Situação da CNH

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

Annotations state idempotentHint=true, readOnlyHint=false, destructiveHint=false. The description adds context beyond these: calling with no args returns a login link, and passing a token authenticates for the session. It explains the flow clearly 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 bit lengthy but front-loaded with the target audience ('MCP.AI for IDE agents') and flows logically from permanent setup to session usage. Every sentence adds useful information, with no filler.

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

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

For a simple tool with one optional parameter and no output schema, the description covers the main use cases and invocation methods. It doesn't mention potential errors or post-auth state, but it's adequate for an agent to select and call the tool correctly.

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

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

Schema coverage is 0%, so the description must explain the 'token' parameter. It does so by stating it should be a JWT ("<jwt>") and used for session-only login. This gives sufficient meaning for a single optional parameter, though it doesn't elaborate on format or validation.

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: 'log in in the browser, copy the access token.' It explains the purpose and the two modes (permanent via config, session-only via token). It doesn't explicitly contrast with sibling 'connect', but the focus on authentication is unambiguous.

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

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

Provides explicit guidance for both usage scenarios: adding the token to server config for a permanent connection, or pasting it for a session-only login. It also states how to invoke the tool (with or without token). It doesn't reference alternatives like 'connect', but the guidance covers when and how to use this tool effectively.

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?

Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint), the description adds valuable context: the data is 'ACESSO PÚBLICO', no credentials are required, there is a per-query cost with prepaid credits, and the client is the data controller under LGPD. This significantly enriches the agent's understanding of the tool's behavior and applicable constraints.

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

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

The description is composed of four sentences, each adding distinct information: purpose, intended user, platform/payment details, and data/legal context. It is front-loaded with the primary purpose and avoids fluff, though it is slightly dense in its middle section.

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 query tool, the description covers the main purpose, usage restriction, data public nature, payment model, and LGPD responsibility. It does not explain the 'completo' parameter or the response format, but since there is no output schema and the tool is straightforward, this is a minor 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 schema provides no descriptions for the two parameters (0% coverage). The description only mentions CPF implicitly ('a partir do CPF'), giving it some meaning, but it completely ignores the 'completo' boolean parameter. Thus, the description only partially compensates for the missing 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 the tool's function: 'Consulta a situação da Carteira Nacional de Habilitação (CNH) de uma pessoa a partir do CPF.' It specifies the verb (consulta), the resource (situação da CNH), and the input (CPF), making it distinct from the unrelated sibling tools.

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

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

The description provides usage context: it is intended for the CNH holder to query their own license ('Feito para o titular consultar a própria habilitação'), and notes practical aspects like no credentials and prepaid payment. It does not explicitly mention alternatives, but the sibling tools are not similar, so this is not a significant omission.

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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is already known. The description adds valuable behavioral specifics beyond this: the state-dependent response with 'authenticated:true and empty pending[]' when connected, and the presence of 'connect_url for the toolkit and per-install URLs' when credentials are missing. It does not contradict 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 two sentences, both information-dense and front-loaded with the primary purpose. Every clause adds value by describing expected states and outputs, with no filler or repetition of schema/annotation content.

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

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

Given the tool's simplicity (no parameters, no output schema, no nested objects), the description is quite complete: it explains the two main states and their corresponding return values. It does not cover partial connectivity scenarios, but this is a minor gap for a status-check tool of this complexity.

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

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

The tool has zero parameters, so the baseline is 4. The description does not need to explain any parameters and correctly focuses on the behavior and return values, which are more relevant for this stateless status check.

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 specific verbs and resources: 'Returns connection status and URLs.' It distinguishes itself from the sibling 'authenticate' by focusing on status rather than the authentication action itself, and it details the conditions (all providers connected vs. missing credentials) that determine the output.

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 the tool is useful: to check if all providers are connected or to retrieve connect URLs when credentials are missing. It does not explicitly name alternatives or say 'use instead of authenticate,' but the scenario-based explanation implies its role as a status/readiness check, which is enough guidance.

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

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

The description goes well beyond the sparse annotations, disclosing that invoke works even when the MCP is not installed, returns connect/checkout links for auth/payment, and that writes require workspace owner/admin. It also reveals installed_in_toolkit vs workspace flags, providing rich 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 information-dense but presented as a single wall of text, mixing core flow, permissions, prompt library, and examples. It could benefit from structured sections or bullets. The use of 'pontualmente' may also confuse readers.

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 (23 parameters, no output schema, minimal annotations), the description covers the main functionality thoroughly: discovery, invocation, installation, billing, permissions, and prompt library. It omits some actions (e.g., resume) and specific params, but overall provides sufficient context for an agent 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?

With 0% schema description coverage, the description compensates by explaining the action parameter and its key values (search, describe, install, invoke, list_tools, etc.) and how tool_id is used. However, many secondary parameters (tier_slug, immediate, cancel_reason, etc.) are left to self-evident names, so coverage is incomplete but still valuable.

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, both a catalog of MCPs/tools and the way to run them. It outlines the core flow (search → describe → invoke) and distinguishes it from sibling tools like authenticate and connect by being the central hub for discovery and execution.

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 workflow guidance: 'Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile ... → invoke RUNS that tool.' It also contrasts install vs invoke ('Use install only to make an MCP PERMANENT ... prefer invoke for a single/occasional use') and notes list_tools for current capabilities. It doesn't explicitly contrast sibling tools, but the action-level guidance is strong.

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 non-destructive (destructiveHint: false) and idempotent (idempotentHint: true) behavior. The description adds that the conversation array should be included for reproduction, which is useful. However, it does not disclose what happens on submission (e.g., confirmation, privacy, rate limits). The description does not contradict 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: two sentences, front-loaded with the purpose and followed by a specific instruction. No redundant info.

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

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

For a simple bug-report tool with no output schema, the description covers the core action but misses details about the return behavior, the purpose of the 'context' parameter, and any post-submission effects. It is adequate but lacks completeness for a 3-parameter tool.

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

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

Schema coverage is 0% (no parameter descriptions). The description only mentions 'conversation array' explicitly, giving some meaning to that parameter, but leaves 'message' and 'context' unexplained. The description partially compensates for the low schema coverage but is insufficient.

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

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

The description clearly states the tool's purpose: 'Report a bug, missing feature, or send feedback.' This is a specific verb with a clear resource, and it distinguishes the tool from the listed siblings (authenticate, connect, etc.), which have different functions.

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 bugs/feedback) but provides no explicit exclusions or alternatives. It does give a usage hint about including the conversation array for reproduction, which adds some context but does not compare with 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?

The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds the detail that it reports both platform and adapter versions, but no further behavioral context (e.g., no authentication requirements, return format) is provided. Given the strong annotation coverage, this is adequate.

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

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

The description is a single, front-loaded sentence without any wasted words. It communicates the essential purpose efficiently.

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, zero-parameter, read-only version tool with rich annotations, the description fully covers what the tool does and what it returns. No output schema exists, but the mention of platform and adapter versions provides sufficient 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 schema trivially covers 100% of them. There is nothing to explain in the description, and a baseline of 4 is appropriate 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 uses the specific verb 'Show' with the resource 'current MCP platform and adapter versions,' clearly stating the tool's function. This is more specific than the generic title and sufficiently distinguishes it from sibling tools by naming the exact 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?

There is no guidance on when to use this tool versus alternatives. It does not mention context, prerequisites, or exclusions, leaving the agent to infer usage solely from the simplicity of the 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?

The description goes beyond annotations by detailing the exact return payload: installed MCPs, connection status, connected accounts, and catalog tool counts. Annotations already establish read-only, idempotent, and non-destructive behavior, so this additional content context adds meaningful transparency without redundancy.

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 entire description is one well-structured sentence that front-loads the core action ('Returns the current toolkit state') and immediately provides the key details. There is 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?

For a zero-parameter, read-only status tool with no output schema, the description is fully self-sufficient. It enumerates all the output categories, making the tool's behavior completely understandable without additional context.

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

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

The tool has zero parameters, which earns a baseline of 4. The description is not required to compensate for missing parameter information, and it does not attempt to, which is appropriate.

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

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

The description precisely states what the tool does: 'Returns the current toolkit state' with enumerated content (installed MCPs, connection status, accounts, catalog tool counts). It clearly distinguishes this info/status tool from sibling tools like authenticate, connect, and report_bug, which are action-oriented.

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 for inspecting toolkit state, but it does not explicitly state when to use this tool over alternatives or mention any exclusions. Given siblings like show_version may overlap, explicit guidance would improve clarity, but the purpose is clear enough to infer typical usage.

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