DETRAN AP: Veículo

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

Annotations already indicate idempotentHint=true, readOnlyHint=false, and destructiveHint=false. The description adds context about token provisioning (permanent vs session) and that calling with no args returns a link, which is beyond annotations. It does not describe failure modes or side effects, but it does not contradict the annotations, so a mid-range score is appropriate.

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 somewhat verbose with an introductory phrase 'MCP.AI for IDE agents (Cursor, etc.):' that could be trimmed. It front-loads the core action but then mixes config advice with usage examples, which could be structured better. It is not excessively long but not minimal either, warranting 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?

With no output schema, the description should clarify expected returns. It mentions getting a link when called without args but does not state what the tool returns on success with a token (e.g., confirmation or status). It also does not address error conditions or how it interacts with sibling tools like 'connect'. Given the tool's simplicity, this is acceptable but not 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 coverage is 0% for the token parameter, so the description must compensate. It explains the token is a JWT, that it is optional (calling with no args is allowed), and describes usage patterns. This gives meaningful semantics beyond the raw schema, though it could be more precise about the token format or expected 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 it is for authentication (log in, copy access token) and distinguishes the action as 'authenticate' for the server. It mentions the context of IDE agents and provides two modes (permanent via config, session via token), which clarifies its function. However, it does not explicitly contrast with siblings like 'connect', so it misses a direct 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 gives explicit usage instructions: call with a token to authenticate, or with no args to obtain a login link. It also explains the permanent config option versus session-only, which helps the agent decide how to invoke it. It does not state when *not* to use this tool or point to alternatives, but the context is clear enough.

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, so the safety profile is covered. The description adds useful behavioral detail beyond annotations by explaining conditional return values (authenticated:true vs connect_url) and the presence of pending[].

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, front-loaded sentences carry all essential information without waste. The first sentence states the core purpose, and the second adds conditional 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?

For a zero-parameter read-only status tool with no output schema, the description is complete: it covers the main return states and related URLs. No additional context is necessary for an agent to select and understand this 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 tool has zero parameters, so the baseline is 4. The description does not need to explain parameter behavior, and it instead focuses on the output semantics, 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 states a specific verb ('Returns') and resource ('connection status and URLs'), and clearly distinguishes this status-checking tool from the sibling 'authenticate' action. The conditional behavior further clarifies what the tool reports.

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 the tool—checking connection status and obtaining URLs—and describes behavior in different states, such as missing credentials. It does not explicitly name alternative tools or exclusions, but the intended use case is evident.

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 mark the tool as read-only and idempotent; the description adds meaningful behavioral context beyond that: prepaid credit cost per query, no platform credentials to the official source, the data is not confidential, and the client is the data controller under LGPD. No annotation contradiction is present.

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 the main purpose, followed by operational and legal details. The LGPD sentence is a bit dense but provides important usage constraints; overall there is minimal 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 simple read-only two-parameter query tool, the description covers purpose, official source, pricing model, credentials, data sensitivity, and legal responsibility. It would be more complete with parameter format details or expected return shape, but the description is reasonably 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 schema has 0% description coverage, and the tool description does not compensate by explaining the expected format or meaning of 'placa' and 'renavam'. The description only gives general vehicle-query context, leaving parameter invocation underspecified.

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 the action ('consulta') and the resource ('veículo DETRAN AP') and adds that it queries an official source. This clearly identifies the tool's purpose and distinguishes it from the unrelated sibling tools such as authenticate, marketplace, and toolkit_info.

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 an official vehicle query, paid by prepaid credit, requiring no platform credentials for the external source, and subject to LGPD responsibility. However, it does not explicitly state when to use the tool versus alternatives or what conditions should prevent its 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?

The description richly discloses behavioral traits beyond the minimal annotations: invoke works even when the MCP is not installed, one-off runs don't bloat the toolkit, connect/checkout links are returned for auth/payment needs, and writes require owner/admin. This goes far beyond the annotation hints and adds critical 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 long but dense with valuable information. It is structured as a flow, though a bit run-on; every sentence earns its place. Could benefit from bullet points or shorter sentences, but it remains readable and efficient for the tool's broad 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 the tool's complexity (multi-action marketplace plus prompt library) and absence of an output schema, the description is remarkably complete. It covers the core discovery/execution flow, payment/auth edge cases, installation semantics, permissions, and all major sub-actions, making it sufficient for an agent to select and invoke the correct action.

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 well by explaining the action-driven flow (search, describe, invoke, install, prompt actions) and connecting them to key parameters like tool_id, arguments, prompt_vars, and prompt_slug. However, it does not explicitly map all 23 parameters, leaving some (e.g., cancel_reason, tier_slug) implicit but inferable from 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 identifies the tool as the official mcp.ai marketplace and catalog of every MCP/tool, with the ability to run them. It explicitly distinguishes core actions (search → describe → invoke) and differentiates from sibling tools by covering the full marketplace/prompt library scope.

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?

Extensive usage guidance is provided: it explains when to use invoke vs install (prefer invoke for one-off, install for permanent), when to use subscribe/cancel, report_bug, request_mcp, and the prompt library functions. It also contrasts with list_tools and mentions owner/admin requirements for write actions.

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=false, destructiveHint=false, and idempotentHint=true. The description adds no extra behavioral context (e.g., side effects, permissions, or consequences), so it relies on the annotations without further elaboration.

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 carry all essential info without redundancy. No filler or irrelevant details, making it efficient and well-structured.

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 and lack of output schema, the description covers the core purpose and a key usage requirement. It does not explicitly state when to avoid using it, but this is not critical for a bug-report tool, so the overall context is adequately 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 description only adds meaning for the 'conversation' parameter (as a reproduction aid), but leaves 'context' and 'message' unexplained. With schema description coverage at 0%, this is insufficient compensation for three parameters, resulting in low semantic enrichment.

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 action ('Report') and the targets ('a bug, missing feature, or send feedback'), distinguishing it from sibling tools like authenticate or connect. The purpose is unambiguous and 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?

Provides implicit guidance by instructing to 'Include the conversation array with recent messages for reproduction', which tells the user what to provide. However, it does not explicitly contrast with alternative tools when one should choose this over others.

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, so the description does not need to restate these. It adds no further behavioral context (e.g., output format, whether network calls are made), but there is 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 a single, precise sentence that conveys all necessary information without any filler. It is front-loaded and highly 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?

For a simple read-only, idempotent version query with no parameters and no output schema, the description is complete. It clearly states what the tool does, and the annotations cover safety without the need for additional elaboration.

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, so the description does not need to explain parameter meanings. The baseline for 0-parameter tools is 4, and the description appropriately focuses on what versions are shown rather than parameter 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 'Show the current MCP platform and adapter versions' clearly states a specific verb ('show') and resource ('MCP platform and adapter versions'). It is unambiguous and distinct from the sibling tools, which focus on authentication, vehicle consultation, marketplace, 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 implies when to use the tool (when version information is needed) but does not explicitly mention alternatives or when not to use it. Given its simplicity, the context is clear enough, but it lacks explicit 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent already knows it's a safe read operation. The description adds valuable context by specifying what the state includes (installed MCPs, connection status, accounts, catalog counts) and the non-real-time nature implied by 'current state'. It doesn't contradict annotations and enhances them by detailing the data scope.

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 one sentence, front-loaded with the primary action, and contains no wasted words. Every clause adds a distinct piece of information about the return content, making it both concise and complete. It is appropriately sized for a zero-parameter tool with no complex 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?

Given the tool's simplicity (no params, no output schema) and the rich annotations (readOnly, idempotent, non-destructive), the description fully covers what an agent needs to know: it tells the agent what the tool does and what it returns. There is no missing information about behavior, side effects, or return format, given that the return format is inherently structured by the catalog description.

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 provides no parameter details. With 100% schema coverage (vacuously, since there are no properties), the description doesn't need to explain parameters, but it does need to clarify what the tool returns, which it does. It earns a baseline 4 due to no parameters, and adds value by describing the retrieved state.

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 a specific verb ('Returns') and resource ('current toolkit state'), and enumerates the exact information it provides (installed MCPs, connection status, accounts, and catalog tool counts). This distinguishes it from siblings like show_version and report_bug, which focus on version and issue reporting, respectively.

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 this tool is for checking the toolkit status, which is useful before operations. However, it doesn't explicitly state when to use it versus alternatives like authenticate or connect, nor does it mention when not to use it. Given its informational nature, this is a minor gap.

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