete. It fails to explain the return format, behavior for missing data, or error handling. The agent would lack sufficient information to use the tool effectively.

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 0% schema description coverage, the description must compensate for the missing parameter meanings. It only says 'many → many', which weakly implies that 'fsyms' and 'tsyms' accept multiple values, but it does not explain 'e', 'sign', or 'extraParams'. The agent would need to infer or guess parameter semantics.

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 'Current price (many → many)' hints at returning prices for multiple cryptocurrency pairs, but it's vague. It does not explicitly state that it retrieves current prices for multiple from-symbols to multiple to-symbols, leaving ambiguity. Compared to sibling 'price', it suggests a multi-to-multi operation but lacks clarity.

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 guidelines are provided on when to use this tool versus alternatives. Siblings like 'price' and 'price_full' are present but no differentiation is offered. An agent would have to guess the appropriate 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?

Annotations already indicate readOnly and non-destructive. The description adds useful behavioral details: dual behavior (retrieve vs list), scoping by identifier, and pairing with related tools.

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?

Three sentences, front-loaded with purpose, then usage, then context. Every sentence adds value with no redundancy.

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

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

Covers purpose, usage, scoping, and relationships. Minor gaps: no mention of error handling or format of returned list. Overall adequate for a simple retrieval tool.

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

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

Schema coverage is 100%. The description reinforces the schema explanation (omit key to list all) but adds no new semantic info 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 retrieves a value saved via remember or lists all saved keys. It distinguishes from sibling tools like remember and forget by explicitly pairing with them.

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 explains when to use recall (to look up stored context) and mentions scoping. It pairs with remember/forget but lacks explicit when-not scenarios or 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?

Annotations already indicate readOnly, openWorld, and non-destructive behavior. The description adds valuable details: it fans out to multiple external sources in parallel, returns structured changes with a count and citation URIs, and explains the since parameter formats. No contradictions with annotations.

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

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

The description is concise and front-loaded with the main purpose. It includes example queries which aid understanding but could be slightly tighter. Overall, every sentence adds value without being verbose.

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 (three required params, no output schema, multiple sources), the description is very complete. It explains the return format (structured changes, count, URIs), the sources used, and the since parameter flexibility. It fully informs an agent of what to expect.

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 schema already documents all three parameters. The description adds minimal extra meaning, such as example 'since' values ('30d') and clarifying that 'value' can be a ticker or CIK. This matches the schema descriptions, so it's adequate but not additive.

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: 'What's new with a company in the last N days/months?' It provides example queries and explains that it aggregates data from multiple sources (SEC, GDELT, USPTO). This distinguishes it from siblings like 'news' or 'entity_profile' which are more focused.

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 lists user queries that should trigger this tool, such as 'what's happening with X?' and 'any updates on Y?' It gives clear context for when to use it, but does not mention when not to use it or provide direct comparisons to 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?

Discloses scoping by identifier, persistence differences between authenticated and anonymous users (24h). Annotations already indicate non-readonly and non-destructive; description adds valuable context.

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

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

Four sentences covering purpose, usage, behavior, and pairing. Efficient but could be slightly tightened; 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?

Given 2 parameters and no output schema, description explains all necessary aspects: what to store, when, how it persists, and how it relates to siblings.

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 already describes key and value with examples; description reinforces with naming conventions and value types (findings, addresses, preferences). Adds extra 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?

Clearly states it saves data for later reuse with specific examples of what to store (tickers, addresses, preferences). Differentiates from siblings recall and forget.

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?

Explicitly tells when to use (when discovering something worth carrying forward) and how to pair with recall/forget.

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?

Annotations already indicate a non-destructive, read-only operation. The description adds value by explaining the return format (IDs plus pipeworx:// citation URIs) and noting that it replaces multiple calls, without contradicting 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?

The description is concise yet informative, front-loading the purpose, followed by examples and usage guidance. Every sentence contributes meaning, though the examples could be slightly trimmed without losing 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?

Given the tool's simplicity (two parameters, full schema coverage, no output schema), the description thoroughly covers purpose, usage, return type, and when to invoke it. It feels complete for an AI agent to correctly select and use this 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 descriptions cover 100% of parameters. The description enhances semantics by providing specific examples for 'value' (e.g., 'AAPL', '0000320193', 'ozempic') and clarifying the role of the 'type' parameter, adding practical context 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 purpose: 'Look up the canonical/official identifier for a company or drug.' It specifies the exact ID systems (CIK, ticker, RxCUI, LEI) and provides concrete examples, distinguishing this tool from siblings like entity_profile or compare_entities by focusing on identifier resolution.

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?

Explicitly advises to use this tool before others that need official identifiers ('Use this BEFORE calling other tools that need official identifiers'). It provides usage context and examples but does not explicitly state when not to use it or list alternatives beyond the implied replacement of multiple lookups.

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?

Annotations indicate readOnlyHint=true and destructiveHint=false, but the description adds no behavioral context (e.g., auth needs, rate limits, or data scope). With no output schema, more behavioral detail is expected.

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

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

Extremely terse (two words) but not functionally concise — it omits essential details and requires the agent to guess meaning. Under-specification is not conciseness.

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, no param descriptions, no usage context. The tool is completely underspecified for an agent to use correctly, especially given the complex domain of cryptocurrency data.

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 0% and the description does not explain the required coinId parameter (type number) or its purpose (e.g., which coin identifier is expected).

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 is "Social stats." which merely restates the tool name without any verb or specific resource, failing to convey what the tool does or what it retrieves.

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 alternatives like price, news, or top_market_cap. The description provides no context for selecting this tool.

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?

Annotations already indicate readOnlyHint=true and destructiveHint=false, so the description adds minimal behavioral context. It does not explain sorting order, data source, or any constraints beyond annotations, missing an opportunity to enrich 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 short but this is under-specification, not conciseness. It lacks necessary information and does not earn its place as a helpful summary.

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 3 parameters and no output schema, the description fails to explain that this tool likely returns a paginated list of top cryptocurrencies by market cap. It does not differentiate from siblings significantly, leaving agents without enough context to use it 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?

With 0% schema description coverage, the description fails to clarify the meaning of any parameters (page, tsym, limit). For example, 'tsym' is not explained, and no usage hints are 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 'Top by market cap' vaguely implies a ranking but lacks a clear verb (e.g., 'list' or 'get') and does not specify the resource (e.g., cryptocurrencies or coins). It is not a tautology but is too minimal to clearly convey purpose.

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 siblings like top_volume_full or top_pairs. No context provided for appropriate usage scenarios.

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?

Annotations provide readOnlyHint and openWorldHint, but description adds nothing about behavior (e.g., ordering criteria, data freshness). Fails to add value beyond 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?

Extremely short but not effective; under-specification leaves critical gaps. Not a model of conciseness because it fails to convey 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 2 parameters (1 required), no output schema, and numerous siblings, this description is grossly incomplete. Fails to equip agent for correct invocation.

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 0%, yet description omits any explanation of parameters (fsym, limit). Agent cannot infer their meaning or usage.

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 'Top trading pairs.' is vague, essentially restating the name without specifying what 'top' means (by volume? market cap?) or what resource is involved. Barely more than a tautology.

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 siblings like price, top_market_cap, etc. Missing context on use cases or prerequisites.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds no additional behavioral context, such as data source, filtering behavior, or pagination, beyond what annotations provide.

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?

Extremely brief (three words) but fails to convey useful information. Not concise in a meaningful way; it is underspecified.

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 three parameters and no output schema, yet the description provides no completeness. Essential details about what volume means and how to interpret results are missing.

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 0%, and the description does not explain any of the three parameters (page, tsym, limit). The agent must guess their roles.

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 'Top by volume' essentially restates the tool name without specifying the resource or action. It does not clarify what entity or dataset is being ranked, making it tautological and uninformative.

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 like top_market_cap or top_pairs. The description lacks context for selection.

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

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

Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds valuable behavioral context: it details the data sources (SEC EDGAR+XBRL), return types (verdict, delta, citation), and the efficiency gain over manual steps. No contradictions with annotations.

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

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

The description is a single, well-structured paragraph that front-loads the purpose and immediately provides usage context. Every sentence adds value, and there is no redundant or filler content.

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

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

Given the tool has only one parameter, no output schema, and comprehensive annotations, the description fully covers what to expect: supported claim types, sources, returned verdict list, and citation format. No gaps remain for an AI agent to interpret the tool's behavior.

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 schema description for 'claim' is already detailed (with examples), achieving 100% coverage. The overall description does not add new parameter-specific semantics beyond reinforcing that the claim should be factual and natural-language. 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's purpose: fact-checking natural-language claims against authoritative sources. It specifies the supported domain (company-financial claims via SEC EDGAR+XBRL) and distinguishes itself from siblings by noting it replaces multiple sequential calls, which is a unique integration benefit.

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 concrete examples of when to use the tool (e.g., 'Is it true that…?') and lists supported claim types. However, it does not explicitly state when not to use it or suggest alternatives for claims outside the financial domain, slightly reducing clarity.

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