Valor FIPE do Veículo

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

Annotations already mark the tool as idempotent and non-destructive, but the description adds valuable behavioral context: the token is a JWT, the config-header approach gives a non-expiring connection, and pasting a token provides only a session-level login. It also explains the no-arg call returns a link. This goes beyond the annotations, though it does not cover side effects like invalidating previous sessions 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?

The description is three sentences that are information-dense and well-structured: purpose, recommended permanent approach, and session-only alternative. It is somewhat verbose but every sentence adds necessary detail, and the core information is front-loaded.

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

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

For a simple one-optional-parameter tool with no output schema, the description covers usage modes well. However, it omits what the tool actually returns in each case (e.g., success message, session state, or error conditions). Since there is no output schema to fill this gap, the description is incomplete on return value semantics.

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 provides no description for the 'token' parameter (0% coverage), so the description must compensate. It does so by explaining that 'token' is a JWT copied from the browser, and that omitting it (no args) returns the auth link. This gives the parameter meaning and clarifies optionality, fully compensating for the schema gap.

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

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

The description clearly states the tool's purpose: authenticating via browser login and copying an access token, with two distinct modes (permanent config header vs session token). This makes the function specific. However, it does not explicitly differentiate from sibling tools like 'connect', so it doesn't fully meet the high bar for distinction.

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

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

The description provides explicit usage guidance: for permanent authentication, add the token as an Authorization header in the server config; for session-only login, call with a token argument or no arguments to get a link. This clearly indicates when to use each form of invocation, though it does not mention when to avoid this tool or compare it to 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, establishing a safe read-only profile. The description adds behavioral detail beyond annotations by specifying the exact return shapes for both connected and missing-credential scenarios. This provides valuable context without contradicting 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 two sentences, with the primary action front-loaded in the first sentence. Each sentence adds distinct conditional information without redundancy. This is optimally 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 the zero-parameter interface and no output schema, the description carries the full burden of explaining return behavior. It fully describes what is returned in both likely states (all connected vs. missing credentials). For a simple read-only status tool, this is 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 tool has zero parameters, so the baseline is 4. The input schema is an empty object with no properties to explain. The description adds no parameter-specific meaning because there are none to document.

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 identifies the resource as 'connection status and URLs.' It also explains conditional behavior (all providers connected vs. credentials missing), which clearly distinguishes it from sibling tools like authenticate. This is a clear, specific purpose.

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

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

The description provides clear context: it is for checking connection status, not for initiating authentication. However, it does not explicitly name alternative tools or state when not to use it, only implying that missing credentials yield a connect_url. With sibling tools like authenticate and toolkit_info, more explicit differentiation would be ideal.

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

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

Discloses key behaviors beyond the annotations: invoke works even when the MCP is not installed, runs one-off without bloating the tool list, requires admin for writes, and returns connect/checkout links when credentials or payment are missing. This aligns with openWorldHint=true and readOnlyHint=false, with 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?

The description is long but densely packed with necessary distinctions for a 14-action tool. It is reasonably front-loaded with the core identity and uses 'KEY:' to highlight critical behavior. It could be better organized with bullets, but every sentence contributes actionable context.

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

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

Covers the full lifecycle: discovery, description, invocation, installation, permissions, billing, prompt library, and alternatives. It even explains the installed_in_toolkit vs installed_in_workspace flags. Missing minor details like the 'resume' action, but overall it provides a complete mental model for a complex tool with 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?

The description adds meaning to the action parameter by enumerating all actions in prose and explains the role of tool_id, mcp_id (implied), and arguments. However, with 23 parameters and 0% schema coverage, many parameters (limit, query, immediate, tier_slug, conversation, cancel_reason, etc.) are left unexplained, so the description only partially compensates for the coverage 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 identifies the tool as the official mcp.ai marketplace, the in-platform catalog and execution engine for MCPs/tools. It explains it covers capability requests and also includes a prompt library, making its scope explicit and distinguishing it from sibling tools like connect or veiculo_fipe_consultar.

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 an explicit core flow (search → describe → invoke) and clear usage guidance: 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT', and 'report_bug sends feedback; request_mcp asks us to build a NEW MCP when nothing fits'. It also explains when invoke returns connect/checkout links instead of running directly.

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, so the safety profile is known. The description adds the contextual point that conversation history aids reproduction, but it does not disclose what happens after submission (e.g., response behavior, rate limits, or side effects). This is acceptable but not richly outlined.

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 concise sentences with no wasted words. It front-loads the primary purpose and immediately follows with a key usage instruction. Excellent structure.

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 sufficiently covers the main functionality and gives important input guidance. For a simple reporting tool, it is adequate, though it lacks details about return values, conversation format, and the optional context parameter. Given the absence of an output schema, this level of completeness is reasonable.

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 conversation parameter's role ('for reproduction') and the message parameter implicitly through the purpose. However, the context parameter is left unexplained. Additionally, the description says 'conversation array' while the schema defines conversation as a string, a minor inconsistency that could confuse.

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 and resource, and it distinguishes this tool from sibling tools like authenticate, connect, marketplace, and show_version, which serve entirely 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 gives clear context on when to use the tool (for reporting bugs/feedback) and provides an instruction to include the conversation array for reproduction. However, it does not explicitly mention exclusions or alternatives, though no direct alternatives exist 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, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds useful context by specifying exactly which versions are shown (MCP platform and adapter), but does not disclose any additional behavior beyond that.

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

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

A single concise sentence that front-loads the verb and resource. No filler or 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 tool is trivial—no params, no output schema—and the description fully captures its functionality. For a version-checking tool, nothing more is needed.

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

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

The tool has zero parameters, and the description implies no input is needed. With an empty input schema, the description adds just enough clarity by indicating the tool simply returns version information. Baseline 4 is appropriate for zero-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 a specific verb 'Show' with a clear resource ('current MCP platform and adapter versions'). It is precise and distinguishes this tool from siblings like authenticate, connect, or marketplace.

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

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

The purpose is so self-explanatory that usage is implied—checking versions—but there is no explicit when-to-use guidance or mention of alternatives. For a simple info tool, this is acceptable but not explicit.

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

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

Annotations already provide readOnly, idempotent, non-destructive hints. The description adds valuable context about what data is returned (MCPs, statuses, accounts, tool counts), going beyond the annotations to set expectations for the response content. 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?

The description is a single, well-structured sentence that front-loads the primary action ('Returns the current toolkit state') and then lists the specific components. Every word adds value, with no 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?

The tool is simple (no parameters, no output schema) and the description fully covers what the agent will receive: installed MCPs, their connection status, connected accounts, and catalog tool counts. Combined with the safety annotations, this is complete for the tool's 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 parameter details, and the schema confirms an empty property set, making the tool straightforward to invoke.

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 the current toolkit state, specifying the exact contents: installed MCPs, connection status, accounts, and catalog tool counts. This specific verb+resource structure distinguishes it from sibling tools like authenticate or connect, 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 usage when an agent needs an overview of the toolkit state, but it does not explicitly state when to use this tool versus alternatives or provide any exclusions. The context is clear enough but lacks direct 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?

Annotations already mark the operation as readOnly, idempotent, and non-destructive. The description adds significant behavioral context: it reveals the pay-per-query cost model, the absence of credentials, the public nature of the data, and the LGPD compliance responsibility. This goes well beyond the annotations and helps the agent anticipate side effects (cost) and legal constraints.

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

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

The description is a compact three-sentence paragraph. The main purpose is front-loaded in the first sentence, followed by practical and legal context. It is not overly verbose, though the LGPD sentence could be seen as extra for an AI agent, but it remains relevant for data privacy compliance.

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 with three parameters and no output schema, the description covers the purpose, identifiers, cost, authentication, data source, and legal aspects. The only notable gap is the lack of explanation for the 'completo' parameter and return value structure, but neither is critical for basic invocation.

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

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

The description explains that Placa and Chassi are vehicle identifiers used to fetch data, partially compensating for the 0% schema coverage. However, it does not clarify the optional 'completo' boolean parameter, and the phrasing 'placa ou chassi' is ambiguous given that both are required in the schema. This leaves some parameter semantics under-specified.

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: 'Dados de um veículo a partir da placa ou do chassi, com o valor de mercado na tabela FIPE' – a specific verb ('consultar' implied), resource (vehicle data via plate/chassis), and output (FIPE market value). It distinguishes itself from the unrelated sibling tools (authenticate, marketplace, etc.) by focusing on a unique vehicle lookup 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?

The description provides practical usage context: it is hosted by the platform, requires no credentials, and costs prepaid credit per query. It also clarifies that the data is public access, which sets expectations for when this tool is appropriate. However, it does not explicitly mention alternatives or exclusions, though none of the sibling tools serve a similar purpose.

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