api-evangelist

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

No annotations are provided, so the description must fully disclose behavioral traits. It describes what the tool measures but omits critical details: whether it is read-only or destructive, what input it requires (the 'document' parameter), how the output is structured, and any side effects. The description is insufficient for safe 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?

The description is extremely concise: two sentences with no wasted words. The first sentence states the core action and dimensions, the second provides an analogy. It is well front-loaded 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?

The tool has a required parameter and no output schema, yet the description fails to explain the input format or return value. Given the complexity of governance measurement, the description is incomplete. It does not cover prerequisites, limitations, or how results are presented.

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?

Although context signals indicate 100% schema description coverage, the description does not mention the required 'document' parameter or explain how to provide it. The schema itself has an empty properties object with additionalProperties true, so the parameter is unclear. The description adds no meaning beyond the schema, leaving the agent uninformed about the input expected.

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

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

The description clearly states the tool's function: 'Measure how much of an API description your governance actually inspects' and specifies the dimensions (coverage by section, each rule's reach, unmatched rules). The verb 'measure' and resource 'coverage of governance inspection' are specific, but it does not distinguish this tool from siblings like api_scorecard or audit_pipeline.

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 analogy 'Like test coverage, one altitude up' hints at context but does not provide concrete criteria or exclusions. Sibling tools exist for similar governance tasks, but the description offers no differentiation.

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 notes the output format (score and grade) and that it uses an apis.json, but does not disclose whether the tool is read-only, requires authentication, or has side effects. As a scoring tool, read-only is implied but not explicit, and no rate limits or error conditions are mentioned.

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 front-load purpose and critical usage guidance. Every sentence adds value without 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?

The description covers the essential input (document/ruleset) and output (score 0-100, letter grade) and lists the evaluated dimensions. It lacks detail on error conditions, performance, or prerequisites beyond the ruleset, but for a scoring tool with no output schema, it provides sufficient context for an agent to use it correctly.

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

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

The input schema has a required 'document' parameter but no property descriptions, leaving it vague. The description adds meaning by clarifying that 'document' should contain a ruleset, and mentions apis.json as a source. This significantly compensates for the schema's minimalism.

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 API maturity with a numeric score and letter grade across specific dimensions (design, governance, documentation, discoverability, agent-readiness, operations). This explicitly distinguishes it from sibling tools like governance_report (focused on governance only) or validate_api (focused on validation).

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 advises passing a custom 'ruleset' and explains why ('a score against rules you never adopted means little'), which guides proper usage. However, it does not explicitly state when to use this tool versus alternatives like certify_api or audit_pipeline, but the distinct purpose makes the context clear.

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

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

No annotations are provided. The description hints at behavioral aspects (applying an overlay, reporting matches) but does not disclose whether the operation is destructive, requires specific permissions, or modifies the original document. Key behavioral details are missing.

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

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

The description is two sentences long, front-loaded with the action and output, and immediately provides the use case. Every word contributes meaning 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?

With no annotations, no output schema, and minimal parameter descriptions, the tool definition lacks essential context. It does not describe response format, error handling, or prerequisites, leaving significant gaps for an agent to correctly invoke the tool.

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

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

The input schema lists required parameters 'document' and 'overlay' but provides no property definitions or types. The description only mentions 'Apply an OpenAPI Overlay to a document', failing to explain expected formats, constraints, or structure for these parameters. Schema description coverage is high only because properties are empty.

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 applies an OpenAPI Overlay to a document and reports matched actions. It specifies the verb 'apply' and the resource 'overlay to document', and distinguishes itself from sibling tools that focus on other API operations like validation or certification.

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

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

The description explicitly mentions the use case: 'deprecation and migration choreography without forking the contract.' However, it does not provide when-not-to-use guidance or list alternatives, though no sibling tool appears to perform a similar function.

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 only mentions input format but lacks details on side effects, permissions, rate limits, or whether changes are made. The tool is likely read-only, but this is not confirmed.

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 no waste. The first sentence states purpose and output; the second gives input instructions. Efficient and easy to parse.

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

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

The description is adequate for a simple tool: it defines input and output. However, it lacks details on error handling, rate limits, or nuances like what happens if the repo is private. Complexity is low, so minimal completeness is acceptable.

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 (100% coverage), but the description adds essential meaning by specifying that 'repo' or 'files' should be passed, which is not evident from the schema alone. This exceeds baseline for no-parameter tools.

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), resource (repository's Spectral CI setup), rubric (8-point maturity), and output (prioritized punch-list). It is specific and distinct from sibling tools like 'api_coverage' or 'api_scorecard' which cover different domains.

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

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

The description explains how to pass input ('public repo (owner/name) or files'), giving clear usage instructions. However, it does not explicitly state when to use this tool instead of alternatives, though the unique function implies context.

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

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

No annotations are provided, so the description carries full burden. It mentions tamper-evidence and SHA-256 fingerprint for re-verification, but does not disclose permissions, side effects, or whether the action is destructive.

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

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

Two concise sentences front-load the main action and add a key detail (SHA-256 fingerprint). 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?

No output schema is provided, and the description does not explain the return format or full process. The schema's use of additionalProperties is not mentioned, leaving ambiguity about expected input structure.

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

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

The input schema has an undefined 'api' property and allows additional properties, yet the description fails to define what 'api', 'named ruleset', or 'profile threshold' refer to as parameters. Schema coverage is misleadingly 100% only because schema is empty.

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

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

The description clearly states the specific action: 'issue a tamper-evident governance certificate'. It distinguishes from sibling tools like verify_certificate by focusing on certification issuance.

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 context is implied from the description (use when you need to certify an API), but no explicit guidance on when not to use or alternatives compared to 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 convey behavior. It indicates a read-only scanning operation ('inventory') but does not mention authorization needs, rate limits, or whether it modifies any state. The description is adequate but not exhaustive.

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: first defines what the tool does, second provides usage recommendation. No extraneous words, all information is front-loaded and directly relevant.

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

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

The description covers purpose and usage, but lacks mention of output format or return value (no output schema). Given the tool's simplicity and the context of siblings, it is mostly complete but could benefit from specifying the output structure.

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

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

The input schema is minimal (required 'document' with no type), but the description adds crucial meaning: 'OpenAPI document' and what it analyzes. This compensates for the schema's lack of detail, though further clarification of the 'document' property would improve score to 5.

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 'inventory' and clearly states it operates on OpenAPI fields for PII, secrets, and sensitive data. It distinguishes from sibling tools like api_coverage or validate_api by focusing specifically on sensitive data discovery.

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

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

It explicitly states when to use: 'Run this before exposing an API to agents.' This is clear usage guidance, though it does not mention when not to use or provide alternatives. The context is sufficient for most agents.

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 behavioral traits such as side effects, read-only nature, or required permissions. It only states that it generates samples, which implies no mutation, but this is not explicitly confirmed.

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

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

The description is a single concise sentence with no fluff. It efficiently communicates the core function but could benefit from additional 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?

The tool has one required parameter ('document') that is not explained in the description. No output schema exists, and the tool's behavior regarding the 'document' input and return value is left entirely to the schema, which lacks property definitions. The description does not provide enough context for the agent to use the tool correctly.

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

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

Schema description coverage is reported as 100%, so the baseline is 3. The description provides no additional meaning about the 'document' parameter or any other input beyond what the schema already conveys.

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 generates runnable curl, JavaScript, and Python samples. The verb 'generate' and resource 'samples for every operation' provide a clear purpose, but it does not explicitly differentiate it from sibling tools like mock_payloads.

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. It does not mention prerequisites, when-not-to-use scenarios, or comparisons with similar tools such as mock_payloads.

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, and the description omits behavioral details such as whether it is read-only, any side effects, or prerequisites. 'Pro.' is 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?

Extremely concise but under-specified; the single sentence adds little value and 'Pro.' is unnecessary.

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

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

For a tool with one parameter and no annotations/output schema, the description fails to provide essential context like return type or invocation instructions.

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

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

Schema coverage is 0%; the description does not explain the 'slug' parameter, its format, or how to obtain 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 'weakest investment dimensions' is vague; it rephrases the tool name without specifying a verb or resource. It does not distinguish from related tools like '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?

No guidance on when to use this tool vs siblings; no exclusions or alternative suggestions 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 states the tool generates a 'report', implying a read operation, but does not explicitly confirm non-destructiveness, required permissions, rate limits, or side effects. The description is insufficient for a tool with no annotation support.

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

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

The description is two sentences, concise and front-loaded with the action. No filler. However, the cryptic second sentence ('The ones that go quiet...') adds color but may not earn its place in terms of clarity.

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

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

Given the tool's complexity (required parameter 'document' with no schema, no output schema, and no annotations), the description is severely incomplete. It fails to explain input format, output structure, or operational constraints.

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

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

The input schema requires a 'document' parameter but defines no properties or type, and the description does not explain what the document should contain. With schema coverage effectively 0% (empty properties), the description adds no meaningful semantics for the parameter.

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

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

The description clearly states the tool's verb ('Report') and resource ('deprecated operation', 'sunset announcement'). It conveys a specific analytical purpose. However, it does not explicitly differentiate from sibling tools like 'governance_report' or 'audit_pipeline'.

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 state prerequisites, conditions, or mention any exclusions. The agent is left to infer usage context from the purpose alone.

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

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

No annotations provided, so description carries full burden. It only states the core functionality but lacks disclosure of behavioral traits like read-only nature, permissions, rate limits, or side effects. The classification terms are not explained.

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

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

The description is a single, well-structured sentence that front-loads the main action. It is concise with no wasted words, though additional structure (e.g., bullet points) could improve clarity given the complexity.

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, and the description does not specify return format, limitations, or the exact nature of 'old' and 'new' parameters. This leaves significant gaps for an agent to use the tool correctly.

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

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

Although schema description coverage is 100%, the schema itself is minimal ('required: old, new') with no property details. The description does not explain what 'old' and 'new' represent, leaving the agent without guidance on how to format these 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 purpose with specific verb 'diff', resource 'OpenAPI versions', and details granularity of classification, making it distinct from sibling tools like 'validate_api'.

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

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

No guidance on when to use this tool versus alternatives, no prerequisites or typical scenarios mentioned. Among siblings, no differentiation 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 must disclose behavioral traits such as destructive potential, authentication needs, or output size. It only describes the transformation vaguely without noting side effects or restrictions.

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, somewhat verbose sentence. It uses front-loaded purpose but includes an em-dash list that could be simplified. No obvious waste, but could be more direct.

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

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

Despite no output schema, the description omits critical details: expected input format for 'ruleset', example usage, and whether the tool is read-only or mutating. The high-level purpose is clear but incomplete for safe 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 required parameter 'ruleset' is not described in the description or schema (empty properties object). The context claims 100% schema description coverage, but the text adds no meaning; the agent cannot infer the format or structure of 'ruleset'.

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 verb ('turn') and resource ('governance ruleset'), and lists specific outputs (AGENTS.md block, system-prompt set, etc.), distinguishing it from sibling tools that focus on APIs and governance 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?

No guidance on when to use this tool versus alternatives like forge_mcp_tools or generate_agent_descriptor. The description implies context for agent authoring but does not explain when this export 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 provided; the description only defines the resource without disclosing behavioral traits like pagination, read-only nature, or result 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?

Single sentence with essential purpose, but could be more specific about what 'focused topic areas' means. No wasted words.

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

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

With 7 parameters, no output schema, and no annotations, the description lacks sufficient detail for an agent to understand results, behavior, or parameter usage.

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

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

Schema coverage is only 29%, and the description adds no parameter details, leaving most parameters unexplained beyond the schema.

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

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

The description clearly states it finds 'focused topic areas' with examples, distinguishing it from other find_* tools that target different content 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?

Implies usage for searching topic areas, but no explicit guidance on when to use this versus other find_* tools or alternatives like get_area.

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

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

No annotations provided, so the description must carry the full burden. It only mentions the type filter, omitting details about pagination, sorting, free-text search, or default behavior. Important behavioral aspects are missing.

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

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

Single sentence that is front-loaded with the action and resource. No redundant words, but could be expanded with key parameter info 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?

With 8 parameters, no output schema, and multiple siblings, the description only covers the type parameter. It fails to explain how other parameters work or what the response contains, making it incomplete for effective tool selection and 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 25%, low. The description adds meaning only for the 'type' parameter by listing its enum values with counts. Other parameters (q, page, sort, tags, limit, match, fields) receive no additional explanation beyond the schema basics.

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

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

Description clearly states it searches governance building blocks by type, listing all available types with counts. This is a specific verb+resource combination that distinguishes it from sibling tools like find_areas or find_conversations.

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 does not mention any context, prerequisites, or exclusions that would help an agent choose correctly.

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 states the tool is free and returns a ranked list, but does not disclose read-only behavior, authentication needs, or details like pagination. It is minimally adequate but lacks depth.

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

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

The description is a single sentence of 13 words, front-loaded with key purpose and scope. It is efficient but could usefully expand on parameters or 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?

Given no output schema, no annotations, and 3 undocumented parameters, the description is too sparse. It omits return format, ranking details, cost implications beyond 'Free', and how it differs from 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%, yet the description only mentions 'by name' for the 'q' parameter. It provides no explanation for 'page' or 'limit' parameters, leaving their purpose unclear beyond schema defaults.

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

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

The description clearly states the tool browses profiled companies (Fortune 1000 + API providers) by name, with ranking by technology-readiness signal. The verb 'browse' and resource 'companies' is specific and distinguishes it from sibling tools like get_company_insight or other find_* tools for different 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?

The description provides no guidance on when to use this tool versus alternatives like find_areas or get_company_insight. It only mentions 'Free' but does not specify context, prerequisites, or exclusions.

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

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

No annotations are provided, so the description must convey behavioral traits. It only defines the resource and does not disclose search behavior, pagination, sorting, or output format. Critical behavioral context like how queries work or what fields are searched is missing.

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

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

The description is a single sentence with no fluff, achieving conciseness. However, it is not front-loaded with the action (find), but given the tool name, it's functional. It could be improved by adding a verb without increasing length significantly.

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

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

Given the tool complexity (7 parameters, no output schema, low schema coverage), the description is woefully incomplete. It provides no information on how to invoke the tool, interpret results, or differentiate from siblings. An AI agent lacks the context to use it 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%, meaning most parameters lack schema descriptions. The tool description adds no information about parameters, not even explaining the search field 'q' or tag filtering. It fails to compensate for the low schema coverage, leaving an AI agent with insufficient 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 identifies the resource as 'recorded discussions with API practitioners' including guest, company, and YouTube/SoundCloud links. It is clear that the tool is about conversations, but it does not explicitly state that it searches or finds them. The verb is implied by the tool name, and the description differentiates from sibling find tools by specifying the 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?

No guidance on when to use this tool versus alternatives like find_videos or find_posts. The description does not mention any context, prerequisites, or exclusions. With many sibling find tools, this omission makes it difficult for an AI agent to select the correct tool.

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

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

With no annotations, the description must disclose behavior. It only says 'with outlines', hinting at output structure, but does not explain search behavior, pagination, or any side effects. For a list tool, this 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 short sentence, but it reads like a promotional tagline rather than a structured tool description. It lacks front-loading of key information and wastes space on 'sixteen years of research' instead of actionable guidance.

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

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

Given the tool has 7 parameters, no output schema, and many similar siblings, the description is woefully incomplete. It does not explain how results are filtered, sorted, paged, or what fields are available. The agent cannot select or invoke this tool correctly based on this description alone.

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%. The description adds no parameter information; the mention of 'outlines' does not clarify parameters. Since coverage is low, the description should compensate but fails.

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 'API Evangelist white papers' which identifies the resource type. Combined with the tool name 'find_papers', the purpose is clear: it finds white papers from API Evangelist research. However, the description lacks a verb and does not explicitly distinguish from siblings like get_paper or search_api_evangelist, so a slight deduction.

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 the many sibling tools (e.g., get_paper, find_videos, search_api_evangelist). There is no mention of use cases, context, 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?

With no annotations, the description must disclose behavioral traits. It hints at read-only behavior ('search or browse') and date range, but omits pagination, sorting, match logic, auth, or rate limits. Insufficient for an 8-parameter 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?

Single sentence, extremely concise, and front-loads the core purpose. However, it sacrifices necessary detail for brevity, making it less useful than it could be.

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

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

Given 8 parameters, no output schema, and no annotations, the description is critically incomplete. It does not explain pagination, sorting, field selection, match behavior, or how to combine filters. Sibling tools exist but no guidance is provided.

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

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

Only 25% of parameters have schema descriptions. The description adds meaning for 'year' and 'tags' (filter by year or tags) but ignores page, sort, limit, match, fields. Fails to compensate for low 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 identifies the verb ('search or browse') and resource ('5,100+ API Evangelist stories') with a time range. It distinguishes from sibling find_* tools (e.g., find_conversations) by specifying 'posts' implicitly, but does not explicitly contrast.

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 get_post or other find_* tools. The description implies filtering but does not state when browsing vs searching is appropriate or mention exclusions.

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

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

No annotations are provided, so the description carries full burden. It discloses that results are ranked by shared-tag relevance with rare/specific tags weighted more, giving insight into the algorithmic behavior. It doesn't mention read-only status or authorization, but the core ranking logic is well explained.

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

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

The description is extremely concise at two sentences, with the first sentence front-loading the core functionality and ranking logic. No redundant information.

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

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

The description covers the main functionality and ranking but lacks details on output format, parameter usage (limit, types), and when to prefer this over sibling find_* tools. Without an output schema or parameter descriptions, the agent needs more guidance for proper invocation.

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

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

Schema description coverage is 0%, so the description must compensate. It explains the required 'type' and 'slug' parameters but does not describe the optional 'limit' and 'types' parameters, leaving their purpose ambiguous. The mention of content types in the second sentence hints at 'types' but lacks clarity.

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 the most related content across the entire network based on a document's type and slug, using shared-tag relevance. It distinguishes itself from sibling tools that focus on specific content types by offering a cross-content 'more like this' search.

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

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

The description implies usage when wanting to find related content to a given document, but it does not provide explicit guidance on when not to use it or alternatives (e.g., specific find_* tools). No exclusion criteria or complementary tool mentions.

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 behavioral traits. It only describes the tool's subject matter without mentioning safety, side effects, or operational characteristics (e.g., read-only, idempotent, permissions). This leaves behavioral uncertainty.

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 minimal waste, getting straight to the point. The primary purpose is front-loaded, and the sibling distinction is appended parenthetically. One could argue 'by Kin Lane' is slightly extraneous, but 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 7 parameters, no output schema, and many sibling tools, the description is incomplete. It does not explain the response structure, pagination, or the effect of parameters like 'fields'. Users would need extra context to use the tool effectively.

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

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

Schema description coverage is low (29%), and the description adds no information about parameters. It does not explain how to use 'q', 'tags', 'sort', etc., beyond the bare schema. With low coverage, the description should compensate but fails to do so.

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 services related to API Evangelist's offerings (API strategy, governance, discovery, evangelism). It distinguishes from the sibling tool find_solutions with an explicit note, providing specific verb+resource and 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 tells when not to use this tool (for third-party vendor registry, use find_solutions). However, it does not provide guidance on when to use this tool over other find_* siblings like find_papers or find_posts, missing comprehensive 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; description provides some context (740+ solutions, ranked by adoption) but does not disclose read-only nature, pagination behavior, or error conditions.

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-loads key details. Concise but could be broken into structured bullets for readability.

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

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

With 7 parameters, no output schema, and no annotations, the description lacks information on return format, pagination, and parameter combinations, making it incomplete 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 coverage is 29%; description adds meaning for 'q' parameter but does not explain page, sort, limit, match, or fields, leaving most parameters underdocumented.

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?

States it's a registry of third-party API services and tools with ranking, distinguishing it from sibling find_* tools. Could be more explicit about the search/listing 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 find_solutions vs other find_* tools. Does not specify prerequisites or typical use cases.

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

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

No annotations are provided, so the description carries the full burden. It mentions browsing and ranking but does not explicitly state read-only behavior, rate limits, or authentication needs. The description is adequate for a simple search 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, concise and front-loaded. The second sentence is slightly metaphorical but not overly wasteful. Every sentence serves a purpose.

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

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

Given 4 parameters and no output schema, the description is incomplete. It explains the purpose and two parameters but fails to document 'page' and 'limit', and does not describe the output format. For a find tool, it lacks sufficient detail.

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 should explain all parameters. It only adds meaning for 'q' (search) and 'sort' (frequency/breadth), but omits 'page' and 'limit'. This is insufficient to compensate for the lack of schema documentation.

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

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

The description clearly states 'Browse and rank the network tag taxonomy' with specific verbs and resource, and distinguishes from sibling tools by focusing on tags rather than areas, building blocks, etc.

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 implies usage for exploring the tag taxonomy ('Search with q. The map of what API Evangelist covers.'), but provides no explicit when-to-use or when-not-to-use guidance, nor mentions alternatives.

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

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

With no annotations, the description carries the full burden. It only mentions the registry's content, not the tool's behavior (e.g., search, pagination, read-only nature). Minimal transparency.

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

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

The description is a single sentence, which is concise, but it lacks structure and essential information. Not overly verbose, but also not effective.

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

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

Given 7 parameters, no output schema, and no annotations, the description is incomplete. It does not explain the tool's purpose, parameters, or output format.

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

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

Schema description coverage is only 29%, and the description does not add any meaning to parameters. It fails to compensate 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 describes a resource (registry) but does not explicitly state that the tool finds or searches tools. The verb 'find' is only in the name, not reinforced in the description. It is somewhat vague.

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

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

No guidance on when to use find_tools versus alternatives like get_tool or other find_* tools. The description lacks any context about typical use cases 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; description does not mention search behavior, return format, pagination, or any side effects.

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

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

Single sentence is concise but lacks context that should be included for 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?

With 7 parameters and no output schema, the description omits pagination, sorting, and filtering behavior, 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 coverage is only 29%; description adds no detail beyond schema parameter names and basic descriptions already present.

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 searches a video library with transcripts, distinguishing it from siblings like find_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 guidance on when to use this tool versus alternatives like search_api_evangelist or other find_* tools for different 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It only mentions the content domain and filtering, omitting any information about pagination, rate limits, idempotency, or destructive potential. The agent cannot assess safety or performance implications.

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 it front-loads a vague characterization of the vocabulary rather than the tool's core function. It could be restructured to state the action first, then the content scope.

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

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

Given 8 parameters, no output schema, and no annotations, the description is profoundly incomplete. It does not explain how parameters like page, sort, and limit affect results, what the response looks like, how filtering with tags and match works, or how to properly construct queries. The agent lacks essential 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?

Schema description coverage is only 25% (2 of 8 params described). The description adds value only for the 'category' parameter ('Filter by category'), but fails to clarify the purpose of unnamed parameters like page, sort, limit, match, and fields. Important constraints (e.g., maximum limit=100) are left solely to 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 is a noun phrase describing the vocabulary content rather than stating an action. It says 'The API vocabulary... Filter by category', but does not explicitly state that the tool searches or retrieves vocabulary items. The name 'find_vocabulary' implies search, but the description lacks a clear verb-resource pairing.

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 use this tool versus its many sibling find tools (e.g., find_areas, find_building_blocks). There is no mention of use cases, prerequisites, or alternative tools, leaving the agent to infer usage from the tool name and category list.

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

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

No annotations exist. The description discloses that the tool generates multiple files but does not mention behavioral aspects like required permissions, whether it modifies existing resources, rate limits, or error handling. For a generative tool, this is minimal disclosure.

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

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

The description is a single sentence that efficiently conveys the core action and outputs. It could benefit from structure (e.g., listing parameters or clarifying input requirements), but it is not 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?

The tool is complex with multiple outputs, yet the description only lists them without explaining their nature or purpose. Given no output schema, the description should provide more context about what each artifact is. It partially meets completeness for a low-complexity tool but falls short for this complexity.

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

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

The input schema requires a 'document' parameter but has no property definition. While schema coverage is reported as 100%, the description does not explain what 'document' is (e.g., file path, URL, string content). It adds no meaning beyond the schema, which itself lacks clarity.

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: forging an MCP server design from an OpenAPI, and explicitly lists the outputs (per-operation tools, Agent Skills, enriched OpenAPI, server.json, apis.json properties). This distinguishes it from sibling tools that are primarily query or analysis 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 implies the tool is used when you have an OpenAPI and want to generate MCP server artifacts, but provides no when-not-to-use guidance or alternative tool references. The context is clear but lacks explicit usage boundaries.

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

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

No annotations are provided, so the description carries full burden. It fails to disclose behavioral traits such as whether the tool is read-only or destructive, what permissions are needed, side effects, or how the 'choice' is made. The description only lists outputs without 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 front-loads the action and lists outputs efficiently. Could be slightly improved with sentence breaks for readability, but no significant waste.

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

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

Given no output schema and no annotations, the description is moderately complete. It covers the main purpose and outputs but lacks behavioral details and usage context. For a tool with no parameters, it could clarify the role of 'Choose' and the expected input format.

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

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

The input schema has no properties and additionalProperties: true, with 100% schema description coverage (no params). The description does not explain the handling of additional properties, but since there are no explicit parameters, the baseline of 4 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 uses specific verbs ('Choose', 'emit') and clearly lists the resources and outputs: 'an API exposes to agents', 'Tyk OpenAPI', 'MCP tool manifest', 'Spectral ruleset'. It distinguishes this tool from siblings like 'forge_mcp_tools' and 'generate_agent_descriptor' by naming unique outputs.

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 is for configuring agent access and governance, but does not explicitly state when to use it versus alternatives like 'forge_mcp_tools' or 'generate_agent_descriptor'. No 'when-not' or prerequisite 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?

No annotations are present, so the description should disclose behavioral traits. It does not mention input requirements (the schema has no parameters but allows additionalProperties), side effects (e.g., file overwrite), authentication needs, or whether the tool reads from context. The output is described but not how it is delivered.

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 the core function and contents. It is concise but could be better structured with separate sentences for clarity. Almost no redundant information.

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

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

No output schema is provided, and the description does not specify the return format (e.g., whether it creates files or returns content). It lists contents but lacks details on how the tool is invoked or what the agent should expect after calling it. For a tool with no annotations and no output schema, more completeness is expected.

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 defined parameters but allows additional properties. The description does not explain what inputs the tool expects (e.g., API identifier from context or free-form keys). With 0 parameters, a baseline of 4 might be considered, but the missing guidance on how the tool determines which API to process reduces clarity.

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 generates 'llms.txt' and 'AGENTS.md' files for an API, listing specific contents (base URL, auth, operation table, deprecated operations, usage rules). It is a specific verb-resource combination and distinguishes from sibling tools like 'export_agent_rules' which likely exports in different formats.

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 when-to-use or when-not-to-use guidance is provided. The description does not compare to alternative tools (e.g., 'export_agent_rules', 'certify_api') nor mention prerequisites or context, leaving the agent to infer usage from the purpose alone.

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

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

No annotations are provided, and the description fails to disclose whether the operation is read-only, requires authentication, or any side effects. The term 'walk' implies traversal but does not specify behavioral safety.

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

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

The description is a single concise sentence, which is efficient, but it sacrifices clarity by being too brief and metaphorical. It front-loads the main idea but lacks structured 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 no output schema, no annotations, and sparse parameter documentation, the description is severely incomplete. It does not explain what the returned graph contains or how to interpret results, leaving major gaps for agent understanding.

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 parameter 'slug' has zero schema description coverage, and the description adds no explanation of what 'slug' means or its expected format. This leaves the agent without guidance on how to invoke the tool correctly.

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 indicates it returns one topic area with its related-area graph, which distinguishes it from other get_* tools that retrieve different resources. The verb 'walk' is somewhat metaphorical but conveys the idea of navigating connections.

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 over siblings like find_areas or other get_* tools. The description does not state prerequisites or alternative contexts.

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?

Adds minimal behavioral info beyond schema (include returns full body), but no annotations and no discussion of side effects, errors, or 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?

Single sentence is concise but lacks structure; no parameter breakdown. Adequate but not optimal.

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 3-param tool with no output schema, description omits return format, error handling, and relationship to siblings. Incomplete.

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

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

Schema coverage is 0% but description only clarifies the include parameter. Does not explain slug or type beyond schema enums. Insufficient compensation.

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

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

Clearly states it retrieves one building block by type and slug, and explains the include parameter. Differentiates from sibling list tools implicitly.

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?

Implies use when specific building block needed, but no explicit when-to-use or alternatives. Siblings like find_building_blocks are not addressed.

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

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

No annotations provided, so the description carries full burden. It does not disclose whether the tool is read-only, any side effects, or authorization needs. No behavioral context beyond the output 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?

One sentence, front-loaded with key terms. The word 'Pro' adds negligible value and could be removed. Otherwise, efficient for the content provided.

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

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

Given no output schema, the description hints at output structure (40 dimensions, etc.) but does not fully explain return format or pagination. With many siblings, more context on usage and output would be beneficial.

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

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

Schema coverage is 0% and the description adds no explanation for the 'slug' parameter (e.g., how to find it, format). With only one parameter, the description should have provided context, but it 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?

Description clearly states it provides a full demand-side profile with 40-dimensions, adopted stack, and per-quarter history. It distinguishes from siblings like 'get_company_insights' (plural) and other get_* tools by specifying scope. However, 'Pro' is ambiguous.

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 vs alternatives like 'company_gaps' or 'insights_dimensions'. The description implies comprehensiveness but does not state scenarios or exclusions.

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

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

No annotations provided, so description bears full burden. It lists contact methods (email, form, etc.) but does not describe the output format (e.g., is it a list, structured object?) or any side effects. Since the tool has no parameters and is read-only in nature, transparency is adequate but not thorough.

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 is front-loaded with the tool's purpose. Every word earns its place with no filler. Ideal conciseness for a simple tool.

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

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

Given no parameters and no output schema, the description sufficiently conveys the tool's content. It lists all contact methods. Could be more complete by specifying the return structure (e.g., a list or fields), but it is adequate for 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?

Input schema has zero parameters, so schema description coverage is 100% trivially. The description adds no parameter-level detail, but none is needed. Baseline for no parameters is 4, and the description meets it without adding confusion.

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 'Every way to reach API Evangelist...' clearly states the tool returns contact methods, which matches the tool name 'get_contact'. It distinguishes from sibling tools like get_area or get_feeds which return different resources. However, it lacks a specific verb like 'retrieves' or 'lists', relying on 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?

No explicit when-to-use or when-not-to-use guidance. The utility is implied by the name and description, but no alternatives or exclusions are mentioned. Given the sibling tools are all get_* tools with distinct purposes, the context partially clarifies, but explicit guidelines 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?

No annotations are provided, so the description must disclose behavioral traits. It only describes the output and an optional behavior, but does not mention authentication needs, error handling, or side effects. The tool is implied to be a read operation, but that is not explicit.

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

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

The description is a single, concise sentence that front-loads the primary purpose. It efficiently communicates the core functionality without extraneous 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 get tool with two parameters and no output schema, the description covers the basics (returns conversation details, guest, media links, optional writeup). However, it omits potential error conditions and does not contextualize among the many 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?

The input schema has 0% description coverage, so the description must compensate. It explains the include parameter's effect ('returns the writeup'), adding value. However, the required slug parameter is only implicitly described as identifying the conversation, lacking explicit 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 it retrieves a single conversation with guest details and media links, and explains the effect of the include parameter. The verb 'get' combined with 'conversation' is specific, though it does not differentiate from sibling tools like get_post or get_video.

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 get_feed or find_conversations. The description does not mention prerequisites or contexts where this tool 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 provided, so description carries full burden. Discloses it is static, machine-readable, zero-auth, which is sufficient for a simple read operation. Does not detail output format beyond JSON/APIs.json.

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, well-structured sentence. No fluff, front-loaded with key purpose.

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

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

For a simple tool with no parameters and no output schema, description fully captures what the agent needs to know: it's a public, static feed endpoint.

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

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

No parameters in schema; baseline is 4. Description reinforces that no key is needed, aligning with 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?

Clear verb 'get' and resource 'feeds', specifies they are static machine-readable feeds. Distinct from sibling tools as it's the no-key alternative.

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

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

States it's a no-key alternative, implying use when authentication is not available. Lacks explicit when-to-use vs other tools but provides clear context.

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

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

No annotations provide safety/read-only hints, and the description does not disclose behavioral traits such as side effects, permissions, rate limits, or pagination behavior. The description adds only the fact that it returns a list, but no deeper transparency.

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

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

The description is a single sentence that is relatively concise. It conveys the core functionality without extra verbiage. However, it could be slightly more structured (e.g., listing parameters separately).

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 (three parameters, no output schema) and the presence of many sibling tools, the description is too minimal. It does not explain what the output list contains, how pagination works, or how this tool differs from similar 'get_' or 'find_' 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%, so the description must compensate. It only lists the enum options for 'section' but does not explain 'page' or 'limit'. While the parameter names are somewhat self-explanatory, the description adds no additional semantic value beyond the schema's field names.

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

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

The description clearly identifies the tool's purpose: retrieving one editorial guidance section as a list of specific content (history, technology, etc.). The verb 'get' is implied by the name, but the description could be more explicit about returning section content rather than just listing options.

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

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

No guidance on when to use this tool versus siblings (e.g., find_areas, get_overview). There are no explicit conditions, exclusions, or alternatives mentioned. The agent must infer usage from the name and description alone.

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

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

No annotations are provided, so the description must convey behavior. It states the tool returns counts, entry points, and how to engage, which adequately describes the non-destructive read nature. Could be slightly improved by explicitly noting no side effects, but the description is sufficient.

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

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

The description is extremely concise at two sentences, with the most important directive 'START HERE' placed first. Every word adds value, and no redundant information is 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 tool's nature as an overview with no parameters and no output schema, the description adequately explains what is returned (counts, entry points, how to engage). It could mention that the overview is of the entire network, which is already implied, so it is largely complete.

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

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

The input schema has zero parameters, and schema description coverage is 100% (empty object). The description does not need to add meaning for parameters since there are none. The 'START HERE' hint reinforces that no arguments are needed.

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

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

The description explicitly states 'START HERE' and describes the tool as providing an overview of the API Evangelist network, including counts, entry points, and how to engage. This clearly distinguishes it from sibling tools like get_area or find_posts which focus on specific subsets.

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 'START HERE' directly tells the agent to use this tool first, providing clear guidance on when to invoke it. No exclusions or alternatives are needed as it's the entry point.

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

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

No annotations are provided, so the description carries the burden. It discloses the return content (outline and URL) but does not mention authentication, rate limits, or any side effects. The behavioral transparency is adequate but not detailed.

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, efficient and front-loaded with the key purpose. However, it lacks structure (e.g., bullet points or separate sections for parameters/usage), which could improve clarity.

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

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

Given the simplicity of the tool (single param, no output schema), the description is mostly complete in stating what the tool returns, but it fails to document the 'slug' parameter meaning, which is essential for correct invocation.

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

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

Schema description coverage is 0%. The only parameter 'slug' has no description in the schema or in the tool description. The description does not explain what a 'slug' is or how to obtain it, leaving the agent without critical information to invoke the tool correctly.

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 paper with its full outline and purchase/landing URL, using a specific verb 'get' and resource 'paper', distinguishing it from sibling tools like 'find_papers' which likely list 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 guidance on when to use this tool versus alternative tools (e.g., find_papers for listing). No prerequisites or context for when to invoke get_paper 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 provided, so description carries full burden. It discloses the return includes full markdown body when 'include' is specified, but does not describe default return structure, authentication needs, or rate limits. Adequate but not fully transparent.

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

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

Single sentence with all essential information front-loaded. No redundant words; every part adds value.

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

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

For a simple 2-parameter tool with no output schema, the description covers the primary behavior and parameter effects. Minor gap: does not specify default return without 'include', but overall 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 has 0% description coverage; description adds significant meaning: slug format 'YYYY-MM-DD-slug' and effect of 'include' parameter. This compensates well 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 'One story by slug' specifying the verb (get) and resource (story/post). It distinguishes from siblings by noting the slug format and the 'include' parameter, making the tool's purpose very specific.

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

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

No explicit guidance on when to use this tool vs alternatives. Tool name and description imply it's for posts, but without stating when not to use or suggesting alternatives, the agent must infer from context.

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

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

No annotations are provided, so the description must carry the full burden. It only mentions the include parameter but does not disclose behavior such as read-only nature, error handling, permissions, or side effects. The term 'full detail' is vague.

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

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

The description is a single sentence with clear front-loading of the main function and a brief note on the optional parameter. No wasted words.

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

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

Given the low complexity (2 params, no output schema), the description covers the basic retrieval and optional inlining. However, it lacks behavioral details and could hint at the response structure, which is absent.

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 compensates by indicating slug is the identifier and include inlines the pitch. However, it does not explain what 'content' or 'full pitch' means, leaving some ambiguity.

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

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

The description explicitly states it returns 'full detail for one service offering by slug', clearly identifying the resource and lookup method. It distinguishes from siblings like 'find_services' and other getters for different 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?

The description implies use when you need detailed info for a single service, but provides no explicit guidance on when to use versus alternatives like 'find_services' or when not to 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 provided; the description discloses that it returns website and adoption count, suggesting a read operation, but does not explicitly state side effects or lack thereof.

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, front-loaded with the core purpose, no wasted words.

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

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

For a simple getter with one parameter and no output schema, the description adequately covers purpose and return fields. Minor improvement would be clarifying that it returns a single solution object.

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' is mentioned in the description as the lookup key, adding meaning beyond the schema which only specifies type. However, schema description coverage is 0%, so the description partially compensates.

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

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

The description clearly states the tool retrieves a single solution by slug and includes website and adoption count. It distinguishes from sibling tools like find_solutions by specifying 'one solution' and the detail returned.

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

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

The description implies use when a specific solution's details are needed, but does not explicitly state when to use versus alternatives like find_solutions.

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

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

The description discloses the type of data returned (counts, top tags), but does not explicitly state it is read-only or safe. With no annotations, the description carries the full burden; it is adequate but lacks details on side effects or conditions.

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 efficiently conveys the tool's purpose and outputs. No superfluous text.

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

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

For a simple tool with no parameters and no output schema, the description adequately explains what the tool returns. However, it could explicitly note that it is a read-only aggregation to 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?

The tool has zero parameters, so the description does not need to explain parameter semantics. Baseline score of 4 applies as there is no missing information.

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, and top tags. This distinguishes it from sibling tools that retrieve individual entities (e.g., get_post, get_tag) or search (find_*).

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

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

No guidance on when to use this tool versus alternative aggregation or search tools. The description does not mention prerequisites, limitations, or context for usage.

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

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

No annotations are provided, so the description must cover behavioral traits. It mentions 'per-type counts' and 'everything it labels across the whole network', indicating a comprehensive response. However, it does not disclose performance impacts, pagination behavior for labeled items (despite page/limit parameters), or the exact effect of the types filter on returned data. Adequate but not thorough.

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, compact sentence that conveys the essential information without extraneous words. Every phrase adds value, and the structure is front-loaded with the core purpose.

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

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

Given the tool's complexity (retrieving a tag with aggregated counts and items across multiple types) and lack of output schema, the description gives a reasonable idea of the response shape. However, it omits details like ordering, error handling, and the exact structure of counts. It is sufficient for basic understanding but leaves gaps for precise invocation.

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

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

Schema description coverage is 0%, so the description must add meaning. It explains the 'types' parameter ('Filter with types') and implies the 'slug' parameter (for identifying the tag). However, the pagination parameters 'page' and 'limit' are entirely unmentioned, leaving their purpose unclear. Two out of four parameters are partially 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 retrieves a single tag along with its per-type counts and all labeled items across the network. It specifies filtering by types, distinguishing it from sibling tools like find_tags which would list tags. The verb 'get' and resource 'tag' are explicit.

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

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

The description does not provide explicit guidance on when to use this tool versus alternatives. While the purpose implies it's for detailed info on one tag, there is no direct comparison to siblings like find_tags or other get_* tools. No when-not-to or prerequisites 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 present, and the description fails to disclose behavioral traits beyond returning chronological order. It does not mention pagination, authentication requirements, rate limits, or lack of 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 efficiently conveys the core purpose. It is front-loaded and contains no extraneous information, though it could be slightly restructured for clarity.

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

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

Given no annotations or output schema, the description is insufficient. It does not describe the return format, pagination behavior, or any constraints beyond the timeline options.

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

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

The description adds context for the 'timeline' parameter by explaining each enum value, but ignores 'page' and 'limit' entirely. With 0% schema coverage, the description should compensate for all parameters.

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

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

The description clearly identifies the tool's function: retrieving one of four specific research timelines in chronological order. It names each timeline with a brief explanation, making the purpose specific and distinct from sibling tools like get_area or get_overview.

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 get_timeline versus alternatives such as get_overview or find_conversations. The description does not mention prerequisites, 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. Description indicates a read operation with return fields but omits error handling, rate limits, or prerequisites. Adequate for a simple get but leaves gaps.

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

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

Single sentence, no redundancy. Efficiently conveys purpose and return fields.

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 low complexity (1 param, no output schema), description covers basic functionality. Missing error details and exact response shape but sufficient for typical 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 has 0% description coverage; description adds 'by slug' but does not elaborate on slug format or validation. Minimal added value beyond schema structure.

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

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

Description clearly states it retrieves a single tool by slug with specific fields (website, adoption count, radar ring). Distinguishes from sibling 'find_tools' which likely returns a list.

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

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

Description implies usage for fetching a specific tool by slug but does not explicitly state when to prefer it over siblings like 'find_tools' or how to handle missing slugs.

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

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

No annotations provided; description bare. It does not disclose side effects, authentication needs, rate limits, or error handling (e.g., what if slug not found). For a read operation, minimal behavioral disclosure given missing annotations.

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

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

Single concise sentence that conveys core functionality without extraneous text. Efficient and to the point.

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 two parameters, description is adequate but lacks details on optional return format, error behavior, and whether YouTube id is sufficient for identification. Leaves gaps for an agent.

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

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

Schema description coverage is 0%, so description must add value. It explains that the 'include' parameter with ['content'] returns full transcript, which aids understanding. But for 'slug', no additional meaning beyond the 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?

Description clearly states the verb (get), resource (video by slug), and output (YouTube id, optionally full transcript). It distinguishes from sibling tools like get_paper by specifying video-specific details.

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

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

Implied usage: use when you have a video slug and need its YouTube id or transcript. No explicit when-not-to-use or comparison to alternatives like get_paper or find_videos.

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 does not disclose behavioral traits such as whether it writes to disk, requires authentication, or has side effects. The agent cannot infer safety or resource usage.

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

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

Single sentence, front-loaded with key information, no wasted words. Could benefit from slight expansion but remains concise.

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

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

Lacks details on output format (e.g., is the HTML returned or saved?), error conditions, and whether it requires additional dependencies. Without annotations or output schema, the description is incomplete for reliable agent 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?

The input schema specifies a required 'results' property but provides no description or type. The tool description mentions 'Spectral findings' but does not explain the parameter format or constraints, leaving the agent uncertain about what to pass.

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 converts Spectral findings into an HTML governance report with severity summary and grouping by rule. The purpose is specific and distinct from sibling tools like api_coverage or api_scorecard, but it does not explicitly differentiate.

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

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

No guidance on when to use this tool versus alternatives, no prerequisites or context about input requirements, and no mention of 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, and the description does not disclose behavioral traits like whether the operation is read-only, has side effects, requires special permissions, or is rate-limited. It only describes the outcome, not the nature of the 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 three sentences that front-load the core purpose, then detail inputs and an optional flag. Every sentence contributes information, and there is no extraneous text.

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

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

Given the complexity of aggregating governance across multiple APIs, the description explains what is returned (per-api scores, estate aggregates, punch-list) and an optional parameter for more detail. However, it does not mention error handling or performance implications.

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 an empty properties object and additionalProperties:true, providing no structure. The description compensates by clarifying that apis is an array of objects with id and document, and that ruleset is user-provided. This adds essential meaning beyond the schema.

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

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

The description clearly states it runs governance checks across multiple APIs and rolls them up into aggregates. It uses specific verbs like 'run' and 'roll up', and distinguishes from siblings like api_scorecard (likely per-API) and governance_report (could be broader).

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

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

The description specifies required input (apis and ruleset) and an optional detail flag, but does not provide guidance on when to use this tool vs alternatives such as api_scorecard or validate_api. It lacks explicit when-to-use or when-not-to-use context.

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

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

No annotations provided. Description lacks behavioral details such as whether the topic must exist, if caching applies, or any rate limits. The 'PRO' tag suggests access restrictions but is not explained.

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 efficiently conveys the tool's output components. Slightly dense but not overly verbose; could benefit from structural separation.

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 1-param tool with no output schema, description adequately explains what the guide contains. However, output format or how to use the result is not mentioned.

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 topic with 100% description. Description adds concrete examples (e.g., 'gateways', 'api governance') and explains what the guide includes, adding meaningful context beyond the schema.

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

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

Description clearly states it produces a curated guide for an API topic, bundling multiple resource types. This distinguishes it from sibling tools like get_area or find_services, which return single 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 explicit guidance on when to use this tool versus alternatives. The 'PRO' prefix hints at premium status but doesn't clarify usage context.

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

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

No annotations are provided, and the description only mentions 'Free', which is not a behavioral trait. It fails to disclose destructive potential, authentication needs, rate limits, or how the tool behaves with invalid parameters.

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

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

The description is concise at one sentence, but it omits critical details. While efficient, it is under-specified for practical use, earning a middle score.

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 incomplete. It does not explain the output format, ranking methodology, or how parameters affect results, leaving significant gaps.

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

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

Schema description coverage is 0%, meaning the description adds no explanation for parameters. It does not clarify the meaning of 'page', 'type', or 'limit', nor the enum values of 'type'. The agent must rely solely on the schema, which lacks descriptive context.

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

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

The description clearly states the tool returns adoption rankings for services, tools, or standards, using the verb 'ranked'. This distinguishes it from siblings like 'find_tools' and 'get_tool', but lacks explicit differentiation from '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?

No guidance on when to use this tool versus alternatives. No context about prerequisites, typical use cases, 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, the description should disclose behavioral traits. It only mentions 'Free', but omits whether the tool is read-only, requires authentication, or has rate limits. No details on side effects or output structure.

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

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

The description is extremely concise at 12 words, but lacks structure. It front-loads key information about ranking and dimensions, though it could benefit from breaking into bullet points or adding a sentence about usage.

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

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

For a tool with no output schema, the description should explain the output format and ranking criteria. It does not clarify what 'by company signal' means or what the returned object looks like, making it incomplete for agent use.

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

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

Schema description coverage is 0%. The description does not mention the 'page' and 'limit' parameters or how to use them. This leaves the agent without guidance on pagination and data volume.

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 cross-section ranking of 40 tracked investment dimensions by company signal, with examples like AI and cloud. This distinguishes it from siblings that focus on individual companies or specific 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?

No explicit guidance on when to use this tool versus alternatives like 'find_areas' or 'get_stats'. The word 'Free' hints at no cost but does not specify 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 are provided, so the description bears full responsibility for behavioral disclosure. It mentions outputs (scorecard, flow map) but does not state whether the tool reads or writes, any side effects, authentication needs, or rate limits. The description is minimal for a tool producing derived artifacts.

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

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

The description is a single sentence that efficiently conveys the main action, input, and outputs without redundancy. It is slightly run-on but still clear and front-loads the core purpose.

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

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

Given the tool's complexity (mapping to scorecard and flow map) and the absence of an output schema, the description provides a high-level purpose but lacks details on expected input format (beyond 'from an APIs.json') and output structure. It is adequate for a basic understanding but not fully self-contained.

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 any additional properties. Schema description coverage is 100% (vacuously). The description adds no parameter details, but since there are no documented parameters, it is not penalized heavily. The baseline of 3 is adjusted upward because no parameters exist to explain.

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 being mapped: 'each REST operation to its MCP tool and Agent Skill'. It specifies the input source (APIs.json) and the outputs (coverage scorecard and flow map), distinguishing it from sibling tools like 'api_coverage' or 'api_scorecard'.

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 use when you have an APIs.json and want to map the API-MCP-Agent-Skill chain, but lacks explicit guidance on when to use this tool versus alternatives, or any exclusions or prerequisites.

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

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

With no annotations provided, the description must convey behavioral traits. It does not state whether the tool is read-only, destructive, or requires authentication. No side effects or limitations are mentioned.

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

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

The description is a single, short sentence that efficiently conveys the core action. However, it is not front-loaded beyond the first word, and the brevity sacrifices clarity.

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

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

Given the lack of annotations and output schema, the description is incomplete. It does not specify the input format, output structure, or any behavioral details, leaving significant gaps for an agent to invoke the tool correctly.

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

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

The input schema has a required 'document' property but no description. The text mentions 'from its schema' but does not explain what 'document' should contain (e.g., a valid OpenAPI schema). Schema coverage is 100% but the schema itself lacks details.

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

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

The description clearly states the tool's action ('Generate') and the resource ('example request and success-response payload'), specifying the scope ('for every operation from its schema'). This differentiates it from siblings like 'code_snippets' or 'diff_api_versions'.

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. There is no mention of prerequisites, context, or when not to use it.

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

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

The description discloses the main behavioral traits: it suppresses certain violations and surfaces others, returning a gate-able set. However, it does not mention side effects, required permissions, error states, or whether the operation is read-only. Without annotations, the description carries the full burden but provides only partial transparency.

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

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

Two concise sentences with no fluff. The first sentence states the core action, the second explains the outcome and return value. Every sentence earns its place.

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

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

Given no annotations and no output schema, the description lacks details about the waivers file format, the meaning of 'sanctioned violations', and the structure of the returned 'effective failing set'. The tool has two required parameters and complex behavior, so the description is insufficient for complete understanding.

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 required parameters 'waivers' and 'violations' but defines no properties (empty schema). The description adds meaning by naming them as 'waivers file' and 'lint output', but does not specify formats, constraints, or types. With 100% schema coverage (since description mentions both params), baseline is 3, and the description adds marginal value.

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

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

The description clearly states the tool's action ('Reconcile a waivers file against lint output') and specifies what it does: suppress sanctioned violations and surface expired/stale/expiring ones, returning the effective failing set. It distinguishes itself from sibling tools which are mostly find/get/validate operations, making purpose 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?

No guidance is provided on when to use this tool versus alternatives, nor does it mention prerequisites, context, or scenarios where it should not be used. The description only explains what the tool does, lacking any usage direction.

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 the tool is destructive, read-only, requires authentication, or what the output/return format is. The description only states the action without behavioral context.

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

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

The description is a single sentence that gets to the point. It is front-loaded with the primary action. However, the phrase 'the anti-sprawl view of an estate' is somewhat metaphorical and could be clearer, but overall it is concise.

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

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

Given no annotations, no output schema, and an open input schema, the description is insufficient. It lacks information on what the tool returns, any side effects, prerequisites, or how to specify which APIs to score. This is a significant gap for a scoring/detection 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?

The input schema has no defined properties but allows additionalProperties: true. Schema coverage is 100% because there are no properties, but the description adds no information about expected input fields. The tool likely accepts free-form input, which is undocumented, leading to ambiguity.

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 'score' and the resource 'reusability of a set of APIs', and adds 'detect duplication' for specificity. It distinguishes from siblings like api_coverage and api_scorecard by focusing on reusability and anti-sprawl.

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 assessing reusability and duplication, but provides no explicit guidance on when to use this tool vs. alternatives like api_scorecard or certify_api. No exclusions or context hints beyond the phrase 'anti-sprawl view'.

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 fails to state that the tool is read-only or disclose any behavioral traits such as rate limits, pagination behavior, or result structure beyond the schema.

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

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

The description is two sentences, front-loaded with the main purpose, and every sentence provides essential information without waste.

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

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

No output schema exists, and the description does not describe the return format or any behavioral details about results. Given the tool's complexity (8 parameters), crucial context is 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 only 25% (2 of 8 parameters described). The description adds meaning for the 'types' parameter by listing valid values, but does not explain parameters like page, sort, limit, match, or fields, leaving 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 'Unified search across the whole network' and lists a broad set of content types, distinguishing it from sibling tools that are category-specific find or get 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 implies usage for broad cross-category search but does not explicitly state when to use this over category-specific find tools, nor does it provide any exclusions 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 bears full burden. It discloses that the tool lints and returns findings, and mentions custom rulesets. However, it does not specify if the tool is read-only, any authentication needs, or rate limits. The behavior is implied but not fully transparent.

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

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

The description is only two sentences, both highly informative. The first sentence states the action and scope; the second provides a usage tip. No filler words, all sentences earn their place.

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

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

Given the tool's complexity (multiple spec types, custom rulesets) and the absence of an output schema, the description covers the main functionality and a usage hint. It could mention the format of findings or error handling, but overall it is complete enough for an agent to understand the tool's purpose and basic configuration.

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 sparse with no property descriptions and a confusing structure (0 params but required 'document'). The description adds meaning by indicating the primary parameter is a specification document and a 'ruleset' parameter exists. This compensates for the schema's lack of 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 clearly states the tool lints OpenAPI, AsyncAPI, Arazzo, or JSON Schema documents using Spectral, which is a specific verb and resource. It distinguishes from sibling tools like audit_pipeline or validate_onboarding by focusing on specification linting.

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

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

The description provides guidance on when to pass a custom 'ruleset' vs using the default catalog, and explicitly suggests using this before gating on anything. It lacks explicit 'when not to use' but gives clear context.

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

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

Without annotations, the description discloses core behavior (validation and reporting) but lacks details on side effects, authorization, or error handling.

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

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

Single sentence, concise, directly states purpose and output.

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 validation tool with one parameter and no output schema; describes input and expected report, though missing details on report 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 schema defines a 'descriptor' parameter with minimal structure; the description adds meaning by explaining it expects an AID and what validation entails.

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 validates an API Onboarding Descriptor (AID) against a schema and reports optional sections, distinguishing it from sibling tools like validate_api.

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

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

No guidance is provided on when to use this tool versus alternatives such as validate_api or verify_certificate.

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

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

No annotations provided, so description carries full burden. It explains failure conditions but does not state whether the tool is read-only, has side effects, or requires authentication.

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

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

Two sentences efficiently convey purpose and behavior with no extraneous 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 verification tool but lacks information about return values (e.g., boolean or error message), which is missing due to no output schema.

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

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

Schema has only required field names; description explains that `certificate` is a governance certificate and `api` is the API it attests to, adding essential meaning.

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

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

Description clearly states the tool re-verifies a governance certificate against its API and explains failure conditions. It is distinct from siblings like `certify_api`.

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

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

Context implies use for checking certificate validity; failure conditions are given. However, no explicit when-not-to-use or alternatives besides the implication that `certify_api` is for creation.

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