DETRAN ES: Veículo

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

Annotations already indicate non-destructive and idempotent behavior. The description adds context about session vs. permanent token handling but does not disclose additional behavioral details like error handling, side effects, or state changes. With annotations present, this meets the baseline but adds limited extra insight.

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 moderately sized but packed with essential usage details. It is front-loaded with the core action and then details both authentication paths. No redundant or filler sentences, though it could be slightly more concise without losing clarity.

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 what the tool returns. It mentions 'get the link' for no-args but does not state the return value when a token is provided (e.g., success/error message). It covers usage flows adequately but omits explicit return/error semantics, which could matter for agent decision-making.

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 single 'token' parameter. The description compensates well by explaining that the token is optional, used for session-only login when provided, and that calling without args yields a link. This adds meaningful meaning beyond the schema's bare property definition.

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: authentication for MCP.AI IDE agents. It specifies the action (log in, get token) and the resource (authentication access). It is distinct from sibling tools like connect or marketplace, as it is the sole authentication tool.

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 instructions offering two modes: permanent via server config or session-only via token parameter. It also explains that calling with no args returns a link. It does not explicitly state when not to use it, but as the only auth tool, 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 goes beyond the readOnly and idempotent annotations by detailing the different return states (authenticated vs. missing credentials) and the URLs provided. It does not mention any side effects or error scenarios, but since the tool is read-only and idempotent, the annotations cover core behavioral expectations, and the description adds useful outcome specifics.

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 well-structured: two sentences that first state the overall function and then explain the two possible return scenarios. It is easy to read and contains no unnecessary details.

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), the description provides sufficient context by explaining the main return states and URL paths. It does not cover edge cases like network errors or partial connectivity, but for a simple status check, it is reasonably complete and self-contained.

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 (empty schema), so there is nothing to add. According to the rubric, with full schema coverage, the baseline score is 3; the description does not need to elaborate on parameters that do not 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 clearly states the tool's purpose: returning connection status and URLs. It distinguishes between the two outcomes (authenticated vs. missing credentials) and specifies the exact data returned, making the tool's function 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 implies the tool is for checking connection status, but it does not explicitly state when to use it over alternatives like 'authenticate' or other sibling tools. There is no guidance on conditions that warrant using this tool versus others, so usage context is only indirectly inferred.

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 readOnly/idempotent/non-destructive, and the description adds important non-obvious context: prepaid credit cost, no platform credentials, hosted official data, non-confidential nature, and LGPD responsibility. No contradiction was found, though returns behavior and failure/edge cases are not covering.

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, front-loaded with the resource and action, and the legal/commercial context is given in short discrete sentences. There is some repetition of the word “oficial”, but it is minor and does not obscure the 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?

For a tool with six parameters, zero schema coverage, and no output schema, the description over-delivers. An agent would still struggle to know what return data is expected, what the optional login/cert fields do, and what makes a request valid.

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 no descriptions at all, and the description does not explain the meaning or formatting of placa, renavam, login_cpf, login_senha, pkcs12_cert, or pkcs12_pass. “Veículo” helps associate placa/renavam generally, but the agent would have to guess at credential-fields and value formats.

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 names the vehicle (“DETRAN ES”) and action (“consulta em fonte oficial”) and is unmistakably a read-only vehicle lookup. The siblings are platform utilities such as authenticate or marketplace, so this tool is clearly distinct.

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 useful context: it is an official no-costs-per-query citizen-level data query, not sensitive data, and the customer owns the LGPD purpose. However, it does not say the most explicit when to use this tool, when not to use it, or which alternatives are preferred.

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 disclosing that writes require workspace owner/admin, that invoke runs tools even when the MCP isn't installed and returns connect or checkout links when credentials/balance are missing, and that install makes tools natively available in future sessions. No contradiction with annotations; it enriches the safety/behavior model.

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 definition and core flow, and it packs a lot of operational guidance into a single dense paragraph. While almost every sentence adds information, the structure would benefit from bullet points or section headers, and some phrases are repeated.

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 14 action values and no output schema, the description covers the main outputs: describe returns full MCP profile, invoke returns either a run result or connect/checkout links, get_prompt returns filled text, publish_prompt returns a shareable link. It is less explicit about the return values for install/uninstall/subscribe/cancel/report_bug/request_mcp/resume, so it isn't fully 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?

With 0% schema coverage, the description compensates by explaining the central action enum and the workflow parameters (mcp_id, tool_id, prompt_slug, etc.), and by providing narrative context for prompt-library variables. However, it leaves several parameters unexplained, such as immediate and tier_slug, and the resume action is never mentioned, so the burden isn't fully lifted.

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 defines the tool as the official mcp.ai marketplace catalog and execution engine, with a concrete three-step flow (search → describe → invoke). It distinguishes this mega-tool from siblings by framing it as the platform-level catalog and runner, not a specific integration or utility.

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 guidance: use search then describe then invoke for one-off runs, prefer invoke over install for occasional use, use install only for permanent toolkit membership, and use list_tools to see currently callable tools. It also delineates subscribe/cancel, report_bug, request_mcp, and the prompt-library actions, providing a clear decision tree.

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 readOnlyHint=false (write action) and destructiveHint=false. The description adds context that the conversation array is needed for reproduction, which is useful behavioral information. However, it does not disclose side effects (e.g., creating a ticket) or response behavior, so it only partially adds value beyond 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 extremely concise: two sentences that front-load the purpose and immediately provide a key usage instruction. No fluff or repetition of schema basics.

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 simplicity of this tool (3 params, no output schema) and the annotations, the description covers the essential information—purpose and a critical usage detail. It doesn't elaborate on expected outcomes, but for a bug-report tool this is not a significant omission.

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 zero description coverage, so the description must compensate. It clarifies the 'conversation' parameter (include recent messages for reproduction) and implies 'message' is the main report content. However, the 'context' parameter remains unexplained, leaving a gap for agents unsure how to fill it.

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 exactly what the tool does: 'Report a bug, missing feature, or send feedback.' This is a specific verb+resource that clearly distinguishes it from siblings like 'authenticate' or 'show_version', 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 provides clear instructions on how to use the tool (including the conversation array for reproduction) and implicitly indicates when it should be used (for reporting issues). It doesn't explicitly exclude alternatives, but given the sibling list contains no similar tools, the usage context is clear.

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, which fully cover the tool's non-mutating behavior. The description adds no extra behavioral traits (e.g., return format, error handling) but doesn't contradict annotations. Credit is minimal beyond structured fields.

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, precisely stated, with no filler. It is front-loaded and every word 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 trivial zero-parameter, read-only tool with comprehensive annotations, the description is fully sufficient. It explains exactly what the tool reports, and no output schema is needed since the description implies it returns version strings. Sibling tools are distinct, so no additional context is required.

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?

There are zero parameters, so the baseline is 4. The description mentions 'current' versions and specifies 'MCP platform and adapter', providing semantic meaning about what is shown, which is useful even though no parameter documentation 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 'Show the current MCP platform and adapter versions' clearly states the verb (show) and the resource (versions of MCP platform and adapter). It distinguishes itself from sibling tools like authenticate, connect, and marketplace by focusing on version information, which is a distinct 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 implies usage context—use this tool to check version information. It doesn't explicitly state when not to use it or name alternatives, but with no parameters and a unique purpose among siblings, the context is clear and no exclusions are needed.

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 safety profile is well covered. The description adds value by specifying what the state includes (installed MCPs, connection status, accounts, catalog tool counts), which goes beyond the annotations. It doesn't mention potential latency or data freshness, but for a read-only info tool, 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, well-structured sentence that front-loads the purpose and lists the key output components. Every element earns its place, and there is no redundancy or filler. It is concise and informative.

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), the description is complete enough. It explains what the tool returns and the scope of the state. It could mention whether the state is real-time or cached, but for a toolkit info tool, this is a minor gap. The description covers the essential information an agent needs.

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 description doesn't need to explain any. The schema coverage is 100% (vacuously), and the description fully explains what the tool returns. With no parameters, a baseline of 4 is appropriate since the description compensates for the lack of parameter details by explaining the output.

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, listing specific elements: installed MCPs, connection status, connected accounts, and catalog tool counts. This is specific and distinguishes it from siblings like authenticate or connect, which perform actions rather than report state.

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 is a read-only informational tool for checking toolkit state, which is clear from the context. It doesn't explicitly state when to use it versus alternatives, but the purpose is distinct enough that usage context is clear. No exclusions or alternatives are mentioned, but the tool's role as a status reporter is evident.

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