Cadastro PF Plus

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

Annotations declare idempotentHint=true, destructiveHint=false, readOnlyHint=false, and the description does not contradict these. The description adds valuable context about persistence (permanent vs session-only) and the no-args behavior to get a link, beyond what annotations state. It stops short of explaining edge cases like invalid tokens or clearing existing sessions, but overall it discloses key behaviors.

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

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

The description is front-loaded with the primary purpose and then details two usage modes and the no-args behavior. It is somewhat dense and long, but every sentence adds necessary information. No filler words or repetition.

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

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

Given the tool's moderate complexity (two flows, optional token), the description covers the workflow thoroughly: browser login, token copy, config vs. session, and no-args call. It does not describe the return value or success/error behavior, but in the absence of an output schema this is a minor gap. Overall it provides enough context for an agent to select and invoke the tool correctly.

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

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

The schema provides only the token property name with no description and 0% coverage. The description compensates fully by explaining that the token is a JWT to be pasted for session-only login, that it can be omitted to get the link, and that a permanent connection can be set via config. This gives the agent complete understanding of the parameter's purpose and optionality.

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

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

The description clearly states the tool is for authenticating to MCP.AI for IDE agents, using a browser login and access token. It distinguishes itself from siblings by focusing solely on authentication and explaining the two login modes (permanent via config vs session-only via token). It is not a tautology and gives specific actionable steps.

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

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

The description provides clear context for when to use this tool: when setting up authentication for MCP.AI. It explains the two distinct flows (permanent config and session-only token) and how to call with or without the token parameter. However, it does not explicitly mention when not to use this tool or list alternatives, though none are apparent among siblings.

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

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

Annotations already declare readOnlyHint=true and idempotentHint=true, and the description adds state-dependent behavior: 'authenticated:true with empty pending[]' when all connected, and 'connect_url' when credentials are missing. This provides helpful context beyond what annotations offer, with no contradictions.

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

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

Two sentences, straight to the point. The first sentence states the core purpose; the second explains the two key behavioral cases. No fluff or redundancy.

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

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

The description covers the two main states (all connected vs. missing credentials) and the return values for each. It doesn't explicitly address partial connection, but for a simple read-only status tool with zero parameters, this is sufficient. No output schema exists, so the description's return-value details help fill that 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?

The tool has zero parameters, so schema coverage is trivially 100%. Baseline for 0-parameter tools is 4, and the description appropriately adds no parameter-specific detail because none exist.

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 ('returns') and identifies the resource ('connection status and URLs'). It clearly distinguishes from sibling tools like 'authenticate' by focusing on status retrieval rather than creating or modifying 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?

The description clearly implies usage: use this tool when needing connection status or connect URLs. It doesn't explicitly exclude alternatives, but the context makes it obvious when this is the appropriate choice, as opposed to tools like 'authenticate' or 'marketplace'.

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 this as read-only and idempotent, which the description complements by adding important behavioral traits: it is hosted by the platform, requires no credentials, incurs a cost per query, accesses only public official data (not private or confidential), and places LGPD compliance responsibility on the client. These details go well beyond 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 concise paragraph that front-loads the main purpose, then adds relevant context (hosting, authentication, cost, data classification, LGPD). Every sentence earns its place without redundancy or fluff.

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

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

For a simple read-only tool with two parameters and no output schema, the description provides sufficient context about purpose, access, cost, and legal compliance. However, it omits explicit guidance on the 'completo' parameter and does not describe the return data structure, which 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?

The input schema has two parameters (CPF and completo) with no descriptions (0% schema coverage). The description mentions 'expanded data' but does not explicitly explain the 'completo' boolean parameter or its effect on the response. The only hint is 'além dos dados básicos,' which is too vague to fully clarify the parameter's semantics.

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

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

The description clearly states the tool's purpose: it retrieves expanded registration data (dados cadastrais ampliados) for an individual from their CPF, in addition to basic data. This is a specific resource and action, and it distinguishes itself from the unrelated sibling tools (e.g., authenticate, report_bug).

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 useful context indicating when to use the tool: it queries public-access official data, requires no credentials, and is paid per query with prepaid credit. It does not explicitly mention alternatives or exclusions, but none of the sibling tools are competitors, so the context is sufficient.

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

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

The description discloses key behaviors beyond annotations: invoke runs uninstalled MCPs, returns connect/login links for credentials, returns checkout links for payments, and requires workspace owner/admin for writes. It also covers the prompt library's non-MCP behavior. No contradictions with annotations (readOnlyHint=false, openWorldHint=true) exist.

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

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

The description is dense and comprehensive, but somewhat lengthy. It is structured into clear sections (core flow, key caveats, prompt library) and every sentence adds value, though some could be tightened. The front-loaded core flow gives immediate orientation.

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 23 parameters, no output schema, and many actions, the description is remarkably thorough. It covers the primary flows, auth requirements, payment edge cases, role-based permissions, and the separate prompt library. It even notes the distinction between installed_in_toolkit vs installed_in_workspace, leaving little ambiguity for the agent.

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

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

With 0% schema description coverage, the description does substantial work by explaining the semantics of action values (search, describe, invoke, install) and the purpose of mcp_id, tool_id, and arguments. It does not cover all 23 parameters (e.g., limit, immediate, tier_slug), but it conveys the essential parameter relationships for the core flow, earning above baseline.

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

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

The description clearly identifies the tool as the official mcp.ai marketplace and explains its dual role as a catalog and execution engine. It distinguishes itself by listing concrete capability requests like 'find an MCP that does X' and 'consulta um CPF', and outlines the core flow of search → describe → invoke, making it unmistakable what the tool does.

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

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

The description provides explicit when-to-use guidance, e.g., 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT', and 'instead' alternatives like using search_calls_extensive (implied by structure). It also explains when to use report_bug and request_mcp, giving clear decision criteria for the agent.

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 idempotentHint=true, readOnlyHint=false, and destructiveHint=false. The description adds minimal behavioral context beyond that, such as the instruction to include conversation for reproduction, but does not disclose what happens after reporting (e.g., ticket creation) or any side effects. 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 concise and front-loaded, using two sentences to convey purpose and usage guidance without unnecessary words. Every sentence adds value.

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

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

For a simple tool with 3 parameters and no output schema, the description covers the main purpose and mentions the reproduction step, but it omits guidance on the 'context' parameter and does not describe the return value or post-report behavior. The conversation type mismatch further reduces 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 coverage, the description carries responsibility for parameter guidance. It mentions 'conversation array' but the schema defines conversation as a string (likely a serialized array), which is misleading. It does not explain the 'message' parameter's expected content or the 'context' parameter. Only partial and ambiguous parameter guidance is provided.

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 verbs and resources: 'Report a bug, missing feature, or send feedback.' This is explicit and distinguishes it from sibling tools, which are unrelated (authenticate, connect, 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?

The description indicates when to use the tool ('Report a bug, missing feature, or send feedback') and provides concrete guidance on reproducing the issue by including the conversation array. It does not explicitly mention when not to use it, but the sibling tools are unrelated, so there is no ambiguity.

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

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

Annotations already indicate readOnly and idempotent behavior. The description adds value by specifying that both platform and adapter versions are included, giving the agent clarity on what to expect from the output.

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

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

The description is a single, concise sentence that is front-loaded with the action and clearly states the output. Every word contributes meaning without any waste.

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

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

For a version-display tool with no parameters, annotations, and no output schema, the description adequately covers what the tool does and what it returns. It is complete within the context of its 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 tool has zero parameters, so the schema covers all inputs vacuously. The baseline for 0 params is 4; no additional parameter information is needed.

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

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

The description clearly states the tool's function with a specific verb ('Show') and resource ('current MCP platform and adapter versions'). It distinguishes itself from siblings like authenticate and report_bug, which serve different purposes.

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

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

The description implies usage when version information is needed, but does not explicitly state when to use it over alternatives or mention any exclusions. For a simple, zero-parameter tool in this context, implied usage is acceptable.

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, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds value by specifying exactly what state data is returned (MCPs, connection statuses, accounts, tool counts), which goes beyond the annotations and clarifies the tool's output behavior.

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

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

The description is a single, well-structured sentence that front-loads the purpose and enumerates the return components without any fluff or repetition. Every word earns its place, making it highly 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?

For a parameterless, read-only state inspector, the description fully covers the tool's purpose and return payload. Since there is no output schema, enumerating the returned fields (installed MCPs, connection status, accounts, catalog tool counts) provides complete contextual information.

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 accepts zero parameters, so there are no parameter semantics to clarify. Applying the baseline of 4 for descriptions with no parameters is appropriate; the description correctly omits any parameter-related explanation.

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

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

The description uses the specific verb 'Returns' with the resource 'current toolkit state' and enumerates the exact content: installed MCPs, connection status, accounts, and catalog tool counts. This clearly distinguishes it from the sibling action tools like authenticate or connect, which perform different operations.

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

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

The description clearly implies the tool is for inspecting toolkit state, providing context for when it should be used. However, it does not explicitly state when not to use it or name alternative tools for similar information, so it stops short of full usage guidance.

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