apis-io

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

With no annotations, description should explain behaviors like idempotency or error states. It only states the basic action; lacks details on side effects or special cases.

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 at the expense of necessary detail. Could be improved without adding length by clarifying parameters 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 2 required params, no output schema, and no annotations, the description is insufficient. It omits critical information about parameter roles and expected outcomes.

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%. The description does not explain what 'id' or 'members' represent or their expected formats. The mention of 'slug or aid' is not linked to the parameters.

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

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

Description clearly states the action (add) and resource (providers/APIs to a list). It specifies input types (slug or aid) but does not differentiate from siblings like create_list or delete_list.

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. No context on prerequisites, such as needing an existing list or authentication.

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

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

No annotations are provided, so the description bears full burden. It outlines the return content (top matches per section with counts) and mentions the `limit` parameter. However, it lacks details on return structure, error behavior, or any side effects. For a read-only search, this is acceptable but not comprehensive.

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

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

Two concise sentences plus a brief note on `limit` and sibling usage. Every sentence adds value, front-loading the key purpose and guiding next steps. 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?

Given 12 parameters, no output schema, and no annotations, the description provides good context: federated overview, top matches per section, count, and filter options. It correctly directs to siblings for full lists. Could mention output format or error handling, but overall enough for an agent to use 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 42% (5/12 parameters have descriptions). The description adds context by listing filterable categories (tags, artifact types, industry, region, rating band) and clarifying `limit` is per section. However, it does not explain several parameters like `area`, `match`, `min_score`, `providers`, or `sort` beyond what the schema provides. More detail would compensate for low coverage.

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

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

Description clearly states the tool provides a federated overview of the APIs.io catalog, returning top matching APIs, providers, and tags with counts. It distinguishes from siblings like find_apis, find_providers, find_tags, get_api, and get_provider, which handle single-type listings and details.

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 marks itself as the starting point ('START HERE') and directs users to sibling tools for paging/sorting full lists (find_*) or single entities (get_*). This provides clear when-to-use and when-not-to-use guidance.

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

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

No annotations are provided, so the description must disclose behavioral traits. It only mentions 'Pro' hinting at premium access, but fails to explain auth requirements, data mutability, or any side effects.

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

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

The description is very short, but it sacrifices clarity for brevity. Critical information is missing, making it unhelpful despite its 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?

For a single-parameter tool with no output schema and no annotations, the description fails to explain input format, output structure, or any contextual details. It is severely 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?

Schema coverage is 0% for the only parameter 'slug'. The description does not explain what 'slug' represents (likely a company identifier) or provide any additional meaning.

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

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

The description states the tool identifies a company's weakest investment dimensions, but the verb is implied and the term 'investment dimensions' is vague. It does not clearly distinguish from sibling tools like 'gap_analysis' or 'industry_gap_analysis'.

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 sibling list includes many similar tools, but the description provides no 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?

With no annotations, the description carries the full burden. It mentions the output components but does not disclose behavioral traits such as authentication requirements, rate limits, or whether the tool is read-only. The 'PRO —' prefix hints at premium access but is not explicit.

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

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

The description is a single sentence that is front-loaded and efficient. It lists the output components clearly. The 'PRO —' prefix is slightly unnecessary but does not detract significantly.

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

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

Given no output schema, the description explains the return type (composite/band, leaders, artifact-coverage matrix), which is helpful. However, for a comparison tool, additional detail on interpretation or example usage could improve completeness. It is adequate for the complexity.

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

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

Schema description coverage is 100%, so the schema already defines 'providers' as 'Provider slugs to compare (2+).' The description adds minimal value beyond repeating '2+ providers' and 'side by side', which does not enrich the parameter semantics 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 action ('Compare 2+ providers side by side') and specifies the output components ('composite/band, per-facet leaders, and an artifact-coverage matrix'). It distinguishes from sibling tools like 'get_provider' and 'find_providers' by focusing on multi-provider comparison.

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

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

The description implies usage for comparing multiple providers but does not explicitly state when to use it vs alternatives like 'find_providers' or 'get_provider'. No 'when-not' guidance or alternative names are provided, but the context of sibling tools helps.

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

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

With no annotations provided, the description carries full burden. It discloses that the list is 'persistent' and requires an API key, but fails to mention behavior on duplicate names, creation limits, or side effects. For a creation tool, more transparency is needed.

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

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

The description is a single, clear sentence with no wasted words. It is front-loaded with the key action and resource.

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 2 parameters, the description lacks information on return values, error conditions, or how the created list can be used later. It is incomplete for an agent to fully understand 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 has 2 parameters with 50% description coverage (only 'members' has a description). The tool description adds no extra meaning beyond the schema; it does not clarify that 'name' is required or what constitutes valid 'provider slugs'.

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

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

The description clearly states the verb 'Create', the resource 'named, persistent list', and the domain 'of providers or APIs'. It distinguishes itself from sibling tools like 'add_to_list' and 'delete_list' by focusing on list creation. The 'PRO' tag indicates premium status.

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

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

The description mentions the prerequisite of an apis.io API key, but does not provide explicit guidance on when to use this tool versus alternatives like 'add_to_list' or 'delete_list'. Usage context is implied but not clearly differentiated.

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

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

With no annotations provided, the description must disclose behavioral traits. It does not mention whether deletion is permanent, if there are side effects, or any authorization requirements beyond ownership. This is a critical gap for a destructive operation.

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?

Although concise, the description is too sparse. It consists of only 4 words, sacrificing necessary detail for brevity. Front-loading is fine, but the content is inadequate.

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 is a simple delete with one parameter, no output schema, and no annotations, the description should cover ownership criteria, return behavior, and potential errors. It does none of this, leaving the tool under-specified.

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 'id' lacks any description in the schema (0% coverage). The description adds no additional meaning, leaving the agent to infer what 'id' refers to (e.g., list ID). This 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 clearly states the action 'Delete' and the resource 'a list', and implies ownership. It distinguishes from siblings like create_list, get_list, list_lists, and delete_saved_search. However, the 'PRO' tag may be extraneous.

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 vs alternatives, nor are there any exclusions or prerequisites beyond the implied ownership. 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?

With no annotations, the description must disclose behavioral traits. It indicates deletion (destructive action) and ownership requirement, but does not explain error handling, reversibility, or permission details.

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

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

The description is brief and front-loaded, but it omits context for the 'PRO' tag and could include essential details without becoming 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 simplicity, the description lacks critical details such as behavior on success/failure, id validation, and ownership enforcement, 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?

Schema coverage is 0%, so the description should compensate for the sole parameter 'id', but it provides no additional meaning (e.g., format, source, or example).

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 specifies the verb 'Delete', the resource 'saved search', and the ownership condition 'you own', clearly distinguishing it from sibling tools like save_search (create) or run_saved_search (execute).

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

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

No guidance is provided on when to use this tool versus alternatives. The 'PRO' label hints at a condition but offers no explanation of usage 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It transparently states that the tool accepts any identifier resolvable by resolve() and returns only the requested groups. It also mentions cost implications ('Free base'). However, it does not discuss auth, rate limits, or mutability (likely read-only).

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

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

The description is concise (two sentences plus a brief note) and front-loaded with the key benefit. Every word adds value, avoiding redundancy. The structure efficiently communicates purpose, usage, and parameters.

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 does not explain the return format (e.g., structure of combined groups) or how multiple groups are merged. Since there is no output schema, the description should provide more details on what the agent can expect. It covers core functionality but lacks output structure completeness.

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

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

Schema coverage is 100% (both parameters described). The description adds significant meaning beyond the schema: it explains that 'id' can be a slug or any identifier resolve() accepts, lists the field group options with cost notes, and indicates defaults. This fully compensates for any schema brevity.

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 resolves a slug or identifier and returns selected field groups, distinguishing it from chaining multiple get_* calls (e.g., get_provider, get_provider_rating). The verb 'resolves' and resource 'provider data' are explicit, and sibling differentiation is achieved by naming alternatives.

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 ('instead of chaining') and lists field groups with cost distinctions (free vs Pro). It provides clear context for use but does not explicitly state when not to use it (e.g., for a single field group), though that is implied. The naming of alternative tools adds guidance.

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

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

With no annotations, the description must disclose behavior. It mentions license tier, bulk export, and attribution, but lacks details on authentication, rate limits, performance implications, or whether it's read-only. For a bulk export tool, some operational context is missing.

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 concise 4-sentence paragraph. Key information (bulk export, dataset options, target audience, attribution) is front-loaded. No extraneous words or 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 no output schema and simple parameters (enum + optional string), the description sufficiently covers what the tool does, what it returns, and who it's for. It effectively distinguishes the tool from paginated siblings like find_ratings and find_providers, making it complete for its 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?

The schema covers 50% of parameters (co_brand has description; dataset lacks schema description). The description compensates by explaining each dataset option's content (e.g., 'ratings' includes facets, trend, etc.), adding significant meaning beyond the enum 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 the tool exports the entire dataset (ratings or providers) in one pull, contrasting with a 100-row page. It specifies the two dataset options and their contents (e.g., 'every rated provider with facets, trend, rubric + provenance'), making the purpose unambiguous and distinct from paginated sibling 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 targets 'media outlets and analysts licensing the data to publish rankings and trends,' and implies bulk export use. It does not explicitly list when not to use, but the hint about 'not a 100-row page' suggests alternatives like find_ratings. Adding explicit exclusions would improve clarity.

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

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

No annotations provided, and the description doesn't disclose behavioral traits like auth requirements, side effects, or whether the export is safe. Only mentions 'PRO' implying a subscription.

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 'PRO' indicator. Efficient but lacks structure; every word serves a purpose.

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

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

For a 2-parameter export tool with no output schema, the description provides enough context (output type, team commit) but could be more detailed about the document 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 100% and adequately explains both parameters. The tool description adds no additional meaning beyond the schema, meeting the baseline.

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

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

The description clearly states the tool exports a designed capability stack as an APIs.json document with an Arazzo hint, distinguishing it from sibling tools like recommend_stack or find_apis.

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 recommend_stack. Lacks context on prerequisites or conditions for use.

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

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

No annotations are provided, so the description carries full burden. It discloses pagination and sorting but lacks details about authentication, rate limits, or potential side effects (though likely read-only). Minimal behavioral context beyond the schema.

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

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

The description is very concise with two sentences: one summarizing purpose and filters, the other giving usage guidance. No redundant information; every sentence serves a 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?

Despite having 15 parameters and no output schema or annotations, the description does not explain return values, pagination mechanics, sorting defaults, or how to interpret results. It leaves significant gaps 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?

Description mentions filtering by tag, provider, artifact type, industry, region, or rating band, covering some parameters but ignoring many (q, area, sort, view, limit, match, fields, min_score). With 40% schema coverage, description adds limited 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 tool provides a 'paginated, sortable list of APIs across providers' with explicit filtering dimensions. It distinguishes itself from the sibling apis_io_search by directing users to use that first for cross-type overviews.

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 includes a usage hint ('Use apis_io_search first for a cross-type overview'), providing context for when this tool is appropriate. However, it does not explicitly state when not to use it or give comparisons to other sibling tools.

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

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

With no annotations, the description should reveal more behavior. It mentions inlining bodies but omits details on pagination, result format, the match enum, and any side effects or constraints.

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

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

Three short sentences with minimal redundancy. Could be slightly reordered, but effectively front-loads the tool's purpose and key filters.

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?

Missing output schema and annotations; description lacks details on response structure, pagination behavior, and ordering, making the tool hard to use without external documentation.

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 low (29%), but description adds meaning for 'providers' and 'include' filters beyond the schema. However, it ignores page, limit, and match parameters, leaving gaps.

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 searches for APIs.json discovery documents, with specific verbs ('find', 'Filter') and a distinction from the sibling 'find_artifacts' tool.

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 recommends 'find_artifacts' for cross-type search when this tool is inappropriate, and lists filter parameters (q, tags, providers, include).

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

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

No annotations are provided, so the description carries full burden. It mentions that 'include=["content"] inlines bodies,' a key behavioral trait. However, it does not disclose pagination behavior (page, limit), match logic (any/all), or result format. With no output schema, this leaves gaps for an agent.

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

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

Two sentences that front-load the purpose, then list key filters and an alternative. Every part earns its place; no redundancy or 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 7 parameters, no output schema, and many sibling tools, the description covers the main filters and the 'include' behavior but omits pagination, match logic, and result structure. It is adequate but not fully complete for an agent to confidently use 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 low (29%). The description adds meaning for 'include' (inlines bodies) and 'providers' (provider filtering), but does not explain 'page,' 'limit,' or 'match' beyond the schema defaults/enums. It partially compensates for the schema's lack of 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 'Arazzo workflows across the catalog. Multi-step API workflows chaining operations.' It identifies the specific resource type (Arazzo workflows) and distinguishes from sibling tools like find_artifacts, which is explicitly mentioned for cross-type search.

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

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

Provides explicit filtering guidance: 'Filter by q / tags / providers; include=["content"] inlines bodies.' Also gives an alternative: 'Use find_artifacts for cross-type search.' This tells agents when to use this tool versus others.

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

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

No annotations are provided, so the description must disclose behavioral traits. It describes the tool as a 'browse' operation, implying it is read-only and safe, but it does not address pagination, authorization needs, or what 'scored' means. Missing important behavioral details.

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

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

The description is a single sentence that front-loads the core purpose and includes examples and capabilities. It is concise without being terse, but could be slightly more structured.

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

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

No output schema exists, so the description should explain return values and pagination. It mentions results are 'scored provider indexes' but does not specify the response structure, fields, or pagination behavior, leaving the agent with incomplete 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?

The input schema has 4 parameters with 0% description coverage, so the description must compensate. It only loosely maps 'q' to text search and 'sort' to provider count, but omits 'page' and 'limit' entirely. No parameter formats or examples are given.

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

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

The description clearly states the tool browses a taxonomy of areas, gives concrete examples like authentication and webhooks, and distinguishes itself from sibling tools (e.g., find_tags, find_industries) by specifying 'curated, scored provider indexes' and 'areas taxonomy'.

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

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

The description implicitly advises when to use the tool—when searching for areas by text or sorting by provider count. It does not explicitly exclude alternatives, but the examples and context make the use case 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?

No annotations provided, so description carries full burden. It mentions inlining bodies with include=['content'] but lacks details on pagination, ordering, result format, rate limits, or auth requirements.

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

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

Relatively compact, front-loads purpose and alternatives. List of types is long but necessary; overall efficient with minimal 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?

Fails to explain return value format (no output schema), pagination behavior, or filtering semantics beyond type. 7 parameters with many siblings call for richer context than provided.

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, description only clarifies 'type' (lists values) and 'include' (inlines bodies). Parameters 'q', 'page', 'tags', 'limit', 'providers' remain undocumented, leaving significant gaps.

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 finds artifacts of any one type across the catalog, and explicitly distinguishes from dedicated find_<type> siblings by positioning itself as the cross-type entry point.

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 prefer dedicated find_<type> tools when the type is known, and lists available types. Provides clear context for when to use this tool vs alternatives.

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

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

No annotations are provided, so the description carries the full burden. However, it does not disclose behavioral traits such as read-only nature, auth requirements, or side effects. The description only states what the tool does, not its behavioral impact.

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

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

The description is concise with two sentences, front-loading the main purpose and key filters. Slightly more detail could be added without verbosity.

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

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

Given the complexity (8 parameters, no output schema, no annotations), the description lacks details on return format, pagination behavior, and result structure. It covers enough for basic usage but is incomplete for advanced scenarios.

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 low (38%). The description adds value by explaining filter parameters (q, tags, providers, include) but does not cover all 8 parameters (e.g., page, limit, match, version are not mentioned). It partially compensates for the low coverage but leaves gaps.

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 finds AsyncAPI (event-driven) specifications, uses specific verbs and resources, and distinguishes from the sibling tool find_artifacts by recommending it for cross-type search.

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

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

Provides explicit guidance on when to use: for AsyncAPI/event-driven APIs. Mentions filtering options and suggests using find_artifacts for cross-type search, effectively differentiating from alternatives.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It reveals that include=['content'] inlines bodies, which is a key behavioral trait. While it doesn't discuss pagination, rate limits, or auth, for a read-only search tool this is acceptable. The description adds value beyond schema by explaining the inline 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 extremely concise—two short sentences with no redundant information. Every word adds value (specifies resource type, filters, and sibling differentiation). It is front-loaded with the most important information.

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

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

The tool has 8 parameters and no output schema, yet the description only covers filtering options and inline behavior. It lacks information about the response structure, pagination, ordering, and default behavior. While the pattern of similar find_* tools may fill gaps, the description alone is not fully complete for an agent to understand all aspects of tool 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 low (38%) with only 3 of 8 parameters documented. The description adds meaning for three parameters (q, tags, providers) and the include parameter but ignores page, limit, match, protocol. Since coverage is low, the description should compensate more fully; it provides some context but not enough to fully understand all parameters.

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

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

The description clearly states it finds 'AsyncAPI event channels', specifying the resource type (event channels/topics/streams). It distinguishes itself from siblings by mentioning 'Use find_artifacts for cross-type search', making its purpose specific and unique.

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 direct guidance by naming an alternative tool (find_artifacts) for cross-type search, implying when not to use this tool. It also lists filter options (q, tags, providers) giving context for usage. However, it doesn't explicitly state when to prefer this tool over other similar find_* tools, leaving some ambiguity.

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

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

No annotations provided, so description carries full burden. It discloses that include=['content'] inlines bodies, which is a key behavioral trait. However, it does not mention any potential side effects, auth requirements, or rate limits. For a non-destructive search tool, this is adequate but could be slightly more comprehensive.

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

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

The description is extremely concise—two sentences—yet packs in the tool's purpose, key filters, and a sibling alternative. Every sentence earns its place with no redundancy.

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

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

Given the presence of many sibling find_* tools, the description is complete enough for selection and invocation. It covers what the tool finds, how to filter, and when to use an alternative. However, it lacks explicit mention of sorting, pagination, or return format, which would be helpful for invocation. With no output schema, a bit more detail on results would improve completeness.

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

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

Schema coverage is low (38%), but the description compensates by explaining the purpose of key parameters: q (free text), tags (tag slugs), providers, and include (content inlining). It also adds meaning beyond the schema by stating that include inlines bodies. Not all 8 parameters are explained (e.g., page, limit, sort, match), but the most important ones are covered.

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 finds Postman/Open collections across the catalog, specifically runnable request collections. It distinguishes from the sibling tool 'find_artifacts' by mentioning cross-type search, making the purpose precise and unique.

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 tells when to use this tool and when not: 'Use find_artifacts for cross-type search.' It also outlines available filters (q, tags, providers, include) giving clear usage 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?

With no annotations, the description must disclose behaviors. It indicates a read-only operation ('Browse') and cost ('Free discovery'), but lacks details on pagination, rate limits, authentication, or output structure.

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

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

Two concise sentences with no waste. The first sentence states the core action and scope, the second adds value (free discovery). Ideal front-loading.

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 annotations, the description is minimally complete for a simple browse tool. However, it lacks parameter explanation and output format, which could hinder correct usage by an AI 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 description coverage is 0%, and the description does not explain the parameters (q, page, limit). The tool name suggests a query, but no additional meaning is provided beyond the schema's basic type and constraints.

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 browses Fortune 1000 companies by name, ranked by technology-readiness signal. It distinguishes from siblings like find_apis or find_providers by focusing on company profiling. The phrase 'Free discovery' adds context about cost.

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

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

The description implies usage for initial discovery (free) but does not provide explicit when-to-use or when-not-to-use guidance, nor alternatives among siblings like get_company_insight or company_gaps.

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

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

No annotations exist, so description carries full burden. Mentions filtering and including content, but does not describe pagination, sorting, or return format behavior, leaving gaps.

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

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

Two sentences, no filler. Front-loaded with core purpose, then functional details. Every phrase 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?

Covers core filtering and sibling separation, but lacks details on pagination, sorting, and output structure. Adequate for basic use but not fully comprehensive.

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 low (38%). Description adds meaning for q, tags, providers, and include, but omits page, sort, limit, and match parameters.

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

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

Clearly states tool returns example payloads (request/response examples) from the catalog. Explicitly distinguishes from sibling 'find_artifacts' by noting it is for cross-type search.

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

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

Directly tells when to use an alternative ('Use find_artifacts for cross-type search') and lists filtering options (q, tags, providers, include). Provides 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?

No annotations are provided, so the description carries the full burden. It discloses that include=['content'] inlines bodies, which is a behavioral trait. However, it doesn't mention side effects, rate limits, or authentication needs, but the tool is a read-only search, so the description is reasonably transparent.

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

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

The description is concise: two sentences that quickly convey purpose, filtering options, and a sibling reference. Every sentence is informative and there is 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 8 parameters, no output schema, and no annotations, the description is somewhat thin. It doesn't explain pagination behavior, return format, or default sorting. While it provides essential filtering guidance, it lacks details that would help an agent fully use 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 only 38% (3 out of 8 parameters described). The description adds meaning by mentioning filtering by q/tags/providers and explaining the include parameter behavior. However, parameters like page, limit, and match are not addressed in the description, leaving gaps.

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 finding FinOps/billing models, explaining it covers 'how usage is metered and billed.' It distinguishes from siblings by naming find_artifacts for cross-type search.

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

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

The description explicitly mentions filtering by q/tags/providers and include, and directs users to find_artifacts for cross-type search. It implies when to use this tool (for billing models) but lacks explicit exclusions or comparisons with other find_* tools.

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

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

No annotations provided, so description carries full burden. It mentions that include=['content'] inlines bodies, but lacks details on authentication, rate limits, or response structure. Minimal behavioral disclosure beyond the core function.

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

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

Two sentences, front-loaded with purpose, followed by filter details and sibling reference. Every phrase 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?

With 7 parameters and no output schema or annotations, the description covers key filters and cross-type alternative. Lacks explanation of default behavior or return format, but sufficient for a simple search tool.

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

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

Schema coverage is low (29%), but the description adds meaning for 'providers' (filter) and 'include' (inline bodies) beyond the schema. However, parameters page, limit, and match remain undocumented.

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 finds 'GraphQL schemas' and 'GraphQL type systems', using a specific verb and resource. It distinguishes from siblings by referencing find_artifacts for cross-type search.

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

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

Explicitly lists filter parameters (q, tags, providers) and explains the include option. Provides an alternative tool (find_artifacts) for cross-type searches, giving clear when-to-use guidance.

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

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

With no annotations, the description should disclose behavioral traits, but it only mentions browsing and sorting. It does not address pagination, default behaviors, rate limits, or authentication requirements, leaving significant gaps.

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

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

The description is extremely concise at one sentence, front-loading the main action and sorting capability. However, the brevity sacrifices completeness, though this is a structural strength.

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

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

With 4 parameters, no output schema, and no annotations, the description is too minimal. It lacks details on search behavior (q), pagination, result structure, and sorting options, making it incomplete for effective tool use.

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%. The description adds partial meaning for 'sort' (sort by provider/API count) but fails to explain 'q', 'page', or 'limit'. Given the low coverage, the description compensates insufficiently.

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 browses industry verticals, which aligns with the name and differentiates it from siblings like 'find_apis' or 'find_providers'. It also mentions sorting capability, adding specificity.

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 among the sibling tools. The description only states what it does, not the appropriate context or exclusions.

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

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

No annotations provided, so description carries full burden. Only mentions 'by slug' and 'Free.' Lacks disclosure of read-only nature, permissions, or side effects.

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

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

Very concise single sentence plus 'Free.' Efficient but could benefit from more context without losing 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?

Given no output schema and 1 parameter, description is incomplete. Lacks return format, pagination info, and edge cases.

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 0% description coverage. Description adds meaning to 'slug' by stating it refers to provider/company, but lacks format or source guidance.

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 finds which VC firms back a given provider/company by slug. The phrase 'reverse portfolio edge' distinguishes it from typical portfolio lookups.

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?

Usage is implied but no explicit guidance on when to use this tool versus alternatives like find_vcs or vc_portfolio. No when-not or prerequisites mentioned.

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

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

No annotations exist, so the description must carry the burden. It mentions inlining bodies with include=['content'] but lacks details on safety (read-only), pagination limits, or whether modifications occur. The behavior of the tool is partially described but not comprehensively.

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: first states purpose, second provides usage hint and alternative. Every sentence is informative and front-loaded, 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?

For a search tool with 8 parameters and no output schema, the description covers core functionality (filtering and inlining) but omits details on sorting, pagination, and match behavior. It is adequate but not fully comprehensive.

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

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

Schema coverage is only 38%. The description adds meaning for q, tags, providers, and include parameters, but does not clarify page, sort, limit, or match. Given low coverage, more parameter explanation 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 states the tool finds 'JSON-LD contexts across the catalog' and 'Linked-data vocabularies,' which is specific and distinguishes it from sibling tools like find_artifacts (cross-type search) and find_vocabularies (likely broader).

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 using find_artifacts for cross-type search, giving a clear when-not-to-use. It also mentions filtering by q/tags/providers, but does not compare to other similar tools like find_vocabularies.

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

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

No annotations exist, so description carries full burden. It adds that include=['content'] inlines bodies, but does not disclose read-only nature, pagination behavior, or return format. Adequate but limited.

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

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

Three concise sentences, no filler. Front-loaded with the tool's purpose, then filtering options, then alternative. Every sentence adds value.

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

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

Given 7 parameters and no output schema, the description explains some filters but not pagination or match. Adequate for basic use but not fully comprehensive for all use cases.

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 low (29%). Description adds meaning for q, tags, providers, and include, but omits page, limit, and match. Partially compensates but not fully.

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: finding JSON schemas ('JSON Schemas across the catalog. Standalone data schemas.'). It distinguishes from sibling tools like find_artifacts for cross-type search.

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

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

Explicitly states filtering options (q, tags, providers, include) and directs when to use an alternative ('Use find_artifacts for cross-type search.'), providing explicit when-to-use and when-not-to-use guidance.

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

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

No annotations are provided, so the description must fully disclose behavior. It fails to mention pagination (page/limit), sorting, error handling, or any read-only/destructive implications. Only the include option's effect is noted.

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

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

Two sentences with key information; front-loaded with purpose. However, the first sentence is a fragment ('JSON Structures across the catalog.'), which could be integrated into a full sentence.

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

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

For a tool with 9 parameters and no annotations or output schema, the description is too brief. It lacks details on return format, edge cases, example usage, or constraints beyond the sibling hint. More completeness is needed for adequate agent guidance.

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 44%, so the description must compensate. It clarifies that q, tags, providers are filters and that include=['content'] inlines bodies, which adds value. But it does not explain page, limit, sort, match, struct_type, or their specific roles, leaving gaps.

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 finds JSON structures/data schemas behind APIs, and explicitly differentiates from find_artifacts for cross-type search. The verb 'find' and resource 'JSON structures' are 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?

Specifies filtering by q/tags/providers and the include option. Explicitly advises using find_artifacts for cross-type search, providing a clear when-not guide. However, no guidance relative to other JSON-specific siblings like find_json_schemas or find_json_ld.

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

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

No annotations are provided, so the description carries full burden. It mentions that include=['content'] inlines bodies, a behavioral trait. However, it does not disclose authentication, rate limits, or pagination behavior. For a read-only search tool, it is somewhat transparent but could detail more.

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

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

The description is three sentences with no fluff. It front-loads the purpose, then lists filters, then provides an alternative. 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 8 parameters and no output schema, the description covers the main filtering dimensions and distinguishes from siblings. It lacks details on some parameters (match, page, limit, install_method) but is sufficiently complete for a search tool.

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

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

Schema description coverage is low (38%). The description adds meaning for key parameters (q, tags, providers, include) but does not explain match, page, limit, or install_method. It partially compensates for the low coverage but leaves gaps.

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 the tool finds MCP servers in the catalog and defines them as Model Context Protocol servers. It distinguishes from the sibling tool find_artifacts by explicitly mentioning that find_artifacts is for cross-type search, clarifying the scope.

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

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

The description explains filtering options (q, tags, providers, include) and explicitly suggests using find_artifacts for cross-type search. It provides clear context but does not enumerate when not to use this tool.

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

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

Without annotations, the description adds context about filtering and inlining bodies. However, it does not disclose other behavioral aspects like pagination, sorting, or result format. The description is adequate but not comprehensive.

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

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

The description is concise (two sentences), but the second sentence is a bit cluttered. It could be split for better readability. Overall, it is efficient and front-loaded with the purpose.

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

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

Given 7 parameters, no output schema, and no annotations, the description covers the most important aspects (filters, primary purpose) but omits details on pagination, match mode, and result structure. It is adequate for a search tool but not fully complete.

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

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

Schema coverage is low (29%), but the description adds meaning for key parameters (q, tags, providers, include). Missing params (page, limit, match) are not explained, so the description partially compensates.

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 OpenAPI specifications across the catalog, and distinguishes itself from get_openapi (returns one spec) and find_artifacts (cross-type search). The verb 'find' matches the naming convention and sibling 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 filtering options (q, tags, providers, include) and directs to find_artifacts for cross-type search. It does not explicitly state when not to use this tool, but the context is sufficient for most use cases.

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

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

No annotations provided, and description does not explicitly state read-only nature, authentication needs, or side effects. However, 'find' prefix implies non-destructive query. Could be improved by clarifying safety.

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

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

Two sentences, no filler, front-loaded with purpose. Every sentence adds value: first states what, second states constraints and alternatives.

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 8 parameters, description covers main use case and filtering, but lacks details on pagination, sorting, and match logic. Adequate for a search tool.

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

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

Schema coverage is low (38%), but description adds meaning to key parameters (q, tags, providers, include) by explaining filter behavior and inlining content. However, other parameters (page, sort, limit, match) are not elaborated.

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 retrieves pricing plans and API pricing tiers, and distinguishes from sibling find_artifacts for cross-type search, providing a specific verb-resource pair with differentiation.

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 (pricing plans) and when not (cross-type search), and mentions filtering capabilities with q, tags, providers, and include parameter for inlining content.

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

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

No annotations provided, so description is the sole source. Describes 'by reference' and that include=['content'] inlines bodies, but does not disclose aspects like whether it's read-only, authentication requirements, or pagination behavior beyond schema parameters.

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

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

Two sentences, front-loaded with purpose, then usage guidance. No wasted words.

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

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

With 7 parameters, no output schema, and no annotations, the description is adequate for a search tool but lacks details on pagination, match mode, and return format. Mentions alternative, which helps.

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 low (29%). Description adds meaning for 'providers' and 'include' (inlines bodies), but does not explain 'page', 'limit', or 'match' behavior. It partially compensates but not fully.

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 finds Postman collections, specifies 'by reference', and describes filtering options (q, tags, providers, include). It distinguishes from sibling find_artifacts by mentioning cross-type search.

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

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

Provides explicit alternative: 'Use find_artifacts for cross-type search.' It implies when to use this tool (for Postman collections) but lacks explicit when-not-to-use scenarios.

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

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

No annotations are provided, so the description carries the full burden. It discloses pagination and sorting ('Paginated, sortable list') and enumerates filter dimensions. While it does not explicitly state read-only behavior or rate limits, the 'list' wording implies a safe read operation, which is adequate.

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

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

The description is a single sentence that is front-loaded with the core purpose ('Paginated, sortable list of providers'), followed by filter categories and a usage hint. Every word earns its place; 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?

Given the tool has 15 parameters, no output schema, and many siblings, the description is reasonably complete. It covers the main purpose, key filters, pagination, and an alternative tool. It does not explain every parameter, but the schema provides partial coverage. A slightly longer description could improve completeness for edge cases.

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 only 40%, so the description must compensate. It lists key filter categories (text, tag, artifact type, industry, region, rating band), which correspond to many parameters. However, it does not explain parameters like match, fields, min_score, or providers, leaving some gaps.

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 'Paginated, sortable list of providers' and lists specific filter dimensions (text, tag, artifact type, industry, region, rating band), leaving no ambiguity about what the tool returns.

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 using `apis_io_search` first for cross-type overview, providing a clear when-to-use hint. However, it does not differentiate from other sibling `find_*` tools for specific entity types, which would be beneficial given the large sibling list.

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

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

No annotations are provided, so the description carries the burden. It mentions that include=['content'] inlines bodies, giving some behavioral detail, but lacks information on idempotency, authentication requirements, or response structure. It does not contradict any annotations since none exist.

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 and key features. Every sentence adds value: purpose, filtering options, and an alternative tool. 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?

Given 8 parameters, no output schema, and no annotations, the description covers core filtering but omits details on pagination, sorting, default behavior, and return format. Adequate but incomplete for a tool of this complexity.

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

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

Schema description coverage is low (38%). The description adds meaning for q, tags, providers, and include parameters, but silent on page, sort, limit, and match. It partially compensates but leaves gaps for key parameters.

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

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

The description states 'Rate-limit policies across the catalog' and 'Declared throttling policies', clearly identifying the tool as a searcher for rate-limit policies. It distinguishes from siblings by suggesting 'Use find_artifacts for cross-type search', showing this tool is scoped to rate limits.

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 filtering options (q, tags, providers, include=['content']) and an explicit alternative ('Use find_artifacts for cross-type search'). It does not explicitly state when not to use this tool, 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?

No annotations provided. Description only mentions it is 'PRO' (possibly indicating access restriction) and returns movers. Does not disclose other behaviors like auth needs, rate limits, or side effects.

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

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

Description is a single sentence, which is concise but too minimal. It front-loads the key action but omits supporting details that could aid understanding.

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 is incomplete: it does not define 'rating movers', 'previous scoring build', or output format. Lacks context for effective use.

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%. The description does not explain the 'limit' parameter, its meaning, or how it affects results. Schema provides defaults and constraints, but description adds no 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?

Description clearly states it finds the biggest rating movers up/down since previous scoring build. The verb 'find' and resource 'rating movers' are clear. It distinguishes from siblings by focusing on movers specifically.

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 find_ratings or get_rating_history. The description does not mention any prerequisites or 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?

No annotations are provided, so the description must fully disclose behavior. It mentions filtering and sorting but omits key details like pagination (implied via page/limit params), tie-breaking, empty results, or whether the leaderboard is real-time vs. cached. This leaves significant behavioral gaps.

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

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

Two efficient sentences. The first sentence introduces the tool and its filtering capabilities; the second expands on sorting. No redundant information, every phrase adds value.

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

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

No output schema is provided, so the description should at least hint at the return structure. It covers main functionality (filtering/sorting) but omits pagination, default limit, and whether results are ranked. With 9 parameters and no output schema, the description is adequate but not complete.

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

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

Schema description coverage is only 11% (only sort has a description). The description compensates by explaining the role of parameters: 'filter by band, score range, trend, or facet threshold' and 'sort by composite (default), delta, or any quality facet'. It adds meaning for band, min_score/min_facet, sort, and trend, though not all 9 parameters are covered.

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 as a 'ranked ratings leaderboard' and specifies multiple filtering and sorting options. It distinguishes from siblings like find_rating_movers by mentioning 'delta (biggest gainers)' and from generic rating tools by focusing on leaderboard ranking with quality facets.

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 the tool (for leaderboard ratings) and lists filters and sort options, giving context. However, it does not explicitly state when not to use it or mention alternatives among the many siblings, lacking exclusion guidance.

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

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

No annotations provided, so description must disclose behavioral traits. Only mentions sorting capability; does not state if read-only, auth needs, rate limits, pagination details, or error handling.

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

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

One sentence, concise, but lacks essential details. Every sentence should earn its place; this one is too sparse.

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

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

Given 4 parameters with no schema descriptions, no annotations, and no output schema, the description is severely incomplete. Agent cannot reliably invoke or understand return values.

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%. Description does not explain any of the 4 parameters (q, page, sort, limit). Only hints that 'sort' relates to provider/API count, but no specifics on allowed values or how to use other parameters.

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

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

The description uses verb 'browse' and resource 'geographic regions'. It adds sorting capability by provider/API count. While 'browse' is somewhat vague, it clearly distinguishes from siblings like 'get_region' (singular) and other 'find_*' 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 like 'get_region'. No mention of prerequisites, exclusions, or typical use cases.

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

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

No annotations provided, so description covers core behavior (filtering, inlining bodies via include=['content']). Lacks disclosure of auth, rate limits, or read-only nature.

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

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

Two focused sentences; front-loaded with purpose, then filters and alternative. 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?

Covers key purpose and filters, but lacks detail on sorting, pagination, match behavior, and return value format (no output schema).

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

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

With 38% schema coverage, description adds meaning for q, tags, providers, and include, but glosses over page, sort, limit, match.

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 tool finds Spectral governance rulesets/linting rulesets, and differentiates with sibling find_artifacts for cross-type search.

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

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

Explicitly mentions filter options and points to find_artifacts as alternative for cross-type search, but does not cover when to use other sibling find tools.

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

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

No annotations are provided, so the description carries the full burden. It reveals that 'include=["content"] inlines bodies', which is a behavioral trait for parameters. However, it does not disclose other behaviors such as pagination limits, rate limits, or whether the operation is read-only. The description is adequate but not rich.

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

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

The description is concise with two sentences and a fragment. It front-loads the purpose and then provides filtering and alternative guidance. 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?

Given 8 parameters, no output schema, and no annotations, the description covers purpose and some filtering but omits details on sorting, pagination, and match logic. The alternative sibling is mentioned. It is moderately complete but not fully self-sufficient.

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 only 38%, but the description adds meaning for 'q', 'tags', 'providers', and 'include' by stating filtering options and that include inlines bodies. It does not cover 'page', 'limit', 'sort', or 'match'. The added value partially compensates, but gaps remain.

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 as finding OAuth scopes that an API defines. It uses the verb 'find' and resource 'scopes', and distinguishes from sibling 'find_artifacts' for cross-type search. The first sentence is slightly cryptic ('across the catalog'), but overall the purpose is clear.

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

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

The description specifies that this tool is for the Pro tier, setting a prerequisite. It also explicitly suggests using 'find_artifacts' for cross-type search, providing an alternative. No explicit when-not-to-use, but the context is sufficient.

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 filtering capabilities and the effect of including content, but with no annotations, it fails to disclose pagination, rate limits, or potential side effects beyond being a read operation.

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

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

The description is concise with five short sentences, front-loading the core purpose, though it could be more structured for readability.

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 8 parameters, no output schema, and no annotations, the description covers the main purpose and a sibling alternative but omits details on pagination, sorting, match logic, and 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 description adds meaning for q, tags, providers, and include, partially compensating for the low 38% schema coverage, but leaves page, limit, sort, and match unexplained.

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 finds 'Security artifacts across the catalog' and lists specific categories, distinguishing it from the sibling tool find_artifacts with an explicit alternative.

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?

Provides when-to-use context by naming find_artifacts as the alternative for cross-type search, though it lacks explicit exclusions 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?

No annotations provided, so the description must carry the burden. It states the logic ('by shared tags') but omits behavioral traits like read-only nature, authentication needs, rate limits, or any side effects. This is insufficient for a tool with no annotations.

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

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

Single sentence, no wasted words. Information is front-loaded and easy to parse.

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?

Tool has 2 parameters and no output schema. Description explains input and logic but lacks details on output format, pagination, error handling, or edge cases. Adequate for a simple tool, but could be more comprehensive.

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 0% description coverage. The description adds minimal meaning: 'aid' is the given API, 'limit' controls result count. It explains the similarity logic but does not elaborate on parameter formats, defaults, or constraints 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?

Description clearly states the tool finds APIs similar to a given one using shared tags. The verb 'find' and resource 'similar APIs' are specific, and the method 'by shared tags' is defined. It distinguishes from siblings like 'find_apis' (general search) and 'get_api' (single API).

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

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

No explicit guidance on when to use this tool versus alternatives. The description implies usage for finding similar APIs via tags, but does not mention when not to use it or provide comparisons to siblings like 'find_apis' or 'get_api'.

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

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

No annotations are provided, so the description must disclose behavior. It lists the criteria for similarity (tags, industry, region, artifact coverage) which is helpful, but does not mention whether it is read-only, any authentication requirements, rate limits, or the format of the response.

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 could be slightly expanded to include parameter details without losing 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?

Given no output schema and 0% schema coverage, the description is too minimal. It does not explain the return format, ordering, or how to effectively use the limit parameter. More context is needed for an agent to use the tool correctly.

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

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

Schema coverage is 0%, so the description must compensate. It does not explain the 'slug' parameter (the given provider identifier) or the 'limit' parameter. The description only vaguely hints at input through 'given one', leaving parameters underspecified.

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 finds providers similar to a given one as alternatives using specific criteria (tags, industry, region, artifact coverage). This distinguishes it from sibling tools like find_providers and find_similar_apis.

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

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

The description implies usage for finding alternatives to a given provider but does not explicitly state when to use it over other tools or when not to use it. No direct comparison with siblings is provided.

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

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

No annotations provided, so the description must cover behavior. It describes filtering and inlining but does not state read-only nature, pagination behavior, or error cases. It is not contradictory but lacks depth.

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

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

The description is two sentences, mostly efficient. The first sentence repeats 'Agent Skills' slightly redundantly. Overall no wasted words, front-loaded with key info.

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 7 parameters, no output schema, and no annotations, the description covers filtering basics but lacks pagination details, match logic, and response format. Adequate for simple use but not complete.

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

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

Schema coverage is 29% (only q and tags described). The description adds value by mentioning q, tags, providers, and include as filters and inlining. However, it omits page, limit, and match, leaving them unexplained. Partial compensation.

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 resource as 'Agent Skills' and states it operates 'across the catalog'. It lists filtering options (q, tags, providers) and mentions inlining bodies with include. It distinguishes from find_artifacts for cross-type search.

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

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

It explicitly advises to use find_artifacts for cross-type search, providing an alternative. It implies use for skills-only searches. No explicit 'when not to use' but sufficient guidance given sibling 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?

No annotations provided, so description bears full burden. Only mentions pagination and sorting, but lacks details on behavioral traits like rate limits, authentication, error handling, or idempotency. Minimal disclosure.

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

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

Two concise sentences with no fluff, front-loading key purpose and guidance.

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

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

For a tool with 6 parameters, no annotations, and no output schema, the description is too brief. It lacks details on return format, default behaviors, error handling, and edge cases.

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 67% (4 of 6 parameters described). The description adds no extra meaning beyond the schema; it does not compensate for the 2 undocumented parameters (page, limit) or clarify 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?

Clearly states it lists tags in the taxonomy with pagination and sorting. Specifically mentions using apis_io_search for cross-type overview, distinguishing from siblings.

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

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

Explicitly suggests using apis_io_search first for cross-type overview, providing usage guidance. However, lacks explicit when-not-to-use or prerequisites.

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

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

No annotations are provided, so the description carries full burden. It mentions a 'network-matched, rated portfolio graph' but does not disclose whether the tool is read-only, has rate limits, or other behavioral traits. The 'Free.' note is minimal.

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

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

The description is two sentences, front-loading the purpose and adding key context about portfolio graphs and sorting. Every sentence earns its place; 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?

With 6 parameters, no output schema, and no annotations, the description should provide more context. It omits pagination details, result structure, and behavioral expectations, 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 50%, and the description adds meaning for some parameters: it mentions search fields (q, tags, category) and explicitly lists sort options with default. However, page and limit parameters are not explained beyond schema.

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

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

The description clearly states the tool finds venture-capital firms by name, thesis tags, or category, and mentions a network-matched portfolio graph. It distinguishes from sibling tools like find_investors or find_providers by targeting VCs specifically.

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

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

The description implies usage for searching VCs but provides no explicit guidance on when to use versus alternatives or when not to use. It does not mention any prerequisites or exclusions.

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

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

No annotations are provided, so the description carries full behavioral disclosure burden. It mentions filtering and inlining bodies but does not disclose behavioral traits like read-only nature, authentication needs, rate limits, or side effects. The description lacks transparency about the tool's operational characteristics.

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

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

The description is extremely concise—two sentences—with no wasted words. The purpose is front-loaded, and every sentence adds value. It achieves maximum efficiency.

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 7 parameters, no output schema, and no annotations, the description is incomplete. It fails to explain return format, pagination behavior, or the effect of all filter parameters. While it covers core functionality, it omits important operational context for effective use.

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 only 29% (2 of 7 parameters have descriptions). The description adds meaning by noting that 'include=["content"] inlines bodies' and mentions filters by q, tags, and providers, but it does not explain page, limit, match, or other parameters. It partially compensates for low coverage but leaves several parameters undocumented.

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 finds 'API vocabularies across the catalog' and 'Controlled vocabularies a provider publishes', with a specific verb (find) and resource (vocabularies). It distinguishes from sibling tools by directing to 'Use find_artifacts for cross-type search', making its scope 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 explicitly says when to use it ('Filter by q / tags / providers') and when not to ('Use find_artifacts for cross-type search'), providing clear alternatives. This gives strong guidance on tool selection.

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

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

With no annotations, the description carries the full burden. It discloses behavioral traits: the tool scans for missing artifacts, compares to peer medians, and aggregates stack-level gaps. This is sufficient for a read-analysis tool, though it omits explicit statement of non-destructiveness.

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?

A single sentence conveys all key aspects: the tool is PRO, per-provider analysis, artifact types (MCP, Arazzo, etc.), peer comparison, scoring, and stack-level gaps. No wasted words; every clause 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 no output schema, the description adequately summarizes the output: per-provider lacking artifacts, peer common lacks, score vs median, and stack-level gaps. It does not detail return format or score interpretation, but the core information for an agent to understand the tool's behavior is present.

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 meaning by contextualizing the 'providers' parameter as a stack when multiple are provided, and alluding to the peer-share threshold concept. This enriches understanding beyond the schema's parameter names and types.

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

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

The description explicitly states the tool's function: for each provider, it identifies high-value artifacts it lacks (e.g., MCP, Arazzo, Rules, Skills), compares to peer common publications, and provides a score versus the peer median plus stack-level gaps. This is a specific verb+resource description that clearly distinguishes it from sibling tools like find_providers or compare_providers.

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

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

The description implies usage for gap analysis but does not explicitly state when to use this tool versus alternatives like find_providers or recommend_stack. No exclusions or prerequisites are mentioned, leaving the agent to infer context from purpose alone.

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

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

No annotations are provided, so the description must disclose behavioral traits. It mentions that setting include=["content"] inlines artifact bodies, which is a behavioral detail, but does not state if the tool is read-only, any side effects, or authentication requirements. For a data retrieval tool, this is minimal but not misleading.

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

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

The description is a single sentence that packs the core purpose and a key parameter usage hint. No superfluous words, and it is front-loaded with the main action. It 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 (3 params, no output schema), the description covers the main use case and one parameter behavior. However, it omits explanation of the 'artifact_types' parameter and any return value details. With no annotations, more completeness would be helpful but is not severely lacking.

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 explain parameters. It explains 'aid' as provider:api-slug and 'include' as an optional array with 'content' to inline artifact bodies, but does not explain 'artifact_types'. This partial coverage adds value but leaves one parameter undocumented.

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 full detail for a single API by its identifier (aid). The mention of 'set include=["content"] to inline artifact bodies' adds specific functionality. It is distinct from sibling tools like find_apis which are for 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?

The description implies usage when you have a specific API identifier and need full details. It does not explicitly state when not to use it or compare to alternatives, but the intent is clear enough for an AI to select it over search tools.

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

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

With no annotations provided, the description bears full burden for behavioral disclosure. It mentions synonym-awareness and grouping by type, but omits mutations, authentication, rate limits, error handling, and return format details.

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

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

Two sentences, front-loaded with purpose, every phrase adds value. No verbose or redundant text.

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

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

Given no output schema and moderate complexity (3 params), the description partially explains the return structure ('grouped by type, by_type_counts summary') but lacks details on pagination, limits, or error scenarios. Adequate but not complete.

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

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

Schema covers only 1 of 3 parameters with descriptions (33%). The description adds significant meaning: 'type' is synonym-aware, 'include' with ['content'] inlines bodies, and output includes 'by_type_counts'. This compensates well for schema gaps.

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 artifacts for one API, grouped by type. It mentions 'by_type_counts' as the summary, but does not explicitly differentiate from sibling tools like 'find_artifacts' or 'get_provider_artifacts', which reduces clarity.

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

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

The description indicates passing 'type' to filter and 'include' to inline bodies, but provides no guidance on when to use this tool versus alternatives (e.g., 'find_artifacts'), no prerequisites, and no when-not-to-use advice.

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

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

No annotations provided, so the description carries the full burden. It describes the output but does not disclose behavioral traits like read-only nature, authentication needs, or any side effects. It is accurate but lacks additional context beyond the schema.

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

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

Two sentences efficiently convey the tool's purpose and usage guidance. The first sentence defines what it returns, and the second provides alternatives and parameter hints. No wasted words.

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

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

The tool is simple with no output schema. The description covers the main output elements and directs users to alternatives for more data. It mentions the view and limit parameters implicitly. Slightly more detail on the return format would improve completeness.

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

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

Schema coverage is 67%, with slug lacking description. The description adds context by using slug in the URI structure, implying its role as the area identifier. It also explains the view parameter's behavior. This compensates for the undocumented slug parameter.

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 metadata, site link, and a top sample of member providers for one area. It distinguishes itself from sibling tools like find_providers and specifies the view=full option.

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 this tool (for metadata and sample) versus alternatives (find_providers for full list, view=full for full record). Includes a direct reference to find_providers?area=slug.

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

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

With no annotations, the description carries the burden of behavioral disclosure. The 'PRO' prefix hints at access restrictions, but it does not explicitly state authorization requirements, rate limits, or error behavior. The tool's behavior regarding missing slugs or pagination is unaddressed.

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 short sentence, which is concise but lacks structure. It front-loads 'PRO' importance but does not organize information for quick scanning.

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 (2 parameters, no output schema, no annotations), the description is severely incomplete. It omits return format, error handling, and typical 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 the description provides no explanation of the 'slug' or 'limit' parameters. The agent receives no guidance on what values are valid or how they affect the output.

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 identifies the tool as retrieving top-rated providers in a curated API Evangelist area. It implies the verb 'get' and distinguishes from sibling tools like 'get_region_leaders' and 'get_industry_leaders' by specifying 'area'. However, a more explicit verb would improve 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 'get_industry_leaders' or 'get_region_leaders'. No context is given for prerequisites or typical use cases.

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

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

No annotations exist, so the description carries full burden. It states the data included but does not disclose whether the operation is read-only, requires authentication, has rate limits, or any potential side effects. The description is minimal.

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

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

The description is a single sentence, which is concise but lacks necessary detail. It is front-loaded but insufficiently informative. Every sentence must earn its place; this one does not fully earn its place due to missing semantics.

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

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

Given the complexity (multiple data dimensions) and lack of output schema, the description should explain return format, pagination, or error scenarios. It does not. The single-parameter input is simple, but the output is not addressed.

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 'slug' is not explained in the description. With 0% schema description coverage, the description should clarify what a 'slug' represents (e.g., company identifier, URL path). It does not, leaving the agent guessing.

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 returns a full demand-side profile including 40-dimension readiness scores, adopted stack, and per-quarter history. It uses specific nouns and implies retrieval. However, it does not explicitly state the action (get/retrieve), relying on the name.

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 siblings like find_company_insights, get_provider, or insights_dimensions. The description lacks any context about prerequisites 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?

Without annotations, the description carries the full burden. It discloses that the tool returns metadata and a ranked top sample with a total count, implying a read-only operation. No contradictions exist, and the behavior is sufficiently clear for a retrieval tool.

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

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

The description consists of two short sentences with no wasted words. The first sentence front-loads the core purpose, and the second provides alternative usage. This is an model of 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?

For a relatively simple tool with no output schema, the description covers the main output (metadata + sample providers, ranked, with total). It could elaborate on the structure of the metadata, but given the tool's simplicity and the descriptive parameter schema, it is sufficiently 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 description adds meaning beyond the schema: it explains that `slug` is an industry identifier (used in `find_providers?industry=slug`) and clarifies the `view` parameter when to use 'full'. The `limit` parameter is already well-documented in the schema, so the description compensates for the un-documented `slug`.

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 metadata and a top sample of providers for one industry, using a specific verb ('get') and resource ('industry'). It also distinguishes itself from `find_providers?industry=slug` for the full list, avoiding confusion with sibling 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 explicit guidance: use `find_providers?industry=slug` for the full list or `view=full` for a complete record. This helps the agent choose between this tool and alternatives, though it does not cover all sibling tools (e.g., `get_industry_leaders`).

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

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

No annotations are available, so the description carries full burden. It only says 'top-rated providers' without explaining sorting, what 'top-rated' means, or response structure. Missing behavioral details.

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

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

The description is extremely brief, but that brevity sacrifices information. Not all necessary content is present, making it under-specified rather than concisely 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?

With many sibling tools and no output schema, the description is insufficient. It fails to clarify what 'leaders' means, how results are ordered, or how to use the slug parameter.

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 mention either parameter (slug, limit). No added 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 states 'Top-rated providers in an industry vertical,' which clarifies it returns top providers for an industry. However, it does not distinguish from sibling tools like get_area_leaders or get_region_leaders, and the 'PRO' prefix is unexplained.

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. No context on prerequisites or exclusions is given.

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

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

The description discloses that member information is resolved to current values, which is a behavioral trait beyond a simple get. With no annotations, it partially carries the burden but lacks details on authorization requirements, rate limits, or side effects.

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

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

The description is a single sentence with no wasted words, but it is not front-loaded with the most critical information first. The 'PRO' prefix adds minor contextual value but reduces 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?

Given the tool's simplicity (1 parameter, no output schema), the description covers the basic function and return value. However, it omits potential error conditions, pagination, and more detailed 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?

The schema has 0% description coverage, and the description does not explain the 'id' parameter beyond implying it identifies the list. It adds minimal value over the schema, failing to specify format or source of the id.

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 list with resolved member details (name, band, score). The verb 'Get' and resource 'list you own' are specific. However, it does not explicitly differentiate from sibling tools like 'list_lists' or 'delete_list', but the unique return value provides some distinction.

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

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

The description implies the list must be owned by the user but does not specify when to use this tool over alternatives like 'list_lists' or other get tools. No when-not-to-use instructions or prerequisites are provided.

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