DETRAN AL: Veículo

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

The description goes well beyond the annotations by explaining the permanent vs. session-only behavior, that no-arg calls produce a login link, and that token calls accept a JWT. It also clarifies how authentication state is expected to persist or expire, which is highly useful for an agent.

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 practical and nearly every sentence adds meaningful guidance about authentication setup, session persistence, and call behavior. It is slightly run-on and not perfectly structured by priority, but it remains effective and appropriately compact.

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 simple 1-parameter interface and no output schema, the description adequately covers return behavior (link), usage modes, and configuration guidance. It could also address token expiration or explicit error behavior, but for this tool's complexity, the description is sufficiently 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 and only an optional `token` string, the description carries the full burden of explaining parameter meaning. It explicitly says the token is a JWT to be pasted and that calling without args retrieves the login link, which fully compensates for the bare schema.

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 authenticate/log-in behavior and explains how tokens are provided, including both browser-centric and token-based flows. It is more specific than the tool name, though it does not explicitly distinguish itself from the related sibling tool `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 gives explicit usage guidance: the recommended permanent approach is to configure the Authorization header on the server, and a session-only login is available by passing a JWT. It lacks explicit when-not-to-use or alternatives beyond the two modes, but the practical 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 description explains exactly what happens in two key scenarios (all connected vs missing credentials), including the shape of the return data ('authenticated:true and empty pending[]' vs 'connect_url for the toolkit and per-install URLs'). This aligns with annotations (readOnly, idempotent) and adds valuable behavior detail beyond them.

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, direct, and free of redundancy. It efficiently conveys the tool's purpose and behavior without unnecessary filler.

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 a simple status check with no parameters and no output schema. The description fully explains the two possible outcomes and what is returned in each case, making it complete for an agent to decide and use.

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 schema coverage is 100%. Per the rubric, a high coverage baseline of 3 applies. The description adds no parameter info since there are none, 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 clearly states the tool's function: 'Returns connection status and URLs.' It distinguishes itself from sibling tools like 'authenticate' (which likely initiates auth) and 'show_version' (which shows version info) by focusing on connection status and provider connectivity.

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: whenever you need to check whether providers are connected or need connection URLs. It does not explicitly reference alternatives, but the scenarios described ('When all providers are connected' vs 'When credentials are missing') give 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?

Beyond the annotations (read-only, idempotent, non-destructive), the description discloses additional behavioral traits: it is hosted by the platform, requires no platform credentials, incurs costs via prepaid credits, queries only non-confidential official data, and mandates LGPD compliance. This adds meaningful context about the tool's operational behavior.

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 and repetitive, repeating the idea of querying official sources twice. While it is not excessively long, the structure could be tightened by removing redundancy and front-loading the core action more effectively.

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 tool's purpose, payment mechanism, and legal aspects, but it lacks details about the expected output or response format (since no output schema is provided). It also does not mention any preconditions or error scenarios, leaving some gaps in the operational 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 lists 'placa' and 'renavam' with no descriptions, and the tool description does not elaborate on these parameters. The description only mentions 'vehicle' generally, leaving the meaning and expected format of the parameters unexplained. This fails to compensate for the low 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 that this tool performs a vehicle query from an official Brazilian source (DETRAN AL). It explicitly mentions 'Veículo, consulta em fonte oficial' and distinguishes itself from generic platform 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 does not provide guidance on when to use this tool versus alternatives. It mentions prepaid credits and lack of credentials, but there is no explicit indication of the appropriate use cases or scenarios where this tool should be 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 discloses key behaviors beyond the annotations: invoke runs one-off without installing, install is permanent, writes require workspace owner/admin, and special-case returns for auth/payment. It adds rich context about side effects and permission requirements, and does not contradict any annotation.

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 dense paragraph that front-loads the primary purpose, but it is poorly organized and could benefit from separating sections (MCP catalog, invoke vs install decisions, prompt library). While every sentence contains valuable info, the lack of structure makes it harder to parse.

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 high complexity (14 actions, 23 params, no output schema), the description covers the main flows, decision points, permissions, and the prompt library. However, it omits some actions (e.g., resume) and parameters (immediate, tier_slug), so it is not 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 description coverage, the description must compensate. It explains the core flow parameters (action, mcp_id, tool_id, arguments) indirectly, but many parameters remain unexplained (limit, immediate, tier_slug, cancel_reason, prompt_targets, etc.), leaving an agent to infer their meaning from names alone.

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 runner of MCPs, and lists its core actions (search, describe, invoke, install, etc.). It also introduces the prompt library, but it doesn't explicitly differentiate from sibling tools like the standalone report_bug, which could create minor ambiguity.

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 vs alternatives: 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT'. It also explains the auth and payment flows (connect link, checkout/top-up link, then retry), and suggests request_mcp when nothing fits.

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 the instruction to include conversation data for reproduction, which is useful behavioral context. It does not describe side effects (e.g., creation of a report) or return values, but with no output schema and low complexity, this is acceptable. 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 two sentences with no filler. It front-loads the purpose and follows with a concise instruction. Every part earns its place; there is no 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?

For a simple tool with 3 parameters and no output schema, the description captures the core function and provides reproduction guidance. However, it omits details about the 'context' parameter and does not clarify what happens after reporting (e.g., acknowledgment). Still, it is sufficient for an agent to use the tool correctly for its intended purpose.

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 only explains the 'conversation' parameter ('Include the conversation array with recent messages for reproduction.'). The 'message' parameter is self-evident but not described, and 'context' is entirely unexplained. This leaves significant gaps for two of three parameters.

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.' It uses a specific verb ('report') and resource (bug/feedback), and the mention of including a conversation array for reproduction adds precision. It distinguishes from siblings, none of which relate to bug reporting.

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 implicitly defines when to use the tool—when the user encounters a bug, missing feature, or wants to provide feedback. It also instructs to include the conversation array, which is a contextual guideline. However, it doesn't explicitly mention when not to use it or alternatives, but the sibling tools are unrelated, so this is adequate.

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 false, covering the safety profile. The description adds that it shows 'current' versions, which is helpful context about the returned state, but it does not describe any further behavioral nuances. Given the annotations, this is adequate but not exceptional.

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, clear sentence with no redundant information. Every word earns its place, and it is immediately front-loaded with the verb 'Show' and the key object.

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?

This is a simple, zero-parameter, read-only tool. The description fully conveys what the tool does and provides enough context for an agent to select it correctly. No output schema exists, but the description naturally indicates what will be returned (versions).

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 there is nothing to explain. Per the baseline for 0 parameters, a score of 4 is appropriate. The description correctly focuses on the output (versions) without needing to elaborate on inputs.

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 specifies the exact resource ('current MCP platform and adapter versions'), making the tool's purpose unambiguous. It clearly distinguishes itself from sibling tools like authenticate or connect, which serve 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 implies usage: if you need version information, use this tool. However, it provides no explicit guidance on when to use it versus alternatives, nor does it mention exclusions. The purpose is self-evident, but explicit 'when to use' guidance is absent.

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 covered. The description adds useful behavioral context by specifying the exact snapshot contents (installed MCPs, connection/account status, catalog tool counts), which goes beyond 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, front-loaded sentence that immediately states the verb and resource, then adds precise details. Every phrase contributes useful information, with 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?

Given that the tool takes no parameters and has strong annotations, the description sufficiently covers return contents and likely usage. It could add a note about the output format or whether this is instant state vs. live probing, but overall it is complete enough for a simple status/overview 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 schema is fully comprehensive and no parameter documentation is needed. The description is appropriately focused on the return value rather than parameters.

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 a specific action ('Returns') and a specific resource ('current toolkit state'), then enumerates the exact contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This is distinct from sibling tools like authenticate or connect, so 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?

The description gives clear context about what kind of information the tool provides, making it apparent when to call it for a read-only overview of the toolkit. It does not explicitly name alternatives or exclusions, but the scope is concrete enough that the use case is well understood.

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