DETRAN PR: Veículo (Completa)

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

The description adds behavioral context beyond the annotations: it explains that the token is non-expiring if added to config, versus session-only when pasted. It mentions the browser login flow and the need for the user to paste the token. While annotations are present (idempotentHint, readOnlyHint), the description provides valuable detail about how the token is used and the permanence of the setup.

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 primary purpose, and uses a structured flow: browser login, copy token, then two alternatives (config or session). Every sentence contributes to explaining the authentication process, and it avoids 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?

Given the simplicity of the tool (one optional parameter, no output schema, no nested objects), the description is fairly complete. It explains the authentication flow for both permanent and session-based usage. However, it could have briefly mentioned what response or outcome the agent can expect (e.g., confirmation of auth), but given the low complexity, the description covers the essential 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 input schema has one optional parameter 'token' with no description, and schema description coverage is 0%. The description explains the semantics of the token parameter: it is a JWT that can be passed after the user pastes it, or omitted to get the login link. This adds meaning beyond the schema, but since there is only one optional parameter, the description's explanation is adequate though not extensive.

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: to authenticate an IDE agent (like Cursor) by logging in via browser, obtaining an access token, and either configuring it permanently or using it for a session-only login. It specifically identifies the action (authenticate) and the resource (MCP.AI server), which distinguishes it from siblings like 'show_version' or '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 explicit when-to-use guidance: it explains two usage scenarios: (1) adding a permanent header to the server config, and (2) passing a token for a session-only login, including the option to call with no args to get the login link. It implicitly differentiates from siblings by focusing on authentication context, and it gives clear alternatives (permanent vs. session-based).

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 cover read-only, non-destructive, and idempotent behavior. The description adds valuable conditional detail beyond annotations, such as authenticated:true with empty pending[] when connected, and connect_url plus per-install URLs when credentials are missing. No contradiction exists.

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 compact sentences, immediately front-loads the core purpose, and condenses both success and missing-credential behaviors into efficient, useful prose. No filler or repetition exists.

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 sufficiently complete: it identifies return fields and the two primary states. It could mention error behavior or exact output formatting, but neither is essential for this simple 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 input schema is empty with 100% schema coverage, so there are no parameter details to explain. The zero-parameter baseline applies, and the description adds no confusing or unnecessary parameter-related ambiguity.

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 a specific verb and resource: 'Returns connection status and URLs.' It also describes the two main output states, which makes the tool's purpose distinct from sibling tools like authenticate 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 description clearly implies when to use the tool: check whether providers are connected and retrieve URLs when credentials are missing. It does not explicitly name alternatives or say 'use authenticate to initiate credentials,' so it stops short of full 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 already mark the tool as read-only, idempotent, and non-destructive. The description adds meaningful context: data is from official Brazilian sources, is not confidential, is the same available to citizens, payment is via prepaid credit, no platform credentials are needed, and LGPD obligations belong to the client. This goes well beyond the annotation baseline.

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 core purpose and each sentence provides distinct information: source, hosting/payment, data classification, and LGPD responsibility. It is slightly repetitive in mentioning 'fonte oficial' and 'fontes e órgãos oficiais', but otherwise every sentence earns its place.

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 purpose, payment, legal context, and data sensitivity, which is strong for a simple read-only query tool. However, there is no output schema and the description never explains what data fields are returned or what the required parameters mean, leaving notable gaps for an agent deciding how to invoke 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% and the description provides no explanation for renavam, pkcs12_cert, or pkcs12_pass. The phrase 'sem credenciais da plataforma' could even confuse an agent since certificate credentials are still required. The description fails to compensate for the complete lack of 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 performs a vehicle query ('consulta') against DETRAN PR's official source, with scope 'Veículo (Completa)'. It also distinguishes itself from unrelated sibling platform tools (authenticate, connect, marketplace, etc.) and specifies the data comes from official Brazilian sources.

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 clear usage context: official source, no platform credentials required, prepaid pay-per-query, and non-confidential citizen-available data. It does not explicitly name alternative vehicle-query tools, but the sibling list contains no comparable data tools, so this is acceptable; however, no explicit when/when-not guidance is 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?

The description discloses numerous non-obvious behaviors: invoke works even when the MCP is not installed, it returns a connect link for auth, a checkout/top-up link for payment, and writes require workspace owner/admin. Annotations give minimal behavioral hints (readOnlyHint=false, etc.), so the description carries the burden and does so richly. No contradiction with 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 long but each sentence adds unique information given the tool's 14 actions. It is front-loaded with the core identity and organizes content around flow, key notes, and prompt library. However, it is a dense block of text; breaking it into bullets or sections would improve scannability.

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 core flow, auth/payment handling, permission requirements, and the prompt library, which is a lot for a complex tool. Yet some actions (e.g., resume, uninstall) and parameters (e.g., immediate, conversation) are omitted, leaving minor gaps. It is fairly complete but not exhaustive given the lack of an 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?

With 0% schema description coverage, the description must explain param meanings. It explains key params like action, mcp_id, tool_id, and arguments through the core flow, and the action enum values are described. However, many parameters (immediate, tier_slug, conversation, cancel_reason, prompt_targets, etc.) are not explained, leaving the agent with incomplete semantic knowledge. It partially compensates but not fully.

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 is 'the official mcp.ai marketplace' and 'the way to run them', distinguishing it from siblings like authenticate, connect, and toolkit_info. It specifies the resource (MCPs/tools and prompt library) and the actions (search, describe, invoke, etc.) it supports. This is a specific and informative 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?

The description provides explicit guidance on when to use different actions: 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT'. It also explains when to use list_tools, subscribe/cancel, report_bug, and request_mcp. This gives clear decision-making criteria for the agent.

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, destructiveHint=false, and readOnlyHint=false, so the description does not need to repeat these. It adds a behavioral hint about including conversation data for reproduction, which is useful context beyond the schema. No contradictions found.

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—and front-loads the purpose. Every word adds value, no filler or 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 feedback tool with no output schema, the description covers the core purpose and provides one key usage tip. It is sufficient for an agent to understand what to do, but lacks clarity on the 'context' parameter and potential side effects, though idempotentHint covers repeats.

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 clarify parameters. The description mentions the conversation array but not the 'message' or 'context' fields. 'message' is required and its meaning is implied, but 'context' is unexplained. The conversation field is described as an 'array' even though it's typed as string, which could be misleading.

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 clear verb and resource: 'Report a bug, missing feature, or send feedback.' It is specific about the three purposes and distinguishes itself from sibling tools like authenticate or connect, 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 instructs to include the conversation array for reproduction, giving clear context on how to use it. However, it does not explicitly state when not to use this tool or mention alternatives, but the sibling tools are unrelated enough that it's not necessary.

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 tool is marked readOnlyHint=true, idempotentHint=true, and destructiveHint=false in annotations, so the safety profile is already well-defined. The description adds meaningful context by specifying exactly what the tool reports—platform and adapter versions—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 a single, compact sentence that clearly states the tool's purpose with no filler or redundancy. Every word earns its place.

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, idempotent version-reporting tool with annotations already provided, this description is complete. It fully informs an agent of what the tool does, and no output schema or side effects need to be addressed.

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 zero parameters and 100% schema coverage, there is nothing for the description to clarify. The baseline of 4 applies, and the description 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 uses a specific verb ('Show') and a precise resource ('current MCP platform and adapter versions'), making the tool's exact purpose immediately clear. It is easily distinguished from the sibling tools, which cover authentication, connection, vehicle queries, marketplace, bug reporting, and toolkit information.

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 usage context: when you need to know the current version of the MCP platform or adapter. It does not explicitly discuss exclusions or alternatives, but given the simplicity and uniqueness of this tool, the context is sufficiently 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description goes beyond these by detailing the exact behavioral output (MCP statuses, connected accounts, catalog tool counts), which enriches the agent's understanding of what a read-only, non-destructive call will return. No contradiction found and the disclosure is highly informative.

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 core purpose ('Returns the current toolkit state') and then lists specific details without redundancy. Every word adds value, making it extremely concise and 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?

Given there are no parameters, no output schema, and comprehensive annotations, the description fully covers the necessary context for an agent to understand what this tool does and what information it will receive. The level of detail matches the task complexity perfectly, leaving no 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?

The tool has 0 parameters, so the schema provides complete coverage (100%). Per the rubric, the baseline is 4. The description focuses on return behavior rather than parameters, which is appropriate here since there is nothing to add about parameters. There is no penalty for not discussing parameters when none 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 uses a specific verb ('Returns') with a well-defined resource ('current toolkit state') and enumerates the exact components (installed MCPs, connection status, accounts, catalog tool counts). This clearly distinguishes it from siblings like `connect`, `authenticate`, and `show_version`. It is specific and 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 provides no explicit guidance on when to use this tool versus alternatives like `connect` or `show_version`. There is no mention of prerequisites, exclusions, or decision points. The usage context is only weakly implied by the name and return content, so it falls short of even 'implied usage' at level 3.

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