api-evangelist

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does disclose the nature of the output (coverage by section, per-rule reach, unmatched rules), which signals a read-only analysis. However, it does not explicitly confirm the operation is non-mutating, state prerequisites (e.g., whether governance rules must already be configured), or describe error behavior for malformed documents.

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 compact at roughly two sentences and front-loads the core purpose before the analogy. It is efficient with no filler, though the 'one altitude up' metaphor is slightly expansive and adds limited concrete value for an agent deciding whether to call the tool.

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

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

For a single-parameter analysis tool whose parameter is fully documented in the schema and which has no output schema, the description adequately conveys the output semantics (coverage by section, rule reach, and unmatched rules). Nothing critical for correct invocation appears to be missing.

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

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

Schema description coverage is 100%, and the schema already thoroughly documents the lone 'document' parameter (format accepted, both YAML/JSON strings and parsed objects). The description adds no parameter-specific meaning beyond the schema, so the baseline 3 is appropriate — the structured schema carries the burden.

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 a specific verb and resource: 'Measure how much of an API description your governance actually inspects — coverage by section, each rule's reach, and the rules that match nothing.' This is a clear, specific purpose. However, it does not explicitly distinguish itself from closely related siblings like validate_api, governance_report, or govern_estate — the differentiation is only implicit in the 'governance inspection' framing.

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 analogy 'Like test coverage, one altitude up' implies a use case (analyzing governance thoroughness) but provides no explicit when-to-use or when-not-to-use guidance, and no alternative tools are named. The usage context is implied rather than stated, leaving an agent to infer when this tool is appropriate versus siblings.

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

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

With no annotations, the description must carry the full burden of behavioral disclosure. It mentions the output (score and grade) and that it derives certain dimensions from an apis.json, but it does not disclose whether the operation is read-only, any authentication requirements, rate limits, or side effects. It lacks behavioral transparency beyond the core action.

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

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

The description is two sentences, with the purpose front-loaded and a concise rationale for the ruleset. It is efficient and avoids unnecessary detail, though the second sentence could be more actionable by specifying how to pass the ruleset.

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 leaves several gaps: the ruleset parameter is mentioned but not defined (property name, type, format); the role of 'apis.json' is ambiguous (is it a type of document or additional input?); the output format beyond 'score and letter grade' is unspecified; and there is no mention of error handling or prerequisites. Given the tool's complexity (multiple scoring dimensions) and lack of output schema, the description is insufficient for an agent to reliably call it.

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

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

The schema describes the 'document' parameter well (types and formats), giving 100% coverage for that parameter. However, the description adds crucial information about a 'ruleset' parameter that is not represented in the schema (it would be an additional property). This guidance is valuable for an agent to correctly invoke the tool, thus the description enriches parameter understanding.

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

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

The description clearly states the tool's function: scoring an API's maturity on a 0-100 scale with a letter grade, and enumerates the specific dimensions (design, governance coverage, documentation, discoverability, agent-readiness, operations). This is a distinct verb-resource pair that separates it from sibling tools like api_coverage (which might measure coverage) and validate_api (which might check validity).

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 instructs the user to pass a custom ruleset and argues why that matters, which is a usage directive. However, it does not explicitly state when to use this tool over alternatives (e.g., certify_api, validate_api) or provide exclusions. The context is implied but not explicit.

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 does state that the tool 'report[s] what each action matched,' which is a behavioral output detail. However, it doesn't clarify whether the operation mutates the input document, returns a new version, or what error/failure behavior looks like. Given the lack of annotations, this is a moderate disclosure—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?

Two sentences with zero fluff. The first sentence states the core action and expected outcome; the second sentence gives a concrete use case. It is front-loaded with the main purpose and efficiently covers all necessary information.

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

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

For a tool with only two parameters, both documented in the schema, and no output schema, the description provides enough context to invoke it: it explains the purpose, the input types are clear from the schema, and it hints at the output via 'report what each action matched.' It lacks specifics on return format or side effects, but given the low complexity, this seems sufficient. I would rate higher only if more operational details were needed.

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

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

The input schema has 100% coverage, meaning both parameters (overlay and document) have descriptive comments in the schema. The description adds no extra parameter-level detail beyond what the schema already provides, so the baseline of 3 is appropriate. The description does not conflict with or augment the schema's parameter documentation.

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

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

The description clearly states the function: 'Apply an OpenAPI Overlay to a document' with a specific verb (apply) and resource (OpenAPI Overlay on a document), plus an outcome ('report what each action matched'). It also mentions a clear use case (deprecation and migration choreography), which distinguishes it from sibling tools like validate_api or diff_api_versions by its focus on overlay application and matching reporting.

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 provides a direct usage context: 'Use it for deprecation and migration choreography without forking the contract.' This tells the agent when to reach for this tool. However, it doesn't explicitly name alternatives or conditions when NOT to use it, so I deduct one point for not covering exclusions 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?

No annotations are provided, and the description does not disclose side effects, authentication requirements, rate limits, or other behavioral traits. It only mentions input and output, lacking transparency for a tool that might access external repositories.

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 action and output. Every segment earns its place, with no wasted words.

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

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

The description is incomplete given no output schema and no annotations. It does not specify the structure of the punch-list, the definition of 'files', or any prerequisites. The mismatch between schema and description adds confusion.

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 is empty with additionalProperties true, but the description mentions parameters `repo` and `files`. This adds meaning beyond the schema but is vague on formats and relationships. Schema coverage is 100% due to no parameters, so description compensates partially.

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

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

The description clearly states the tool scores a repository's Spectral CI setup against an 8-point maturity rubric and returns a prioritized punch-list. This distinguishes it from sibling tools, which are diverse and unrelated.

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 provides context for input ('Pass a public repo or files') but does not specify when to use vs alternatives or when not to use. No exclusions or alternatives are mentioned.

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

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

No annotations are provided, so the description carries the full behavioral burden. It adds useful context about tamper-evidence and re-verifiability, but it does not disclose whether issuing the certificate persists state, requires authorization, or what the response contains. For a credential-issuing action, this is under-disclosed.

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 with no filler. The first sentence front-loads the core action and conditions, and the second adds the key self-verification property. 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?

Although the single-parameter schema is simple, the description refers to a 'named ruleset' and 'profile threshold' that are absent from the schema, so an agent cannot tell whether those are additional properties or inferred from the API description. With no output schema and no annotations, the issuance and re-verification flow is also 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 schema already describes the only parameter, 'api', at 100% coverage, so the baseline is 3. The description does not add meaningful parameter detail and, in fact, introduces 'named ruleset' and 'profile threshold' concepts that are not present in the schema, leaving some ambiguity about what can actually be passed.

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 a specific verb ('Issue') and names a precise artifact ('tamper-evident governance certificate'), along with the conditions ('passed a named ruleset at a profile threshold') and the integrity mechanism ('SHA-256 fingerprint'). It is clearly distinct from sibling verify_certificate because this tool issues rather than verifies.

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 use case: certify an API after it passes a ruleset. The fingerprint sentence hints at a separate re-verification action, but it never explicitly names verify_certificate or says when to prefer certify_api over validate_api or audit_pipeline. No exclusions, prerequisites, or alternative routing are provided.

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

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

No annotations are provided, so the description must disclose behavioral traits. It does not state whether the tool is read-only, modifies anything, or requires authentication. It implies an analysis operation ('Inventory') but does not explicitly confirm non-destructive behavior or describe any side effects. This is a significant gap for a tool with no annotation coverage.

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

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

The description is two sentences with zero wasted words. The primary action is front-loaded, and the usage guidance is a direct, actionable sentence. It is concise and well-structured.

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

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

The description explains what the tool does and when to run it, but it does not describe the return value or output format. Since there is no output schema, the description carries the responsibility for explaining what the agent will receive. It lacks details about the inventory structure, classification categories, or any limitations. This is incomplete for a tool that produces a nuanced result.

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

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

The input schema already describes the 'document' parameter comprehensively (100% coverage), including accepted formats and types. The tool description adds little specific parameter semantics beyond the schema. Since schema coverage is high, the baseline of 3 is appropriate.

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

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

The description clearly states the tool's function: inventorying PII, secret, and sensitive fields across parameters and request/response schemas. It uses a specific verb ('Inventory') and names the resource (OpenAPI) and scope. There are no sibling tools with similar purpose, so it is well-differentiated.

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

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

The description provides explicit usage guidance: 'Run this before exposing an API to agents.' This is a clear trigger and context for use. It does not mention alternatives or exclusions, but given the tool's uniqueness among siblings, this is sufficient. It could have explicitly stated when not to use it, but the guidance is useful.

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 carry the burden of behavioral disclosure. It does claim the output is 'runnable' and that path params are filled in, which indicates the tool performs substitution and validation. However, it does not mention potential failure modes (invalid input handling, timeouts, rate limits) or the exact structure of the returned samples. This is partial disclosure 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?

It is a single, dense sentence that front-loads the action and deliverable, with no filler words. Every clause adds information: the languages (curl, JS, Python), the scope (every operation), and the quality criteria (path params filled in, realistic body).

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 low-complexity tool with one fully documented parameter and no output schema, the description is sufficient: an agent knows exactly what to pass and what to expect. The only minor gap is that it doesn't explicitly state that the output is a mapping of operation→snippet, but that is implied by 'every operation'. Stylistically, it's near-complete.

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

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

The input schema already has 100% coverage of the single parameter 'document' with a description explaining accepted types (string or object) and formats (OpenAPI, AsyncAPI, Arazzo, JSON Schema). The tool description adds no additional parameter-level detail, so the baseline of 3 for high schema coverage applies.

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

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

The description states a specific verb ('Generate'), a concrete deliverable ('runnable curl, JavaScript, and Python samples'), a scope ('for every operation'), and two quality guarantees ('path params filled in' and 'realistic body'). This is far from a tautology and clearly distinguishes the tool from all listed siblings, none of which hint at code generation.

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 purpose is self-evident: when you need code samples for API operations. However, there is no explicit statement of when to use this tool versus alternatives (e.g., mock_payloads for payload-only generation) or any guidance on when not to use it. The usage context is implied but not spelled out.

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 explains the output concept (comparative metrics) but does not disclose any side effects, data freshness, or access requirements. It adds value by explaining the meaning of the output, but lacks behavioral details like whether it's read-only or requires specific permissions.

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

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

The description is concise and front-loaded with the key purpose. It uses a clear structure and avoids fluff. The final sentence adds context but is not redundant. It earns its place by explaining why the output matters.

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 (comparative metrics) and lack of output schema, the description provides a good conceptual overview but omits practical details like the format of the index, how to interpret rank/percentile, or any prerequisites. It is adequate but not complete for an agent to fully understand the return value.

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 only parameter 'slug' is undocumented. The description does not explain what 'slug' refers to (e.g., company identifier) or how to obtain it. With a single required parameter and zero coverage, the description should compensate but does not.

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

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

The description clearly states the tool provides a company's investment dimensions with comparative metrics (median, mean, max, rank, percentile, index) against a measured cohort. It distinguishes from siblings like company_peers and company_signals by focusing on dimension scores relative to a cohort, though it doesn't explicitly name alternatives.

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

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

The description implies usage when one needs to interpret raw dimension scores, but it does not explicitly state when to use this tool versus alternatives like company_peers or insights_dimensions. It lacks explicit when-not-to-use guidance or alternative tool references.

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

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

No annotations are provided, so the description must fully disclose behavior. It only states the output is 'weakest investment dimensions' and includes 'Pro' (possibly indicating access level), but does not describe side effects, auth requirements, or data freshness.

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

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

The description is too brief, providing only a noun phrase and the word 'Pro'. While concise in length, it lacks substantive information and does not efficiently convey required context.

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

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

With only one parameter and no output schema, the description must explain both input semantics and result structure. It fails to do so, leaving the agent unable to determine valid inputs or expected 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 single parameter 'slug' has 0% schema description coverage. The description does not explain what a slug represents (e.g., company identifier), how to format it, or where to find it.

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 it returns 'a company's weakest investment dimensions', but lacks an action verb like 'get' or 'list'. The phrase 'Pro' is ambiguous. Compared to sibling tools like 'find_company_insights' and 'insights_dimensions', it does not clearly distinguish its specific purpose.

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

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

No guidance on when to use this tool versus alternatives (e.g., 'find_company_insights' or 'insights_dimensions'). There is no context about prerequisites, input slug meaning, or expected 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?

With no annotations provided, the description carries the full burden and does a good job: it explains the sub-sector-to-industry fallback behavior and the fact that the response will state which basis was used. It also tells the agent that each result carries signal totals and top dimensions, which goes beyond the minimal input 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 a single information-dense sentence with no filler. It packs purpose, the selection fallback, output composition, and a note about the response basis into minimal words, and the key idea is front-loaded.

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

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

The description is reasonably complete for a small input-schema tool: it tells the agent what data is returned and how peer selection works. The main gap is that limit is not described and there is no explicit guidance about when to choose this tool over related sibling tools.

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

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

Schema description coverage is 0%, and neither the input schema nor the description clarifies the limit parameter's role. 'slug' is somewhat inferable from 'this one', and the general purpose implies it is a company identifier, but limit is left completely undocumented in prose.

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 what the tool returns: the companies most comparable to a given company. It goes well beyond a tautology by explaining the comparability rule (same sub-sector where supported, same industry otherwise) and by naming output content like signal totals and top dimensions, which distinguishes it from sibling company_* 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 usage context is implied rather than explicit: it seems intended for retrieving peer companies for a given company, but it does not say when to prefer this over siblings like company_dimensions, company_signals, or find_related. It also provides no exclusions, prerequisites, or 'not for X' 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 carries full burden. It does not disclose whether this is a read-only operation, any side effects, or access restrictions (the 'PRO' prefix might imply a paywall but isn't explained). Its behavior beyond returning data is opaque.

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

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

One sentence with no fluff, but it's structured as a noun phrase rather than an action-oriented instruction. The 'PRO —' prefix is cryptic and not explanatory. It's concise but not effectively front-loaded with a clear verb.

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 one param, no output schema, and no annotations, the description should provide more: what the output looks like, how the slug is used, what 'radar ring' means, and whether it's read-only. The description is too sparse to give an agent sufficient context for correct invocation.

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

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

The description says nothing about the 'slug' parameter; with 0% schema description coverage, the description should compensate. It doesn't even hint that slug refers to a company identifier. The only clue is the tool name 'company_signals'.

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 a specific resource ('the company's adopted stack entity by entity') and what it provides (adoption counts and radar ring). It distinguishes from siblings like find_tools or find_services by focusing on the company-level stack with cohort adoption metrics. However, it's phrased as a noun phrase rather than a verb phrase, so it's not instantly obvious it's a retrieval 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?

No guidance on when to use this versus alternatives such as find_tools, find_services, or company_dimensions. It doesn't explain the context or exclusions. The reader is left to infer based on the resource name.

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

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

With no annotations provided, the description carries the burden of explaining behavior. It does disclose the core selection logic: peers run the item and the company does not, ranked by how many peers carry it. Still, it does not describe output shape, pagination, edge cases, or read/query limitations.

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

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

The description is extremely concise: two sentences that immediately define what the tool returns and who it is for. Every phrase earns its place, and there is no redundant repetition of the tool name or schema.

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 is adequate for a simple ranked-list tool and gives a clear use case, but it is not fully complete: with no output schema and no annotations, the agent still lacks a clear expectation of the returned record shape and the exact semantics of slug/limit.

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 adds little parameter-level guidance. It relates 'this company' to the slug parameter only implicitly, and it does not explain how limit affects the ranked list or what slug values are acceptable.

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 output: it lists what the company's peers run that the company does not, ranked by peer adoption. It also adds a strong use-case framing: 'The opening list for a vendor selling into the account.' It is not a full 5 because it lacks an explicit imperative verb and does not distinguish this from sibling tools like company_gaps.

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 gives a clear audience and context: a vendor selling into the account should use this as the opening list. However, it provides no explicit when-not-to-use guidance or alternatives among the many sibling tools, so an agent must infer when this is preferred over similar company/peer/gap 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 responsibility for behavioral disclosure. It implies a read-only analysis operation but does not confirm side effects, output format, or any error conditions. The informal phrase about breaking consumers hints at impact but leaves behavioral traits ambiguous.

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 short sentences with no filler, and the core action is front-loaded. The second sentence is slightly cryptic but still succinct. It earns a high score for efficiency, though not the highest due to the figurative language.

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 one parameter and no output schema. The description states what is reported but not the format or any caveats. For a single-parameter tool this is mostly adequate, but it lacks details that would help an agent use the result 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?

The schema covers the single parameter (document) at 100%, describing its accepted types and purpose. The tool description adds no additional semantic context about parameter usage, so it stays at the baseline for high schema coverage.

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

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

The description clearly states a specific action (report) and resource (deprecated operations) plus a distinguishing criterion (whether they announce a sunset). It is not a tautology and gives the agent a concrete idea of what the tool does, though it doesn't contrast with siblings like audit_pipeline or api_coverage.

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 a focus on deprecation analysis but does not state prerequisites, when to avoid it, or what distinguishes it from sibling functions. The agent must infer when this is the right choice.

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

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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It omits critical behaviors: how inputs are supplied (file paths, content strings, objects), the output format (since no output schema exists), or whether the operation is read-only. The description only states the what, not the how.

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

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

The description is a single, well-structured sentence that front-loads the primary action and outcome. No filler or redundant phrases; every clause adds useful context.

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

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

Given the tool's complexity (multiple granularities) and the absence of an output schema, the description should clarify both input format and expected output structure. It does not explain how to pass the OpenAPI versions (string or object meaning) or what the classification result looks like, leaving the agent with gaps for successful 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 coverage is 100%, and both parameters (old and new) already have descriptive schemas with aliases. The description adds no parameter-specific detail beyond reinforcing that they are OpenAPI versions, so it does not meaningfully enhance the schema's semantics.

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

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

The description clearly states a specific action ('Compare') on a specific resource ('two OpenAPI versions') and the classification outcome (breaking, non-breaking, addition) with granularity levels. This distinguishes it from other API-related siblings and leaves no ambiguity about what the tool does.

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

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

The description implies the use case (comparing API versions) clearly, and the context is unambiguous. However, it does not explicitly mention when not to use it or point to alternative tools like validate_api or api_coverage, so it lacks explicit exclusions.

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

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

With no annotations provided, the description carries the full burden. It discloses that it returns both the authoritative company count and the nameable companies, and mentions that the basis difference is explained. This goes beyond a simple 'get companies' and alerts the agent to the dual output nature. However, it does not mention any operational constraints like rate limits, data freshness, or the effect of the limit parameter beyond what is in the schema.

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

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

The description is concise, with three sentences that front-load the unique value proposition. The use of all-caps 'PRO — THE INVERSION' is attention-grabbing but arguably excessive; still, it makes the core differentiator immediately apparent. The description wastes no words and clearly explains the purpose and distinctiveness, though the tone is somewhat promotional.

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 (prospecting query with dual return types), the description provides a clear idea of what to expect: both the authoritative count and nameable companies, with the basis difference explained. It does not document pagination or the effect of the limit parameter, but the limit parameter is present in the schema. Since there is no output schema, the description adequately covers the return semantics, though it could mention how 'industry' filtering affects the count versus the named companies.

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

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

The schema already describes 'slug' and 'industry' (50% coverage), and the limit parameter is self-explanatory. The description references the kind parameter via 'service, tool, standard' and clarifies the 'industry' usage via 'broken down by industry'. It does not add meaningful semantics for the 'limit' parameter, and the description does not provide syntax examples or deeper parameter relationships. Given the schema coverage is exactly 50% (not high, not low), the description adds some but not substantial value beyond the schema.

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

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

The description clearly states the tool's function: it runs stack-to-companies as opposed to the sibling tools' company-to-stack direction. It explicitly names the resources (service, tool, standard) and the output (companies showing demand, broken down by industry). This differentiates it from all sibling insights 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 a strong usage context: 'the prospecting query — who should I be selling this to'. It contrasts with siblings by stating every other tool runs company -> stack, implying this is for stack-first queries. It does not explicitly list when-not-to-use cases, but the clear directional inversion and prospecting label serve as a distinct guideline.

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

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

With zero annotations, the description carries full behavioral burden. It discloses what gets produced (four artifact types), which is valuable. However, it never clarifies the operational semantics of 'export' — whether it writes files, returns a payload, or mutates state. Side effects, authentication needs, and failure behavior (e.g., invalid ruleset handling) are all unspecified.

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 dense sentence with zero filler. The verb and resource are front-loaded, the output list is concrete, and the purpose clause earns its place by differentiating the tool from lint-time approaches. Slightly dense due to the four-item em-dash list, but every clause contributes.

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

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

With no output schema and no annotations, the description must cover returns and side effects itself. It enumerates the output artifacts, which mitigates the missing output schema, but leaves operational details open: input format expectations for the Spectral ruleset, persistence behavior, and return structure. In a 50+ sibling toolset with several governance tools, sharper operational clarity would be needed for full completeness.

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

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

Schema description coverage is 100%, so the schema already documents the sole parameter well: it's a Spectral ruleset overriding the catalog default, with rationale ('Score against rules you never adopted means little'). The tool description doesn't add parameter-level detail beyond that, which is acceptable at the baseline 3 since the schema does the heavy lifting.

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

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

The description states a specific verb ('Turn') and resource ('governance ruleset') and enumerates four concrete output artifacts (AGENTS.md block, system-prompt set, per-rule remediation pack, digest). The purpose clause ('so agents follow the rules while authoring, not after linting') clearly distinguishes it from governance_report, govern_estate, and validate_api siblings since it produces actionable authoring-time guidance rather than metrics or validation results.

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 when to use the tool via 'while authoring, not after linting,' suggesting it complements linting-style tools like validate_api. However, it never explicitly names alternatives, states when NOT to use it, or gives conditions for choosing between this and governance_report or govern_estate. Usage guidance is implied but left to inference.

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 describes the nature of the objects (topic areas, subsites) but does not disclose behavioral traits such as read-only/read-write, authentication requirements, rate limits, pagination behavior, or what happens with missing data.

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, front-loaded with the key number (77) and examples, making it highly concise and efficient.

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

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

Given the complexity (7 parameters, no output schema, low schema coverage), the description is severely incomplete. It does not cover parameter usage, return values, or any behavioral context, leaving the agent with insufficient information 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 description coverage is only 29% (only 2 of 7 parameters have descriptions). The tool description adds no parameter meaning beyond what the schema provides, failing to compensate for the low coverage. Parameters like sort, page, limit, fields, match are left completely 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 that the tool finds the 77 focused topic areas of the network, with examples (agents, gateways, security), and notes each is a subsite with its own catalog. This distinguishes it from sibling 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?

The description implicitly indicates this is for locating topic areas, and sibling tool names (e.g., find_tags, find_tools) suggest when to use alternatives. However, no explicit when-not or alternatives are stated, so it doesn't achieve a 5.

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 only mentions searching by type and lists counts, but does not describe pagination, sorting, filtering behavior, or that it returns a list of building blocks. The agent lacks info on result structure and 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 listing types and counts, which is concise and front-loads the key purpose. However, it could be slightly more structured 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 8 parameters, low schema coverage, no output schema, and the tool's complexity as a search function, the description is insufficient. It omits pagination, sorting, match logic, and field selection, leaving significant gaps for the agent.

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

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

Schema description coverage is only 25% (2 of 8 parameters have descriptions). The description adds no parameter details beyond listing allowable types. It does not explain 'q', 'page', 'sort', 'limit', 'match', or 'fields', leaving the agent to guess their meaning.

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

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

The description clearly states the tool searches governance building blocks by type, listing all types with counts. It identifies the specific resource (governance building blocks) but does not differentiate it from other search sibling tools like find_papers or find_posts, which also search by similar parameters.

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 prerequisites, and no exclusion criteria. It only states the basic function, leaving the agent to infer usage context.

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

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

No annotations provided. Only behavioral disclosure is that it is free and likely read-only (browse). No mention of pagination, rate limits, or behavior on empty results. Description carries full burden but adds minimal context.

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

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

Very concise single sentence, front-loaded with purpose. However, could be slightly more structured (e.g., list parameters) 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?

With 3 parameters, no output schema, and no annotations, the description is too brief. Lacks details on return format, sorting, filtering beyond name, or how ranking works. Incomplete 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 coverage 0% and description does not explain parameters. Implicitly maps q to 'by name', but no details on page or limit. Parameter semantics are entirely missing.

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

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

Description clearly states verb (browse/find), resource (profiled companies), and specifics (Fortune 1000 + API providers, ranked by technology-readiness signal). It is distinct from siblings like find_tags or get_company_insight.

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 siblings like get_company_insight. Only mentions it's free, but no context on prerequisites or alternatives.

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

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

No annotations provided, so the description must disclose behavioral traits. It only states the purpose but fails to mention read-only nature, pagination, sorting, or any side effects. The agent lacks critical behavioral context.

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

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

Single sentence, concise and front-loaded with purpose. However, it could efficiently add more detail 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?

No output schema or annotations; description is too sparse for 7 parameters. Lacks details on search behavior, result structure, and constraints, leaving agents underinformed.

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 described). The description adds no parameter-level information, failing to compensate for undocumented fields. Agents get minimal help understanding parameters like sort, match, or fields.

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 conversations, specifically recorded discussions with API practitioners, including guest and company details. It distinguishes from sibling tools like find_videos or find_posts by focusing on conversations, though no explicit 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?

No guidance on when to use this tool versus alternatives like find_videos or find_posts. Agents have no context on which tool to select for searching conversations vs other content types.

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 present, so the description must carry behavioral context. It mentions 'Free' and hints at a read-only browsing operation, but does not state side effects, rate limits, or pagination behavior. The description does not contradict any annotations (none exist), but could be more explicit about 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 concise and well-structured, using two sentences to convey purpose, context, and a pointer to a complementary tool. It avoids verbosity while providing relevant information without unnecessary detail.

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 gives enough to understand the core functionality and relationship to another tool, but it lacks details about output format, ordering, or parameter effects. Since no output schema is provided, some return expectations are unspecified, but the description is not severely incomplete for a simple browse 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 (only 2 of 5 parameters have descriptions: q and min_companies). The description does not explain kind, page, or limit, nor does it elaborate on how ranking works or how parameters affect results. With less than 50% coverage, the description should compensate but does not, leaving these parameters ambiguous.

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

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

The description clearly states the tool's purpose: browsing the demand-side entity catalog, which includes services, tools, and standards, ranked by how many companies carry them. It distinguishes this tool from siblings by focusing on entities and explicitly mentions the inversion relationship with entity_demand.

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 usage context: it mentions the 'left-hand side of the inversion' and suggests calling entity_demand afterward, which guides when to use this tool. However, it does not explicitly contrast with other find_* tools, but the focused entity scope gives sufficient 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 carries the full burden. It states the tool is 'Free' (suggesting no cost) and implies it returns measured data, but it does not mention pagination behavior, output structure, or any side effects. 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 extremely concise: two sentences. The first clearly states what the tool does, and the second adds a key distinction and a cost note. No filler or 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 a pagination-only schema, no output schema, and no annotations, the description provides the essential contrast with find_standards but lacks details on what the returned items look like (e.g., whether they include the measured properties). It mentions the measured attributes (repositories, maturity, etc.) but does not describe the result shape. It is adequate but not comprehensive.

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

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

Schema description coverage is 0%, so the description must compensate for the two parameters (page, limit). It does not mention them at all, nor does it explain any other behavioral details like sorting or defaults. The parameters are common pagination fields, but the description provides no guidance on their usage or expected values.

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 standards bodies that have been measured, with specific attributes (repositories, maturity, governance, coalition). It explicitly distinguishes from sibling tool find_standards, which searches catalog entries. This is a specific verb-resource pair with clear 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?

The description explicitly contrasts with find_standards, telling the agent when to prefer this tool (when measured data is needed vs. catalog lookup). It doesn't mention other potential alternatives like standard_repositories or standard_coalition, but the primary alternative is addressed well.

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 must carry behavioral transparency. It states the content type ('single-PDF deep dives') but omits key behaviors: return type (list of papers?), pagination behavior, read-only nature, auth/permissions, or effect of sort/match. An agent cannot predict side effects or response shape.

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 well-structured sentence that front-loads the resource type and unique attribute. No fluff; each word earns its place. It is concise without being cryptic.

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 7 configurable parameters)Skip, no annotations, and no output schema, the description is heavily underspecified. It omits return format, pagination defaults, match semantics, field selection, and any cautions. It provides only a loose content description, leaving the agent to infer behavior entirely from parameter names.

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 q and tags (2 of 7 fields, ~29%). The description adds nothing about page, sort, match, or fields. With low schema coverage, the description should compensate, but it doesn't clarify any parameter or filtering behavior beyond what's in the schema.

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

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

The description clearly identifies the resource ('API Evangelist papers') and adds a distinguishing characteristic ('single-PDF deep dives... with outlines'). The verb is implicit in the tool name, but the noun is specific and well-defined. It does not reference sibling tools to clarify differentiation, but the purpose is unambiguous.

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

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

There is no guidance on when to use this tool vs alternativesate. No mention of scenarios, exclusions, or relationships to other tools (e.g., find_posts or find_solutions). The description is descriptive, not prescriptive.

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 basic filtering capabilities but does not mention behaviors like pagination, rate limits, or response structure. Minimal transparency beyond the purpose.

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 of 15 words. It is front-loaded with the verb and resource, with no redundant information. Every word is necessary.

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

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

With 8 parameters, no output schema, and no annotations, the description is insufficiently complete. It covers only the core purpose and two filters, leaving out details on pagination, sorting, field selection, and expected 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 only 25%, with only 'q' and 'tags' having schema descriptions. The description mentions filtering by 'year' and 'tags', adding some value, but fails to explain seven other parameters (page, sort, limit, match, fields, year is mentioned but not detailed). This does not adequately compensate for the 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?

The description clearly states the verb (search/browse), the resource (API Evangelist stories), and the scope (5,100+ stories from 2010-present). It distinguishes itself from sibling find_* tools by focusing specifically on 'posts' (stories).

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 or browsing stories but does not explicitly provide when to use this tool versus alternatives. No exclusions or when-not-to-use guidance is given.

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

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

With no annotations or output schema, the description carries the full transparency burden. It does disclose a useful behavioral detail: results are ranked by shared-tag relevance with rare/specific tags weighted more. But it does not describe output shape, pagination, error behavior, or whether the source doc is excluded from results.

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 compact and front-loaded with the core input and output, followed by the ranking heuristic. There is slight redundancy between 'across the whole network' and the later list of content types, but overall every sentence earns its place.

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

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

For a 4-parameter tool with no annotations, no output schema, and 0% schema coverage, the description covers the essential invocation and ranking behavior but leaves valid gaps: the meaning of 'limit' and 'types' is not stated, and the return structure is not described. It is adequate for basic use but not fully complete.

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

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

Schema description coverage is 0%, so the description must explain the parameters. It usefully clarifies that 'type' and 'slug' together identify a document, but it provides no explanation for the 'limit' or 'types' parameters, leaving significant ambiguity for optional filtering and result size.

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 defines a specific operation: given a doc identified by type and slug, return the most related content across the network. It also distinguishes itself from sibling find_* tools by emphasizing cross-type relatedness ('across stories, areas, guidance, papers, conversations, and more') rather than a single content type.

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 phrase 'More like this' implies the intended use case: when you have a document and want related content across types. However, it does not explicitly contrast with sibling tools like find_papers, find_conversations, or find_tags, nor does it state when not to use it.

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

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

No annotations are provided, so description bears full responsibility. It implies a read-only search operation but does not explicitly state behavioral traits such as idempotency, side effects, authentication needs, or rate limits.

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

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

Description is concise (single sentence plus parenthetical) and front-loaded with purpose. Could be more structured but avoids unnecessary verbosity.

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

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

With 7 parameters, no output schema, and no annotations, the description omits essential details like pagination, sorting, field selection, and return format. It is inadequate for an agent to effectively invoke the tool.

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

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

Schema description coverage is only 29% (2 out of 7 parameters have descriptions). The tool description adds no parameter-level information, failing to compensate for the low coverage and leaving meaning of most 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?

Description clearly states the tool finds services offered by API Evangelist, listing specific categories (strategy, governance, etc.) and explicitly distinguishes it from the sibling tool find_solutions for vendor registry.

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 to use find_solutions for third-party vendor registry, giving context on when this tool is appropriate as the 'front door' to API Evangelist services. Does not mention other alternatives 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 present, so the description must disclose behavioral traits. It fails to state that the tool is read-only, describe pagination, or mention rate limits. The description only provides a high-level overview of the registry content.

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 (one sentence), but it sacrifices important details. It is appropriately sized for a brief overview but could be restructured to front-load key search capabilities.

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 severely incomplete. It does not explain search behavior, return format, pagination limits, or how to use filters 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 only 29%, and the description does not explain any parameters. It adds no meaning beyond the schema's minimal descriptions, leaving the agent to guess how 'q', 'tags', or 'fields' affect results.

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 searching a registry of third-party API services and tools, but 'solutions' overlaps with sibling tools like 'find_tools' and 'find_services' without clear differentiation. The purpose is clear but not distinct from 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?

No guidance is provided on when to use this tool versus sibling tools (e.g., find_tools, find_services). The description only states the content of the registry, leaving the agent to infer usage context.

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

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

With no annotations, the description carries the full burden. It discloses that the tool returns tags sorted by count or breadth, explains breadth as 'how many content types use it', and implies read-only browsing. It does not mention pagination behavior, but the schema covers page/limit, so overall transparency is good.

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 front-load the core purpose, then explain search and provide a helpful metaphor. Every sentence adds value without redundancy.

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

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

Given 4 parameters, no output schema, and no annotations, the description covers the main functionality and sorting options. However, it lacks details on the return format (e.g., what fields each tag includes) and pagination behavior, which would aid an agent in using the results.

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

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

Schema description coverage is 0%, so the description must add meaning. It explains 'q' as a search filter and 'sort' with its enum values, including the meaning of 'breadth'. However, page and limit are not described beyond their schema defaults 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?

Description uses specific verb 'browse and rank' and resource 'network tag taxonomy', clarifying it covers all subject tags across 16k+ docs with sorting by frequency or breadth. This clearly distinguishes it from sibling tools like find_areas or find_building_blocks.

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 states 'Search with q' implying use for searching, but lacks explicit guidance on when to use this tool over alternatives (e.g., get_tag for single tags, search_api_evangelist for general queries). No when-not-to-use information 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?

Since no annotations are provided, the description must fully disclose behavioral traits, but it only describes the data content (adoption counts, radar placement). It does not mention that the tool performs a read-only search, any authentication or rate limitations, pagination behavior beyond parameter defaults, or the nature of the response. The lack of behavioral transparency leaves agents unaware of key operational expectations.

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

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

The description is a single, concise sentence that front-loads the core purpose and key features (number of tools, adoption counts, radar placement). Every word serves to inform the agent, with no redundancy or unnecessary detail.

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 7 parameters and no output schema, the description is insufficient for complete understanding. It does not explain how parameters interact, what the return format looks like, or how to effectively narrow searches. Complex query options like 'match' and 'fields' remain unexplained, making the description inadequate for precise agent 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 only 29%, and the description adds no parameter meaning beyond the schema. Only the 'q' and 'tags' parameters have descriptions in the schema; others like 'page', 'limit', 'sort', 'match', and 'fields' are left undocumented. The description does not compensate for this gap, forcing agents to rely solely on parameter types and enum values without context on their effect.

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 registry for open-source tools, specifying it contains 400+ tools with adoption counts and technology-radar placement. It distinctly describes the resource and action (finding tools in the registry), distinguishing it from other 'find_*' siblings that deal with different entities like areas, posts, or services.

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 is provided on when to use this tool versus alternatives. With many sibling 'find_*' tools, the description does not differentiate usage contexts or explain when searching the tool registry is appropriate versus other registries. Users are left to infer from the tool name alone.

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

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

With no annotations (0%), the description must fully disclose behavioral traits. It only indicates 'searchable by transcript', omitting details like pagination behavior (page/limit), sorting, field selection, or error handling. The agent lacks critical behavioral context for correct invocation.

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

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

At 15 words, the description is concise and front-loaded. However, it sacrifices informativeness—for a 7-parameter tool, brevity becomes under-specification. It earns its sentence length but could convey more key details without being bloated.

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, zero annotations, and 7 parameters, the description is incomplete. It fails to specify return format, result structure, or how parameters like 'fields', 'sort', and 'match' affect output. The agent lacks enough information to fully understand tool 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?

Schema description coverage is low (29%). The description adds no parameter meaning beyond what the schema (partially) provides. It does not explain the 'tags', 'match', 'fields', or 'sort' parameters, failing to compensate for the schema's 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's purpose: searching a video library of API interviews and discussions by transcript. It explicitly names the resource ('video library') and the search capability, distinguishing it from siblings focused on other content types (e.g., conversations, papers).

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

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

No usage guidelines are provided. The description does not mention when to use this tool over alternatives (e.g., 'find_conversations', 'find_papers') or specify any exclusions or prerequisites. The agent receives no guidance on selection 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, and the description only mentions 'Filter by category', ignoring pagination, sorting, match modes, or output format. The agent learns little about side effects (likely read-only) or constraints beyond what the schema defines.

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 is efficient, front-loading the tool's scope. However, it omits critical details that could be included without bloating (e.g., a brief note on pagination or match logic).

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 8 parameters (0 required) and no output schema, the description fails to cover pagination, sorting, match behavior, fields selection, or return format. An agent cannot reliably invoke this tool without external knowledge.

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 25% (q and tags have descriptions). The overall description adds no parameter explanation beyond 'Filter by category', which maps to the category enum. It does not clarify sort, match, page, limit, fields, or tags usage.

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

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

The description states the tool covers 'the API vocabulary' and lists content types (resources, actions, etc.), clearly distinguishing it from sibling find_* tools that target specific subdomains (e.g., find_areas, find_building_blocks). However, it lacks an explicit verb like 'search' or 'list', slightly obscuring the action.

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

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

No guidance on when to use this tool vs. alternatives. The description implies generic filtering but does not help an agent decide, e.g., when to use find_vocabulary vs. find_tags. Exclusions and context are missing.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes what the tool produces (design, tools, skills, etc.) but does not mention side effects, whether it mutates input, authentication requirements, error behavior, or the format of the return value. The lack of specification regarding what 'forge' entails—whether it is a pure transformation, requires network access, or returns a single aggregate object—leaves significant ambiguity for an agent.

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

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

The description is a single sentence that efficiently lists the key outputs, front-loading the source ('From an OpenAPI') before enumerating the generated artifacts. It is concise and avoids wordiness, though it packs many items into one clause, making it slightly dense but still readable.

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 complex code-generation tool with no output schema, the description is insufficient. It does not explain the structure of the returned value, whether it is a JSON object with keys for each artifact, or how the artifacts are delivered (e.g., as strings, files, or nested objects). It also omits potential limitations or dependencies, making it hard for an agent to anticipate the tool's behavior and results. More context is needed for correct invocation and interpretation.

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 provides a comprehensive description of the 'document' parameter, covering accepted formats and input variants, so the baseline is 3. The tool description adds only a slight nuance by saying 'From an OpenAPI,' which is actually more restrictive than the schema's broader acceptance of AsyncAPI, Arazzo, and JSON Schema. This introduces a minor inconsistency and does not enhance parameter understanding; it remains at 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's action (forge) and the resource (an MCP server design from an OpenAPI) along with a list of artifacts produced. It distinguishes itself from the sibling tools, which focus on analysis, search, and governance rather than code generation. However, it says 'OpenAPI' whereas the schema also accepts AsyncAPI, Arazzo, and JSON Schema, creating a slight mismatch between the stated scope and actual input types.

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. It does not mention any conditions, prerequisites, or contrast with other tools, leaving the agent to infer that it is for generating MCP server artifacts. This is a notable gap given the large sibling set with overlapping API-related operations.

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 must fully disclose behavioral traits. It mentions 'emit' outputs, implying a generation action, but does not indicate whether it is a read-only operation, requires authentication, or has side effects (e.g., creating files or altering state). The description does not cover safety or destructive potential.

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

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

The description is a single sentence that efficiently conveys the tool's action and outputs. It is front-loaded with the main verb and resource. No unnecessary words are present.

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

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

Given the absence of annotations, output schema, and a free-form input schema, the description is incomplete. It does not explain the expected input format, the behavior of the tool, or what the outputs contain. For a tool that generates multiple artifacts, more context is needed for correct invocation.

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

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

The input schema has no defined properties and allows additional properties, but the description adds no guidance on what the input object should contain. It mentions 'operations and fields' but does not specify format, structure, or examples. Since the schema coverage is effectively 100% (no defined params), the description fails to compensate for the open-ended 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's purpose: 'Choose which operations and fields an API exposes to agents' and 'emit' specific outputs. The verb 'choose' and resource 'operations and fields' are specific, and the tool's function is distinct from siblings, many of which are retrieval or analysis tools. However, the description could be more precise about how the input specifies these choices.

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

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

No guidance is provided on when to use this tool versus alternatives. There are no mentions of prerequisites, context, or exclusions. The description only states what the tool does, not the appropriate usage scenario.

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 is the sole source of behavioral info. It describes the output but does not disclose side effects, required permissions, or whether the tool is read-only or modifies data. The term 'Generate' implies creation but lacks clarity on idempotency or resource 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?

A single, concise sentence that frontloads the main action and lists key content. Every word earns its place with no filler.

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

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

The description explains the tool's output in moderate detail but omits input requirements and broader context (e.g., how the API is specified). Given the lack of output schema, more completeness is needed for an agent to use it correctly. It is adequate but has clear gaps.

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

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

The schema has zero parameters but allows additional properties. The description fails to explain what these properties are or how to specify the API. This omission leaves the agent without necessary input guidance, despite the baseline expectation for zero parameters.

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

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

The description clearly states the tool's function: generating an API's llms.txt and AGENTS.md with specific contents (base URL, auth, operation table, deprecated operations, usage rules). This specific verb+resource combination distinguishes it from sibling tools like api_coverage or export_agent_rules.

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, nor does it mention prerequisites or context. The description does not indicate scenarios where this tool is appropriate or not.

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

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

No annotations provided, and the description does not disclose behavioral traits like permissions, side effects, or limitations beyond the basic purpose.

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

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

The description is short and to the point, but the phrase 'walk the network from here' is somewhat vague, reducing clarity slightly.

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

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

With no output schema and one undocumented parameter, the description should explain what 'related-area graph' entails or the return format, which it does not.

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 single parameter 'slug' has no description in schema or description text; the description adds no meaning about what slug is or how to format it.

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 one topic area with its related-area graph, distinguishing it from sibling tools like 'find_areas' which likely lists areas.

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 need a single area and its network, but no explicit guidance on when not to use or alternatives.

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

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

Discloses that including 'content' returns full body, but does not describe default return structure, error behavior, or other nuances. Without annotations, carries moderate burden.

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 core purpose, no redundant words. Excellent 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?

Adequate for a simple retrieval tool with three params and no output schema. Covers essential lookup and optional full body, but lacks default response details.

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

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

Adds meaning to parameters: slug and type as lookup keys, include as content trigger. Since schema has 0% coverage, this compensation is valuable, though default response is unspecified.

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 the tool retrieves a single building block by type and slug, distinguishing it from sibling 'find_building_blocks' which implies multiple results.

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 like 'find_building_blocks'. The description only states what it does without 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 bears full burden. It only describes what the tool returns, not any behavioral traits like permissions, rate limits, or side effects. The term 'Pro' is vague and uninformative.

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, using a single sentence with a colon-separated list. However, it lacks detail that could be added without significant bloat.

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

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

With 1 parameter, no output schema, and no annotations, the description should provide more context about the return format, prerequisites, or usage. It is insufficient for an agent to use correctly.

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

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

The only parameter, 'slug', has no description in the schema (0% coverage), and the description does not explain what a slug is or how to obtain it. The description adds no value for parameter understanding.

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

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

The description clearly states the tool returns a 'full demand-side profile for one company' and lists specific elements (40-dimension readiness, adopted stack, per-quarter history). This distinguishes it from sibling tools that might provide partial or different perspectives.

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_area or company_gaps. The description does not mention 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. The description doesn't disclose behavioral traits such as whether the result is static, cached, or requires authentication. For a zero-parameter tool, more context on the nature of the output would help.

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 that conveys the purpose efficiently. Front-loaded with key information. No unnecessary 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?

Description is adequate for a simple tool with no parameters and no output schema, but it doesn't specify the format of the returned contact methods (e.g., list of strings). Slightly more detail 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?

Zero parameters, baseline score of 4 as per instructions. Schema coverage is 100%, so no additional parameter meaning is needed.

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

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

The description clearly states the tool returns contact methods for API Evangelist, using a specific verb ('get') and resource ('contact'). It distinguishes from sibling tools (e.g., get_area, get_tag) by focusing on contact info.

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

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

No guidance on when to use this tool vs alternatives like search_api_evangelist. No prerequisites or exclusions mentioned.

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

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

No annotations are provided, so the description must carry the burden. It discloses that include=['content'] returns the writeup, and implies the operation is read-only. However, it lacks details on authentication, 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?

Single sentence front-loading the purpose. No redundant information, but could be more structured by separating core behavior from parameter details.

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

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

Given the lack of output schema and partial parameter coverage, the description provides minimal context. It leaves ambiguity about the format of guest detail and media links. For a simple tool, it is adequate but not comprehensive.

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

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

The schema has 0% coverage, so the description must compensate. It explains the include parameter's effect (returns writeup), but does not describe the slug parameter. This adds some value but not complete.

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 single conversation with guest detail and media links. It mentions the include parameter for content, which differentiates it from other get_* tools like get_post or get_area. However, it could be more explicit about the resource context.

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

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

The description provides no guidance on when to use this tool versus alternatives like find_conversations. It does not mention prerequisites or conditions.

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 indicates the feeds are static and require no authentication ('zero-auth'), which is helpful. However, with no annotations, it omits other behavioral traits such as rate limits, idempotency, or whether the feed content is cached. The transparency is moderate but incomplete.

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

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

The description is a single sentence that conveys core purpose efficiently. It is front-loaded with key information. While concise, it could benefit from a second sentence to clarify output format.

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 zero-parameter tool without output schema, the description adequately explains what the tool returns and its relationship to the broader API. It could be more complete by specifying whether it includes all feeds or a subset, but it meets minimum viability.

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 tool has no parameters, and schema coverage is 100%. The description adds context about the feeds' nature (static, no-key) that goes beyond the empty schema. A baseline of 4 is appropriate as there is no parameter documentation burden.

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 static machine-readable feeds (JSON, APIs.json, zero-auth) and positions it as a no-key alternative. However, it does not specify whether it returns a list of available feeds or the actual feed content, leaving some ambiguity.

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

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. With many sibling 'get_*' tools, it fails to differentiate use cases or mention when a key-based alternative is preferable.

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

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

With no annotations, the description carries full burden. It does not disclose behavioral traits such as whether the operation is read-only, has side effects, or requires authentication. It only states the output is a list, lacking detail on pagination or response structure.

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

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

The description is a single sentence of about 25 words, efficient and front-loaded with the core purpose. It avoids unnecessary words, though it could be more structured.

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

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

Given no output schema and incomplete parameter documentation, the description is insufficient. It covers only the 'section' parameter and fails to explain pagination (page, limit) or the format of the returned list.

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 description must compensate. It lists the six valid values for 'section', adding meaning beyond the enum. However, it provides no information about 'page' or 'limit' parameters, which remain 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 the tool returns one editorial guidance section as a list, listing the six specific section values. It uses a specific verb ('get' implied) and resource, and the mention of 'six lenses API Evangelist organizes guidance through' helps distinguish it from other get_* siblings.

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

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

No guidance is provided on when to use this tool vs alternatives like get_area or get_overview. The description does not indicate context or prerequisites, leaving the agent to infer usage.

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

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

No annotations are provided, so the description carries the burden. It states that the tool returns counts, entry points, and engagement guidance, which is meaningful behavioral information. It does not explicitly state that the operation is read-only or describe response structure, but the 'get' verb and 'returns' phrasing make side effects unlikely.

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 dense sentence with the key instruction front-loaded. The list of content areas is somewhat lengthy but helps an agent understand the scope of the overview.

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 zero-parameter tool with no output schema, the description tells the agent what it will get back (counts, entry points, engagement) and why to call it first. It is complete enough to invoke correctly, though a note on read-only behavior would round it out.

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 tool takes no parameters, so the schema already fully documents the input surface. The description adds useful context about what the returned counts and entry points cover, but no parameter-level detail is needed.

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

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

The description opens with 'START HERE' and clearly identifies the tool as an entry point to the API Evangelist network, listing what it offers and what it returns. This distinguishes it from more specific siblings like get_stats or get_area, though it doesn't name a sibling explicitly.

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?

'START HERE' is an explicit signal that this tool should be the first call an agent makes, providing clear usage context. It does not name alternatives or exclusion conditions, so it stops short of a 5.

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

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

With no annotations, the description partially carries the burden. It indicates a read operation returning a single paper, but lacks details on data freshness, rate limits, or what 'full outline' entails. Adequate for a simple get.

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

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

Extremely concise single sentence, front-loaded. However, it omits important parameter information that could be added without bloating. Otherwise efficient.

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

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

Given the tool's simplicity (single parameter, no output schema), the description is functional but incomplete. It fails to clarify the slug parameter and the scope of 'full outline'. Sibling tools are numerous, but this description does not ensure correct selection.

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' has no description in the schema (0% coverage). The description does not explain what a slug is, its format, or how to obtain it. This is a significant gap.

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

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

The description clearly states the tool returns one paper with its full outline and URL. It distinguishes from sibling tools like find_papers which likely return multiple results. However, the meaning of 'full outline' is vague.

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

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

Implied usage: retrieve a specific paper by slug. No explicit guidance on when to use this versus alternatives like find_papers or get_post. The context is minimal.

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 must disclose behavioral traits. It does not mention whether the tool is read-only, requires authentication, handles errors, or has side effects. The description focuses on input/output but omits safety and operational context.

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

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

The description is a single sentence that efficiently conveys the tool's purpose, key parameters, and output format. No unnecessary 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 annotations, output schema, or parameter descriptions in the schema, the description lacks completeness. It does not describe the return structure beyond 'full markdown body', nor does it cover error conditions, pagination, or related 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?

Schema coverage is 0%, so the description adds meaning: the slug format and the effect of include. However, it does not specify the default behavior when include is omitted or provide full detail on what the response contains beyond the markdown body.

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 one story by slug with a specified format (YYYY-MM-DD-slug), and it explains the effect of the include parameter. This distinguishes it from sibling get_* tools like get_paper or get_video, each targeting different resources.

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

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

No guidance is provided on when to use this tool versus alternatives like find_posts for searching. The description only explains what the tool does, not the context in which it is appropriate.

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

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

No annotations are provided, so the description carries full burden. It discloses that include=['content'] inlines the full pitch, but does not mention any other behavioral traits such as authentication, rate limits, side effects, or what constitutes 'full detail' beyond the include parameter.

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

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

The description is a single, concise sentence that front-loads the primary action and efficiently adds the key parameter behavior. No unnecessary words.

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

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

For a simple getter with two parameters and no output schema, the description covers the essential functionality. However, it could be improved by hinting at the response structure or confirming what 'full detail' includes.

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%, but the description adds meaning to both parameters: slug is the identifier ('by slug'), and include=['content'] is explained as inlining the full pitch. This compensates for the lack of schema descriptions.

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

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

The description clearly states the tool retrieves full detail for one service offering by slug, and includes a specific usage note for the include parameter to inline content. This distinguishes it from sibling getter tools like get_area or get_building_block.

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 versus alternatives; the purpose is implied by the name 'get_service' and the description, but the description does not mention scenarios where other getter tools would be more appropriate.

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?

Given no annotations, the description does not disclose behavioral traits such as whether the operation is read-only, or error handling for missing slugs. It only states what is returned but not 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?

The description is a single, concise sentence of 11 words that communicates the essential information without redundancy.

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

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

Given the low complexity (one parameter, no output schema), the description adequately covers the tool's purpose and output fields. However, it could be more complete by specifying the response format or adding error behavior, but it is 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?

With 0% schema description coverage, the description compensates by explaining that the slug parameter identifies the solution and that the response includes website and adoption count. This gives meaning beyond the bare parameter name.

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 single solution from the vendor registry identified by slug, and specifies the included fields (website, adoption count). This distinguishes it from the sibling find_solutions which likely returns multiple solutions.

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 vs alternatives like find_solutions. It does not mention prerequisites or context 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 for behavioral disclosure. It only describes output content and does not mention whether the operation is read-only, has side effects, requires authentication, or has rate limits. The 'PRO' label indirectly suggests authentication but is insufficient.

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

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

A single, well-structured sentence (15 words) with a clear label 'PRO — catalog intelligence' and a colon-separated list of outputs. No wasted words; every part contributes meaning.

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 simplicity (no params, no output schema), the description is minimally adequate but lacks details on output format, pagination, or examples. The terms 'per-type counts' and 'top tags by reach' are vague. For a tool with many siblings, more context would help an agent decide when to use it.

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

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

The tool has zero parameters, so the description cannot add parameter-level semantics. Per guidelines, baseline is 4. The description does add value by explaining what the tool returns, which helps the agent understand the output without needing to infer from an empty 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 provides catalog intelligence with specific outputs (per-type counts, stories-per-year, top tags by reach). It distinguishes from siblings like get_area or get_tag by focusing on aggregate stats rather than individual entities. However, it does not explicitly use a verb like 'get' or 'retrieve', which slightly reduces clarity.

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

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 api_coverage or company_gaps. The 'PRO' label hints at premium access but is not explicit. There is no mention of prerequisites, restrictions, or when not to use it.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does explain the scope ('across the whole network') and the contents (counts and labeled items). However, it does not mention pagination despite page and limit parameters, and 'everything it labels' could mislead an agent into expecting a single unbounded response when the schema defaults to limit=25.

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, dense sentence with no filler. It front-loads the primary purpose ('One tag') and immediately gives useful scope and filtering details.

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 annotations, no output schema, and 0% schema description coverage, the description should do more. It covers the core purpose and types filtering, but omits pagination behavior, response shape, and any guidance on which sibling tools might serve alternative 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 0%, so the description must compensate. It does add meaning for the 'types' parameter as a filter and implies the slug identifies the tag. But it does not explain page/limit semantics or enumerate valid type values, leaving significant parameter meaning to inference.

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 single tag ('One tag') and specifies what it returns: per-type counts and everything the tag labels across the network, with examples of content types. It also distinguishes this from sibling tools like find_tags and other get_* tools by focusing on a single tag entity.

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 gives clear context for use: retrieve one known tag with its associated counts and labeled items. The phrase 'Filter with types' signals an optional refinement. However, it does not explicitly name alternatives or say when not to use this tool, so it falls just short of a 5.

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

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

No annotations present, so the description must disclose behavioral traits. It mentions 'chronological order' but does not specify that the tool is read-only, how results are paginated, or any other side effects.

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

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

The description is a single sentence that packs the enum options in a list, which is somewhat structured but could be more concise by splitting into separate points.

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

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

No output schema, no mention of return format (e.g., list of events), and missing pagination details. Given the number of sibling tools, more context is needed to guide agent selection.

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 explain all parameters. It only describes the 'timeline' enum values, leaving 'page' and 'limit' unexplained despite their defaults and constraints suggesting pagination.

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 'get' and resource 'timeline', and enumerates the four specific timelines (api, resources, industries, people), distinguishing it from sibling tools that fetch individual entities.

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

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

No guidance on when to use this tool versus alternatives; it only lists the timeline options without explaining contexts or exclusions.

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

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

No annotations are provided, so the description carries full burden. It lists returned fields but omits behavioral traits such as auth requirements, side effects, or read-only nature. Only discloses output shape minimally.

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 of 14 words, perfectly concise and front-loaded. No waste.

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

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

For a simple single-parameter tool without output schema, the description covers basic purpose and return fields. However, it lacks usage guidance and parameter details, leaving gaps for an agent to fully understand 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?

The sole parameter 'slug' is not explained beyond 'by slug'. With 0% schema description coverage, the description fails to define what a slug is or provide format/examples.

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 the tool retrieves a tool from the tooling registry by slug, specifying the returned fields (website, adoption count, radar ring). Distinguishes from sibling tools like get_area or get_post by targeting the tooling registry.

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_tools or other get_* tools. Does not mention prerequisites or contextual 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 must disclose behavioral traits. It mentions the optional include parameter and its effect, but does not state whether the tool is read-only, requires authentication, or any other side effects. The name implies read-only, but it's 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, front-loaded sentence of 12 words with no filler. Every part serves a purpose, stating the core functionality and the optional behavior.

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

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

For a simple get-by-id tool, the description covers the main action and the optional transcript retrieval. However, it lacks definition of the slug parameter and does not describe what the tool returns (beyond the transcript aspect). With no output schema, more detail would be helpful.

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%, so the description must compensate. It explains the include parameter (enum 'content' returns transcript), but does not describe the slug parameter (what kind of slug, format?). The explanation adds some value but is incomplete.

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 that the tool retrieves a single video by slug and can optionally return the full transcript via the include parameter. The verb 'get' and resource 'video' are specific, and it distinguishes itself from sibling tools like 'find_videos' which likely handles listing.

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 video slug and need details or transcript, but it does not explicitly state when to use this tool versus alternatives (e.g., find_videos for searching). No when-not-to-use guidance is provided.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It conveys the output nature (a self-contained HTML report) but says nothing about side effects, whether the operation writes files or performs network calls, or if it is a pure read-only transform. Since the tool mutates input into a persistent artifact, the lack of any side-effect disclosure is a meaningful gap.

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 efficient sentence that front-loads the verb, resource, and output format. The only slightly wasteful element is the vague 'framed toward progress,' which adds tone but little actionable meaning; otherwise there is 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 tool of this low complexity — one documented parameter, no output schema, no nested objects — the description covers the essential facts: the input type, the output format, and the report's structure. The main residual gap is the ambiguous 'framed toward progress' and the absence of any statement about whether the operation is side-effect-free, but these are minor given the tool's simplicity.

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

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

Schema description coverage is 100%, and the schema already documents the sole parameter well, including that it may accept an array or the `{ results: [...] }` wrapper object. The description adds only general context ('Spectral findings'), not new meaning beyond the schema, so the baseline 3 is appropriate.

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

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

The description names a specific operation — turning Spectral findings into a self-contained HTML governance report — with a concrete output format and content outline (severity summary, grouped by rule). This distinguishes it from report-adjacent siblings like api_scorecard and audit_pipeline. The phrase 'framed toward progress' is vague and slightly muddies the scope, so it stops short of a 5.

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

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

Usage is implied rather than stated: an agent can infer it is used after a Spectral run to produce an HTML report, but the description never explicitly says when to choose it over alternatives such as api_scorecard, govern_estate, or audit_pipeline. There is no when-not guidance or mention of exclusions, so the routing burden falls on inference.

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

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

Since no annotations are provided, the description carries the full burden. It discloses the output structure (per-API results, aggregates, punch-list) and mentions 'PRO' implying possible access constraints. But it does not state whether the operation is read-only, if it modifies anything, or address performance implications of running on many APIs—an important gap for a heavy roll-up 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 is compact and front-loaded with the core action ('Run the core governance checks across a WHOLE SET...'), followed by output details and invocation notes. Each sentence adds value; 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 no output schema, the description must fully define the return and usage context. It covers the main outputs and inputs, but lacks details on `ruleset` format, limits on API count, error behavior, or what 'dimensions' are added by `detail`. As a complex tool, these gaps could lead to misuse.

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 documents only `apis` with a description, and the description adds detail on its structure ([{id, document}]) and that `document` alone is accepted. It also introduces `ruleset` and `detail` which are not in the schema (though additionalProperties allows them), but gives only cursory mention—no types or format for `ruleset`, and `detail` is just a boolean flag without further explanation.

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 runs governance checks across a whole set of internal APIs and rolls them up, listing specific outputs (per-API score/grade/errors/PII, estate aggregates, punch-list). It distinguishes from single-API tools by emphasizing 'whole set' and 'roll them up', though it doesn't explicitly name alternative siblings like governance_report.

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 invocation guidance: pass `apis` and `ruleset`, and `detail:true` adds per-API dimensions. However, it doesn't state when to use this vs alternatives (e.g., governance_report for a single API or other scoring tools), nor what conditions trigger its use over siblings.

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

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

No annotations are provided. The description does not disclose any behavioral traits such as whether the tool is read-only, requires authentication, has rate limits, or the cost/complexity of generation.

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 key purpose and includes a bullet-style list of bundled items, making it informative without being overly 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 there is no output schema, the description adequately explains what the guide contains (topics, rules, papers, services). For a single-parameter tool, it provides sufficient context for an AI agent to understand the return value.

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 single parameter 'topic' has a schema description, but the tool description enriches it by listing example topics and explaining that the guide bundles related areas, rules, papers, etc.

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

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

The description clearly states the tool's purpose: 'PRO — Curated guide to one API topic', with specific examples like 'gateways', 'api governance'. It differentiates from siblings by specifying it bundles multiple related resources into a guide.

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 tool should be used to obtain a curated guide for a specific topic, but it does not specify when not to use it or mention alternatives among the many sibling tools.

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

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

No annotations are provided, so the description must carry the behavioral burden. It only mentions 'Free' but does not disclose pagination behavior, data freshness, or any side effects. The description lacks necessary behavioral context beyond the input 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 a single sentence, which is concise but at the expense of missing critical information. It is appropriately short for a simple tool but lacks structure and completeness.

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

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

Given the tool has 3 parameters, no output schema, and no annotations, the description is far too minimal. It does not explain return format, sorting order, filtering options, or any other contextual details needed 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%, and the description does not add any meaning to the three parameters (page, type, limit). The type parameter's enum values are implied in the description ('services, tools, or standards') but not explicitly mapped, and no other parameter behavior is explained.

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 returns services, tools, or standards ranked by adoption, which is a specific verb-resource combination. It distinguishes from sibling tools like 'find_services' or 'find_tools' by emphasizing ranking by adoption, but not explicitly compared with 'insights_dimensions'.

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. It mentions 'Free' but that is about cost, not usage context. No when-not or alternatives are mentioned.

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

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

No annotations are provided, so the description carries the full burden. It only says 'Free', which is ambiguous regarding read-only, auth needs, or side effects. It does not disclose any behavioral traits beyond being possibly cost-free.

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 (one sentence plus 'Free'), which is concise but too brief to be fully informative. It front-loads the core purpose but omits necessary details.

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 simplicity (2 optional params, no output schema), the description is incomplete. It does not explain return values or how the ranking is presented. The tool's function is hinted but not fully fleshed out.

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 the parameters (page, limit) at all. The parameter names are somewhat self-explanatory, but the description adds no value beyond the schema's structural definition.

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 ranks 40 investment dimensions by company signal. It uses a specific verb ('ranking') and resource ('dimensions'), making the purpose clear. However, it does not explicitly differentiate from siblings, though the focus on dimensions is unique among the listed tools.

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

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

The description provides no guidance on when to use this tool versus alternatives. The mention of 'Free' is a status note, not usage context. No prerequisites or situational advice 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?

No annotations are provided, so the description carries full burden for behavioral traits. It mentions outputs (scorecard and flow map) but does not disclose whether the tool is read-only, has side effects, or requires authentication. 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?

The description is a single, well-structured sentence that front-loads the key action and outputs. Every word adds value; no redundancy.

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

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

Given no output schema and no parameters, the description provides a high-level view but lacks details on the output format, coverage scorecard specifics, and how the flow map is delivered. More context on expected 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?

There are zero parameters, so schema coverage is trivially 100%. The description does not need to add parameter information. Baseline score of 4 is appropriate.

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

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

The description clearly states the verb 'Map' and the resource 'REST operation to its MCP tool and Agent Skill', specifying the chain from APIs.json and outputs a scorecard and flow map. It distinguishes itself from sibling tools like api_coverage and api_scorecard by focusing on the mapping process.

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

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

No guidance is provided on when to use this tool versus alternatives. The description implies its purpose but does not explicitly state conditions, 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?

With no annotations provided, the description carries the full behavioral burden. It conveys that this is a non-destructive generation operation, but discloses nothing about error handling for invalid or unsupported schema types, whether all operations are always covered, or scale implications of processing an entire document.

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, efficient sentence with no wasted words and the action verb front-loaded. It is appropriately compact, though the brevity leaves room for additional useful context without bloating.

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

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

Adequate for a single-parameter tool with 100% schema coverage: the description usefully spells out the return value (request and success-response payloads), partially compensating for the missing output schema. Gaps remain in usage context and edge-case behavior, but the simplicity of the tool keeps this from being 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 100%, so the schema already documents the document parameter fully (format, supported spec types, accepted forms). The description adds only marginal context — that payloads are generated 'for every operation' — which slightly reframes the parameter's role but adds no new syntax or format detail.

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 a specific verb ('Generate') and names the resource ('example request and success-response payload for every operation'), making the tool's purpose clear and distinguishable from siblings like code_snippets (code generation) and validate_api (validation). It loses one point for not being more precise about what counts as an operation or how different spec types are handled.

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 given on when to reach for this tool versus alternatives. The sibling code_snippets exists as a natural alternative for producing usage examples but is never mentioned, and no exclusions or preferred contexts are stated.

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 transparency burden. It does disclose the core behavior (suppresses, surfaces, returns) and the return value's significance, but it does not state whether the tool mutates the waivers file, requires any permissions, or how the returned set is structured. These are meaningful gaps for a reconciliation 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?

Two sentences, front-loaded with the purpose and followed by the key return semantic. Every phrase earns its place—there is no filler, repetition of the tool name, or boilerplate.

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 is complete enough for an agent to understand what inputs to provide and what outcome to expect. However, with no output schema, the exact shape of the 'effective failing set' is left unspecified, and the criteria for 'stale' and 'expiring' are not elaborated—minor gaps given the generally clear purpose.

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

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

Schema coverage is 100%, so the baseline is 3. The description adds slight semantic color by calling waivers 'sanctioned violations, with expiry' and violations 'lint output', but it mostly restates what the schema already says. It does not meaningfully expand on accepted formats for the loosely typed union values.

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 a specific verb ('reconcile') and resource ('a waivers file against lint output'), then defines the exact behavior: suppress sanctioned violations and surface expired, stale, and expiring ones. It clearly distinguishes this tool from the many generic find/get siblings by naming its unique reconciliation concern.

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 gives clear usage context: use this when you have a waivers file and lint output and need the effective failing set a build should gate on. It does not mention alternatives or when-not-to-use, but no obviously competing sibling exists and the intended workflow is evident.

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 states the tool's primary function but provides no details about side effects, data requirements, limitations, or what the scoring entails. Since no annotations are present, the description carries full responsibility, and it is insufficient.

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

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

The description is a single sentence that is front-loaded and contains no redundant information. Every word contributes to the core purpose.

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

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

Given no parameters and no output schema, the description should provide more detail about what the analysis includes, how scores are produced, and what form the output takes. Current description is too vague.

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

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

There are 0 parameters, so the schema coverage is 100%. The description does not need to add parameter meaning, and the baseline for 0 parameters is 4.

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

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

The description clearly states the action (score reusability and detect duplication) and the context (anti-sprawl view of an estate). However, it does not explicitly differentiate from sibling tools like api_coverage, leaving some ambiguity.

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

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 api_coverage or governance_report. The description implies it's for analyzing sprawl but provides no explicit context or exclusion criteria.

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

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

No annotations are provided, so the description must carry the full burden of behavior disclosure. It only states that it performs a unified search and supports filtering; there is no mention of what the response looks like, pagination mechanics, any side effects (read-only is implied but not stated), rate limits, or the shape of results. For a search tool, this is minimal.

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

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

The description is a single, information-dense sentence that front-loads the core purpose and then lists content types and filtering capability. No fluff or repetition. The length is justified by the breadth of content types, though it could be slightly more structured (e.g., separating the filter list). Overall efficient.

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

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

Given the tool's complexity (8 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain the default behavior (e.g., all types searched if 'types' omitted), what the return structure is, or how to interpret results across different content types. Agents would need to infer many details. For a general search tool with many siblings, more guidance is warranted.

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 25% (only 'q' and 'tags' have descriptions). The description adds context about the 'types' parameter by listing valid categories, which is useful, but it does not explain 'sort', 'match', 'fields', 'page', or 'limit' semantics beyond what the schema's minimal defaults and enums reveal. It partially compensates for the low coverage but leaves key parameters 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?

Clear statement of purpose: unified search across the network, listing many content types and explicitly mentioning filtering by types. This distinguishes it from the many specific find_* siblings (find_posts, find_tools, etc.) — the 'unified' keyword signals it covers all types, whereas those are targeted.

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 context (unified search covers many types not available in individual finders), but it never explicitly contrasts with alternatives or states when not to use it. No direct mention of the sibling find_* tools or a preference rule (e.g., 'use this for cross-type search, use find_posts for single type'). The context is clear but not explicit.

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

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

With no annotations provided, the description carries the full burden, and it excels by explicitly mentioning provenance of every figure and an explicit list of what is NOT measured. This is a strong form of transparency about data limitations, though it doesn't cover auth, errors, or side effects, which are less critical for a read-only metric 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?

Two sentences, front-loaded with a clear question-like lead-in ('How far a standards body actually got:') and then a list of content elements. It is concise and each clause adds value, though the 'Free...' tagline is somewhat non-essential. Overall very efficient.

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

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

For a simple tool with one required string parameter and no output schema, the description covers the main purpose, output contents, and even limitations (what's not measured). It gives an agent enough context to know what to expect, though it could be clearer about the slug format and possible error conditions.

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 does not explain what the required 'slug' parameter represents, despite the schema having zero description coverage and no helpful information. The description focuses on the output and context, leaving the parameter semantics entirely to inference. The tool name and description imply slug is a standards body identifier, but this is not made explicit.

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 this tool measures a standard body's progress, providing specific metrics (repositories, graduation, share, release cadence, contributors) and adds provenance and exclusion context. This goes well beyond a generic label and differentiates it from sibling tools like 'standard_repositories' by focusing on adoption and transparency.

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

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

No guidance is provided on when to use this tool versus alternatives. There is no mention of sibling tools, conditions that favor this tool, or any exclusions. The line 'Free, because a specification is a public good' hints at accessibility but doesn't help with selection.

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