APF Rural

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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds valuable context about the commercial model (pay-per-query), hosting, public data nature, and LGPD responsibility, which goes beyond the annotations. It does not detail output format but this is not required.

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 (four sentences) and front-loads the primary purpose. The legal LGPD statement is relevant for data protection context and does not feel excessive, though it could be trimmed without losing core meaning.

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

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

Covers access type, payment, and data sensitivity, but misses the practical combination of input parameters (all required vs any one) and the optional 'completo' flag. No output schema is present, so a note on return structure would improve completeness.

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

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

With 0% schema description coverage, the description must explain parameter meanings. It lists the identifier fields but does not clarify formats, the contradiction between 'ou' and required status, or the optional 'completo' parameter. This leaves significant ambiguity for the AI agent.

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 ('Consulta') and the resource (APF Rural) and lists the input identifiers (CPF, CNPJ, APF number, CAR). It effectively distinguishes the tool from the unrelated sibling tools, though the 'ou' (or) phrasing conflicts with the schema's requirement for all four identifiers.

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

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

Provides useful context such as no credentials needed, prepaid credit payment, and public data access. However, it does not explicitly state when to use this tool versus alternatives or any exclusions, relying on the platform context to imply 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?

The description discloses behavioral nuances beyond the annotations: it explains that config-based tokens are permanent and non-expiring, while pasted tokens are session-only, and that calling with no args returns a link. This adds context about side effects and state, aligning with idempotentHint and destructiveHint annotations without contradiction.

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

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

The description is compact and front-loaded, with two sentences covering purpose, usage modes, and config alternative. It is information-dense without redundancy, though slightly long due to the detailed instructions; 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?

For a simple tool with one optional parameter and no output schema, the description covers both call modes, the recommended config setup, and the user's login flow. It lacks explicit details on the return value when a token is passed, but this is a minor gap given the tool's simplicity.

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

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

The description fully explains the optional 'token' parameter: it is a JWT used for session-only login, and the no-arg invocation returns a login link. This completely compensates for the 0% schema description coverage, providing syntax and behavioral meaning beyond the bare schema field.

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

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

The description clearly identifies the tool as an authentication mechanism for MCP.AI in IDE agents, with a specific workflow: log in via browser, copy token, and either add to config or pass as parameter. It distinguishes from siblings by explicitly naming 'MCP.AI for IDE agents (Cursor, etc.)' and detailing the login process, making its 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?

The description gives explicit usage instructions: call with no args to get a login link, call with { token: "<jwt>" } for session-only login, and recommends adding the token to config as a permanent alternative. It clearly explains when to use each mode, though it does not explicitly compare to sibling tools like 'connect'.

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

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

Annotations already declare read-only, idempotent, non-destructive. Description adds conditional response details (authenticated:true and empty pending[] vs connect_url with per-install URLs), which goes beyond annotations. No contradiction.

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

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

Two sentences, front-loaded with the main purpose, no filler.

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

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

For a zero-parameter status tool, the description explains return states adequately. It could clarify what 'pending' represents, but overall sufficient given annotations.

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?

Tool takes zero parameters, so schema coverage is complete. Description adds no parameter details as none exist. Baseline 4.

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

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

Clearly states it returns connection status and URLs, with conditional behavior for connected vs missing credentials. Distinguishes from siblings like 'authenticate' by focusing on status, not 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 explicit when-to-use or alternatives. The description implies usage for checking connection status, but does not mention when not to use or direct to 'authenticate' for authentication flows.

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 critical behaviors beyond annotations: invoke works even when the MCP is not installed, returns a connect link for credentials or checkout link for payment, and writes require workspace owner/admin. These nuances are not visible in annotations and are essential for correct 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?

The description is long but logically organized with labeled flows ('Core flow:', 'KEY:', 'Search/describe', 'Writes', 'It also carries the PROMPT LIBRARY'). Every sentence contributes meaningful information, though a bit more formatting or bullet points could improve scanability. The density is appropriate for the tool's 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?

Covers all major functional areas: discovery, description, invocation, installation, billing, feedback, and prompt library. It explains what happens when credentials are missing or wallet is empty, and mentions installed_in_toolkit vs installed_in_workspace flags. Given the tool's complexity and absence of an output schema, this is nearly complete, though per-action return formats could be more detailed.

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 23 parameters and 0% schema description coverage, the description takes on the burden and does so well for core parameters: action, mcp_id, tool_id, arguments, prompt_slug, prompt_vars. It explains the meaning of each action enum value and key inputs, though it does not exhaustively cover all parameters like limit, immediate, or cancel_reason. Still, it adds substantial 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 opens with a clear, specific statement: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It goes on to explain the core flow (search → describe → invoke) and distinguishes itself from sibling tools like toolkit_info or authenticate by framing itself as the central catalog and execution layer.

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

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

Provides explicit when-to-use guidance: 'Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use.' It also clarifies list_tools for currently callable tools, and differentiates the prompt library workflow (search_prompts/get_prompt/publish_prompt). This gives clear direction on action selection and alternatives within the tool.

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

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

The annotations already provide safety hints (readOnlyHint=false, destructiveHint=false, idempotentHint=true). The description adds the requirement to include the conversation array for reproduction, which is useful context, but does not disclose other behavioral traits such as side effects or response behavior. It does not contradict the annotations.

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

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

The description is a single sentence that front-loads the purpose and includes a key usage instruction. Every word earns its place, with no filler or repetition.

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

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

The tool is simple with three parameters and no output schema. The description provides the core purpose and one parameter instruction, but leaves the required 'message' parameter unexplained and does not describe what happens after reporting. Given the lack of an output schema, this is a moderate gap.

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 purpose of the 'conversation' parameter (recent messages for reproduction) but does not explain the required 'message' parameter or the optional 'context' parameter. With three parameters and only one addressed, the compensation is incomplete.

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

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

The description clearly states the tool's purpose: 'Report a bug, missing feature, or send feedback.' The verb 'report' is specific and the inclusion of the conversation array for reproduction further clarifies its role. It is distinct from sibling tools which are unrelated.

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

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

The description implies when to use the tool (when reporting issues) and gives a concrete usage instruction ('Include the conversation array with recent messages for reproduction'). It does not explicitly mention alternatives or exclusions, but the context is clear enough given the unrelated 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?

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is clear. Description adds no extra behavioral details beyond what annotations provide, but does not contradict them.

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

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

Single sentence, no wasted words, and front-loaded with the action and object. Extremely 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?

Tool is simple with no parameters, no output schema, and annotations covering safety. Description sufficiently explains what the tool does, making it complete for this low-complexity tool.

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

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

Tool has zero parameters, so description need not explain them. Baseline for 0 params is 4, and no further explanation is required.

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

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

Description uses specific verb 'Show' and resource 'current MCP platform and adapter versions', clearly stating what the tool does. It distinguishes from siblings by focusing on version information, which is a unique purpose.

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

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

No guidance on when to use this tool versus alternatives like toolkit_info. There is no mention of when this should be preferred or any context for use.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, establishing this as a safe read operation. The description adds value beyond these by specifying exactly what data is returned (installed MCPs, their connection status, accounts, catalog tool counts), providing concrete behavioral context without contradicting annotations.

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

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

The description is a single, well-structured sentence that front-loads the verb and resource, then provides a compact list of return details. Every word contributes meaning, with no redundancy or filler.

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

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

Given the tool has no parameters, no output schema, and simple read-only behavior, the description is sufficiently complete. It tells the agent exactly what the response will contain, which is all that is needed for 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?

The tool has no parameters, so the schema covers everything with 100% coverage. Per the rubric, a 4 is the baseline for zero-parameter tools because there is no parameter ambiguity to clarify.

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 the specific verb 'Returns' and clearly defines the resource as 'current toolkit state', enumerating exact contents (installed MCPs, connection status, connected accounts, catalog tool counts). This distinguishes it from siblings like 'show_version', which likely only reports a version number.

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 inspecting the overall toolkit state, and the read-only nature is clear from annotations. However, it does not explicitly state when to choose this over alternatives like 'show_version' or 'connect', so it misses explicit exclusions or alternative guidance.

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