Consulta Veicular Estadual

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

Annotations already declare idempotent/non-destructive. Description adds the distinction between permanent config and session-only token, and explains the two invocation modes. It doesn't describe return values, but annotations cover safety.

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?

Three sentences, concise enough, each part adds value. Not as tight as possible but 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?

While the description covers the main use cases, it lacks explicit information about the return value for token validation and error handling. Given no output schema, some detail on expected response 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 schema has no description for 'token', and the description fully explains its meaning (JWT) and the behavior when omitted (returns link). This is high-value compensation for zero schema coverage.

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 performs authentication for IDE agents, explaining both modes (link generation and token validation). It doesn't explicitly differentiate from sibling 'connect', but the purpose 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?

It provides explicit instructions on when to use the config approach vs the tool, and when to call with or without token. It doesn't mention alternatives like 'connect' but gives clear usage context.

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 establish read-only, idempotent, non-destructive behavior. The description adds useful context about return values (authenticated:true, pending[], connect_url) under different conditions, going beyond what annotations provide.

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, front-loaded with the primary purpose and then detailing conditional outcomes. Every word earns its place with no 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?

For a simple 0-parameter tool with robust annotations, the description explains the main response states. It could be more explicit about partial connection scenarios, but overall it is sufficient for correct usage.

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 schema coverage is vacuously 100%. Baseline for zero-parameter tools is 4, and the description correctly adds no unnecessary 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 clearly states the tool returns connection status and URLs, with specific verbs and resource. It distinguishes itself from sibling tools like authenticate, which is an action, while this is a status check.

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 contextual usage information by describing behavior in different states (all connected vs. missing credentials), implying when to call it to check connectivity. However, it lacks explicit exclusions or direct comparison to alternative tools.

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?

For a tool with readOnlyHint false, the description discloses side effects and nuanced behaviors: invoke runs a tool 'without adding the MCP to the toolkit', can return a connect link or checkout/top-up link, and flags installed status on search/describe. It also clarifies the one-off install behind invoke and the prompt library's publish flow, providing substantial context 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 a lengthy single paragraph but packs high information density. It front-loads the primary purpose, then walks through the core flow, key exceptions, auth requirements, and the separate prompt library feature. While not bulleted, every sentence adds necessary behavioral detail; a few could be streamlined, but it remains efficient for the tool's complexity.

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 no output schema, the description provides return-relevant details for major actions (describe returns full profile, invoke returns connect/checkout links, get_prompt returns full text with vars filled, publish_prompt returns shareable link). It also covers permission prerequisites and the permanent vs. one-off distinction. Some actions like `list_tools` only get a terse 'lists what is callable right now', but overall it is sufficient for a tool of this breadth.

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 23 parameters with 0% description coverage, but the description compensates by explaining the semantics of `action` values (search, describe, install, invoke, list_tools, search_prompts, get_prompt, publish_prompt, etc.) and the flow between them. It does not define every parameter (e.g., `immediate`, `tier_slug`, `cancel_reason`), but the action-focused explanation covers the majority of usage scenarios.

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 opens with 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them,' which clearly identifies the tool's dual role. It further enumerates capability requests and the core search/describe/invoke flow, distinguishing its purpose from sibling tools like authenticate or connect.

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 guidance: 'Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile... → invoke RUNS that tool.' It also contrasts `invoke` (one-off) with `install` (permanent): 'Use install only to make an MCP PERMANENT in the active toolkit... prefer invoke for a single/occasional use.' It additionally notes permission requirements ('Writes require workspace owner/admin').

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 idempotentHint=true and destructiveHint=false, so the safety profile is clear. The description adds useful context about including conversation messages for reproduction but does not disclose what happens after submission, expected response, or any side effects.

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 short sentences, front-loaded with the core purpose and a single key usage note. No wasted words.

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, but the description lacks details on what happens after submission, response format, or how the conversation array should be formatted. Given no output schema and sparse parameter coverage, it is minimally adequate but leaves gaps.

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%. The description mentions the conversation array, which helps understand the 'conversation' parameter, but it does not explain the required 'message' parameter or the optional 'context' parameter, leaving meaning uncovered.

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: 'Report a bug, missing feature, or send feedback.' It is distinct from sibling tools, which are unrelated (e.g., authenticate, connect, 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 description implies when to use the tool (for reporting issues or feedback) but does not explicitly contrast with alternatives or mention exclusions. It provides some usage guidance by instructing to include the conversation array for reproduction.

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 cover these. The description adds a slight behavioral trait ('current') implying a live query, but it does not disclose additional details like output format, side effects, or error conditions. This is adequate given the annotations and simple nature of the tool, but no extra context is provided.

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 directly states the tool's purpose. It is front-loaded with the verb 'Show' and includes the necessary resource. Every word earns its place; there is no redundancy or extraneous 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?

Given the tool's simplicity (zero parameters, no output schema, clear annotations), the description is complete. It tells the agent exactly what the tool does and what information it returns (versions). There are no open questions about usage or side effects that would require further detail.

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 schema is empty, so the description does not need to explain any parameter meaning. With no parameters, the baseline is 4; the description adequately focuses on the tool's function without missing parameter 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 purpose with a specific verb ('Show') and resource ('current MCP platform and adapter versions'). It distinguishes the tool from siblings like 'toolkit_info' by naming exactly what versions are displayed. This is a specific, unambiguous purpose statement.

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?

No explicit guidance is provided about when to use this tool versus alternatives, nor are any exclusions or alternatives mentioned. The usage is implied by the purpose statement—the agent can infer that it should be called when the user asks for version information—but there is no explicit context or differentiation from sibling tools.

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 read-only, idempotent, and non-destructive behavior. The description adds value by detailing the exact content returned, which goes beyond the annotations. It does not mention any side effects or caveats, but none are apparent.

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, highly concise, and front-loaded with the main action. It lists the key output items without wasting words, achieving 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?

For a simple, read-only tool with zero parameters and no output schema, the description is complete. It fully explains what the tool returns, covering all relevant aspects of the toolkit state. No additional information 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 schema is empty, so parameter explanation is unnecessary. With 0 params, the baseline is 4, and the description correctly ignores parameters, focusing on 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 with specific data categories (installed MCPs, connection status, connected accounts, catalog tool counts). This distinct resource is separate from siblings like show_version, which focuses on version 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 implies usage when the user needs an overview of toolkit state, but it does not explicitly state when to use this tool instead of alternatives like show_version or marketplaces. No exclusions or alternative tool mentions are provided.

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 established. The description adds valuable behavioral context beyond annotations: payment per query, public access nature, and LGPD compliance responsibilities. This enriches the agent's understanding 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 concise and front-loaded with the core purpose, followed by operational details (hosting, payment), then legal context. Each sentence carries meaningful information without fluff or redundancy. It is appropriately sized for the tool's complexity.

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 main purpose, data source, access credentials, payment model, and legal handling. It lacks details on return format and the behavior of the 'completo' parameter, but given no output schema and the tool's straightforward nature, it is reasonably complete. The 'completo' gap slightly limits 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 description coverage, the description must explain parameters. It explains 'Placa' well ('a partir da placa'), but the optional 'completo' boolean is not described at all. Since there are only two parameters and one is left ambiguous, the description only partially compensates for the missing schema descriptions.

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 queries vehicle data by plate from DETRAN state databases, including debts and vehicle situation. The verb 'consultar' is in the tool name, and the description specifies the resource and scope, distinguishing it from the unrelated sibling tools (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 explains the hosting model, no credentials required, and prepaid credit per query, giving clear context on when to use this tool. It does not mention alternatives because there are no competing vehicle query tools among siblings, but it does not explicitly state exclusions or when-not-to-use scenarios.

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