Openverse

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

Annotations declare readOnlyHint=true, and the description confirms it is a read-only query tool that returns structured answers with citations. Discloses the routing behavior and output format, with no contradictions.

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

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

The description is thorough but well-structured, starting with a clear instruction and followed by a comprehensive list of use cases. It is not overly verbose and each 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 the tool's complexity (1,423+ tools, 392 sources), the description provides sufficient context about what it does and what it returns. The lack of output schema is compensated by explaining the return format (structured answer with citations).

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% for the single 'question' parameter. The description does not add extra meaning beyond the schema's 'Your question or request in natural language', 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?

The description clearly states it is a general-purpose query router for factual data, with specific verb 'routes the question' and resource '1,423+ tools across 392+ verified sources'. It distinguishes from siblings like web search by stating 'PREFER OVER WEB SEARCH'.

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: for factual questions about specific domains (SEC, FDA, FRED, etc.). Gives examples and a list of trigger phrases ('what is', 'look up', etc.). Clearly advises preference over web search, providing usage boundaries.

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 only repeats the read-only nature already indicated by annotations, adding no new behavioral context such as what kind of related audio is returned or any limitations.

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

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

The description is a single concise sentence with no wasted words. However, it may be overly brief, sacrificing completeness for brevity.

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 lack of output schema, no parameter descriptions, and minimal context, the description fails to fully inform an agent about what the tool returns and when to use it.

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 only confirms 'id' is an audio ID, but provides no format, constraints, or additional 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 clearly states it retrieves related audio for a given audio ID. It is specific with a verb and resource, distinguishing it from sibling tools like 'get_audio' or 'search_audio', but lacks detail on the nature of the relation.

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 'search_audio' or 'get_audio'. There is no mention of context, prerequisites, or exclusions.

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

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

Annotations indicate readOnlyHint=true, which is consistent with a comparison tool. Description details data sources (SEC EDGAR/XBRL for companies, FAERS/FDA for drugs) and return format (paired data + citation URIs).

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?

Single paragraph, front-loaded with purpose and usage triggers. Could be broken into multiple sentences for clarity, but no redundant 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?

Despite no output schema, description sufficiently explains return data and behavior. Covers all necessary aspects for an agent to decide and invoke the tool 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?

Input schema covers 100% of parameters with descriptions and enums. Description adds value by explaining parameter usage with examples (e.g., tickers for company, drug names).

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 compares 2-5 companies or drugs side by side, with specific data pulled for each type. It distinguishes from siblings by noting it replaces multiple sequential calls.

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 lists example user queries that trigger this tool (compare X and Y, vs, stack up). Provides clear usage context, though could include explicit when-not-to-use statements.

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, so the description only needs to add behavioral context. It discloses that the tool returns 'top-N most relevant tools with names + descriptions', which goes beyond the annotation. There is no contradiction, and the description aligns with the read-only nature.

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

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

The description is front-loaded with the core purpose and usage instruction. It includes a list of examples that, while helpful, add some verbosity. Overall, it is efficient and well-structured without unnecessary repetition.

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 (query and limit parameters, no output schema), the description adequately covers behavior: it returns top-N relevant tool names and descriptions. It does not detail the ranking algorithm, but that is acceptable for a discovery tool. The description is complete enough for an agent to understand input and output.

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% (both query and limit are described in the schema). The description does not add meaning beyond what the schema already provides; it merely rephrases the purpose and mentions 'top-N', which is implied by the schema description of limit. 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 identifies the tool's purpose: 'Find tools by describing the data or task.' It lists specific domains (SEC filings, FDA drugs, etc.) and explicitly contrasts with other tools by saying 'Call this FIRST when you have many tools available' – distinguishing it from sibling tools that perform direct operations.

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 tells when to use the tool ('when you need to browse, search, look up, or discover') and advises to call it first when exploring multiple tools. It does not explicitly state when not to use it or provide direct alternatives, but the context is clear.

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

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

Annotations have readOnlyHint=true, consistent with a read operation. Description adds detail about return contents (SEC filings, financials, patents, etc.) and citation URIs, going 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?

Two sentences with clear front-loading of purpose. The second sentence is somewhat long but efficiently lists return types. 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?

Despite no output schema, description thoroughly covers return contents (SEC filings, fundamentals, patents, news, LEI) and input constraints. Adequate for a complex 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 has 100% coverage, so baseline is 3. Description adds value by explaining enum options (only 'company'), value format (ticker or CIK), and guidance on name resolution, making it more helpful.

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 states 'Get everything about a company in one call' and provides clear example use cases like 'tell me about X', distinguishing it from siblings like resolve_entity and compare_entities.

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 says when to use (user asks for company profile) and when not to (pass names directly—use resolve_entity first). Also lists what it returns, providing clear 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 aligns with annotations (readOnlyHint=false) and clarifies the destructive action. It adds context about clearing sensitive data, though it does not mention error handling or reversibility.

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 action, no unnecessary words. Highly 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?

For a simple, single-parameter deletion tool with no output schema, the description adequately covers purpose and usage. Could mention return behavior, but not critical given low 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 coverage is 100% and the description merely restates the schema's parameter description ('by key'). No additional semantic value beyond what the schema already provides.

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

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

The description clearly states the action 'Delete a previously stored memory by key.' The verb and resource are specific, and it distinguishes itself from sibling tools like 'remember' and 'recall'.

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 provides when to use the tool: when context is stale, task is done, or to clear sensitive data. Also suggests pairing with 'remember' and 'recall', offering clear guidance on 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 declare readOnlyHint=true, covering safety. The description adds no behavioral context beyond a terse statement. No mention of side effects, performance, or data returned, which limits transparency.

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

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

The description is very concise at four words and is front-loaded. However, it is a noun phrase without a verb. A slight expansion (e.g., adding 'Retrieves') would improve clarity without bloat.

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 get-by-id with one parameter and no output schema, the description is minimally adequate. However, it does not mention what the return contains (e.g., full record metadata) or error conditions, leaving gaps in 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?

The id parameter has no description in the input schema (0% coverage). The description mentions 'by id' but does not describe the format, source, or expected values, failing to compensate for the schema gap.

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 states 'Single audio record by id' which clearly identifies the tool's action (get) and resource (audio record) using an identifier. It distinguishes from sibling tools like search_audio. However, it lacks a verb, making it slightly less explicit than ideal.

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 such as search_audio. The description does not provide context for when a user would have an id or how to obtain one, leaving the agent without usage boundaries.

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, so the description does not need to restate it, but it adds no behavioral traits beyond that. For example, it doesn't mention error handling, return format, or what happens if the id is not found.

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

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

The description is very concise (one sentence), but it sacrifices necessary details such as parameter semantics and usage context. It is front-loaded but insufficiently 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?

Given the low complexity (1 param, no output schema), the description should fully cover what the tool does, but it omits the return value and parameter details, making it incomplete.

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 one parameter 'id' with 0% description coverage in the schema, and the description does not explain what the 'id' represents or its format. The description adds no semantic 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 it returns a single image record by id, which is specific and distinguishes it from sibling tools like search_images that search multiple records. However, it does not explicitly differentiate from other single-record retrieval 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?

The description provides no guidance on when to use this tool versus alternatives, nor any context about prerequisites or limitations.

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

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

Annotations set readOnlyHint: true, which the description does not contradict. However, the description adds no behavioral details beyond that, such as what 'related' means or the nature of the output. With annotations covering the safety profile, a score of 2 reflects the lack of additional 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 very concise at one sentence, but it omits important details like output structure or parameter explanation. It is not verbose, yet the terseness sacrifices completeness. It is adequate but not exemplary.

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 an annotation indicating read-only, the description minimally covers the purpose. However, it lacks information about the return format (e.g., list of image IDs or URLs) and any pagination or ordering. It is sufficient for a basic understanding 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?

The schema has 0% description coverage and only one parameter 'id' of type string. The description does not explain what 'id' represents (e.g., an image ID) or any constraints (e.g., format, required). It relies entirely on the parameter name, providing no added semantic 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 phrase 'Related images for a given image id' clearly indicates the tool retrieves related images for an image ID. It implicitly distinguishes from sibling tools like 'get_image' (single image) and 'search_images' (search). However, it does not explicitly state the action verb (e.g., 'Retrieve'), slightly reducing clarity.

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

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 such as 'search_images' or 'audio_related'. There is no mention of context, prerequisites, or when not to use it.

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

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

The description discloses behavioral traits such as being rate-limited (5 per identifier per day), free, and not counting against quota. It also notes that the team reads digests daily and feedback affects roadmap. Annotations only provide readOnlyHint=false, so the description adds significant context 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 appropriately structured, front-loading the core purpose and then providing detailed guidance. It is somewhat long but every sentence adds value, making it efficient for the complexity of the tool.

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 parameters, 2 required, nested objects, no output schema), the description adequately covers purpose, usage, and behavioral traits. No missing information is evident for an AI 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 description coverage is 100%, so the baseline is 3. The description adds minimal additional meaning beyond the schema's property descriptions for 'type', 'context', and 'message'. While it reinforces the purpose, it does not significantly enhance 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: providing feedback to the Pipeworx team about bugs, missing features, data gaps, or praise. It uses specific verbs and resource terms, and distinguishes itself from sibling tools like 'ask_pipeworx' or 'discover_tools' which serve different purposes.

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

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

The description explicitly states when to use this tool (e.g., when a tool returns wrong data or is missing) and provides exclusions (e.g., 'don't paste the end-user's prompt'). It also mentions rate limits and that it doesn't count against the tool-call quota, offering clear 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 provide readOnlyHint=true. The description adds scoping details (anonymous IP, BYO key, account ID) and pairing context, which are useful beyond annotations. No contradictions.

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

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

Two sentences plus a note, each sentence earns its place. Front-loaded with the main action. 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?

Lacking output schema, the description doesn't detail return format (e.g., type of value, structure of key list). However, the tool is simple and the description covers core usage and scoping. Pairing with siblings fills 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 description coverage is 100% (the type and description are in the schema). The description reinforces that omitting key lists all keys, but adds no new parameter-specific semantics beyond what's in 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 retrieves a saved value or lists keys, using specific verbs ('retrieve', 'list') and resource ('value previously saved'). It distinguishes from sibling tools 'remember' 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?

The description explains when to use (look up stored context without re-deriving) and mentions pairing with remember/forget. It lacks explicit 'when not to use', but the context is clear enough.

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

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

Describes parallel fan-out to SEC EDGAR, GDELT, and USPTO, and return structure (changes, count, URIs). Annotations already indicate read-only, so no contradiction. Missing mentions of rate limits or scope 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?

Single paragraph front-loaded with purpose. Some redundancy (e.g., repeating example queries), but overall concise. Could trim slightly without loss.

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?

Complete description for a read-only monitoring tool: covers sources, parameters, return structure, and output format. No output schema, but description compensates with return details.

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?

Adds value beyond schema by explaining 'since' format (ISO vs relative shorthand) and value types (ticker or CIK). Schema coverage is 100%, so baseline is 3; the extra examples and guidance push it to 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?

Description clearly states 'What's new with a company in the last N days/months?' and provides specific example queries. It distinguishes from siblings like entity_profile by focusing on temporal changes across multiple sources.

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 lists when to use with example user queries. Does not mention when not to use or alternatives, but the context is clear enough for an agent to decide.

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

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

The description discloses key behavioral traits beyond annotations: persistence behavior ('authenticated users get persistent memory; anonymous sessions retain memory for 24 hours'), scoping by identifier, and pairing with recall/forget. No contradiction with readOnlyHint=false.

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 four sentences, each serving a purpose: core action, usage examples, storage details, and tool pairing. It is front-loaded but could be slightly more terse.

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 moderate complexity (2 required params, no output schema), the description covers purpose, usage, persistence, and siblings. It lacks return value details, but no output schema exists 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?

Schema coverage is 100%, so baseline is 3. The description adds extra context with naming conventions for keys and value types, exceeding basic schema info.

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: 'Save data the agent will need to reuse later' and distinguishes it from siblings like recall and forget by explicitly mentioning 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 provides clear usage scenarios (e.g., 'discover something worth carrying forward') and hints at alternatives (recall, forget). However, it does not explicitly state when not to use the tool.

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

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

Annotations declare readOnlyHint true. Description adds that tool returns IDs plus pipeworx:// citation URIs and replaces multiple calls, providing behavioral context beyond the annotation.

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 concise sentences front-loaded with purpose, followed by usage guidance, examples, and a efficiency claim. No superfluous wording.

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 2-param tool with no output schema, description sufficiently explains return values (IDs + URIs), gives examples, and states usage order, making it complete for an agent to invoke correctly.

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

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

Input schema has 100% coverage with descriptions. Description adds value by explaining the type enum and value formats with concrete examples, enhancing the schema's 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?

Description clearly states the tool resolves names to canonical identifiers, with specific ID systems (CIK, ticker, RxCUI, LEI) and examples. It distinguishes from siblings like 'entity_profile' and 'compare_entities' by focusing on identifier lookup.

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 before other tools needing official identifiers. Examples show when to use, but no explicit when-not-to conditions are given.

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. The description adds the 'Creative-Commons-licensed' scope but does not disclose pagination behavior, default result count, or any side effects. It is consistent 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?

Single sentence, front-loaded with verb and resource, minimal waste. However, it could be improved by adding a brief usage note without much expansion.

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 six parameters, no output schema, and only a readOnlyHint annotation, the description is insufficient. It does not explain the purpose of each parameter or the return format, leaving significant 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 description coverage is 0%, and the description provides no explanation for any of the six parameters (e.g., 'query', 'source', 'license'). The agent must rely on parameter names alone.

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') and the resource ('Creative-Commons-licensed audio'), distinguishing it from sibling tools like 'get_audio' which likely retrieves specific audio files.

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 such as 'get_audio' or 'audio_related'. The agent must infer usage from context.

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

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

Annotations already declare readOnlyHint=true, and the description aligns by indicating a search (read) operation. However, the description adds no additional behavioral context 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?

The description is a single, concise sentence that is front-loaded with the key action and resource. 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?

With no output schema and 7 parameters, the description is too brief. It does not cover return format, pagination, or parameter details, leaving the agent with significant 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 description coverage is 71%, which is moderately high. The description does not add any parameter semantics beyond the schema, but the schema itself documents most parameters. Baseline 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 it searches for Creative-Commons-licensed images, which is a specific verb+resource. It distinguishes from sibling tools like 'search_audio' and 'get_image', but could elaborate more on the scope of search.

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

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 'search_audio' or 'get_image'. The description lacks any when-to-use or when-not-to-use context.

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

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

Annotations already mark the tool as read-only (readOnlyHint: true). The description adds behavioral context: it returns a structured verdict, actual value with citation, and a percent delta. It also notes that this is a v1 implementation with domain limitations and that it consolidates multiple internal operations (NL parsing, entity resolution, lookup, comparison), which is useful for the agent's expectation management.

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: starts with purpose, then usage guidance, then domain/version, then return values, then efficiency benefit. It is concise with no redundant information, though it could be slightly tightened by removing the efficiency claim if unnecessary.

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 and no output schema, the description provides sufficient context: input format, domain limitations, output structure, and performance characteristics. It is complete for an agent to understand when and how to use it, though more detail on the verdict enum values might further enhance 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?

The only parameter 'claim' has a schema description that explains it expects natural-language factual claims and provides examples. The tool description further elaborates on the type of claims (company-financial) and the format, adding value beyond the schema. Since schema coverage is 100%, baseline is 3, but the description's supplementary details and constraints warrant a 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 clearly states the tool is for fact-checking factual claims, specifically financial claims for public US companies. It uses strong verbs ('fact-check', 'verify', 'validate', 'confirm/refute') and specifies the exact resource type. It distinguishes itself from sibling tools by highlighting its specialized domain and efficiency improvements over sequential calls.

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 instructs when to use: 'Use when an agent needs to check whether something a user said is true', with examples like 'Is it true that…?'. It also defines the scope ('v1 supports company-financial claims') and indicates it replaces multiple steps, implicitly guiding the agent away from piecing together separate calls.

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