ECRVSP Veículos: Gravames

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

It discloses that calling with no arguments returns a browser login link, calling with a token enables session-only login, and config-based tokens provide a permanent non-expiring connection. This adds meaningful behavioral context beyond the simple annotations and does not contradict 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 front-loaded with purpose and uses three sentences to cover the entire workflow. The second sentence is somewhat dense with options, but each part earns its place and there is no redundant 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 description covers the essential authentication workflow: browser login, token acquisition, permanent config option, session-only token option, and no-args behavior. It doesn't describe response details or error cases, but for an auth tool with no output schema this 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?

With 0% schema description coverage, the description fully compensates by explaining that the optional 'token' parameter accepts a JWT access token pasted by the user, and that omitting it returns the login link. This gives the agent clear semantics for both parameter presence and absence.

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 authentication mechanism for MCP.AI IDE agents, explaining the browser login and token copy flow. It is specific about what the tool does, though it doesn't explicitly differentiate itself from the sibling 'connect' 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 gives concrete guidance on when to use each invocation mode: permanent config header vs. session-only pasted token, and no-args to fetch the login link. It lacks an explicit 'when not to use' or comparison against sibling tools, but the usage paths are clearly explained.

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 readOnly, idempotent, and non-destructive hints. The description adds value by explaining conditional return behavior (authenticated:true when all connected, connect_url when missing credentials). This goes beyond annotations but doesn't cover edge cases like partial connectivity or error states.

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, front-loaded with the primary purpose, and every sentence adds value. No redundancy or fluff, making it highly concise 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 low complexity (no params, simple return object), the description covers the main output states (all connected vs missing credentials). However, it does not address potential partial connection states or other error conditions, leaving some gap in 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 tool has zero parameters, and schema coverage is 100% (none documented). The description doesn't need to explain parameters. Baseline for 0 params is 4, and the description does not introduce any 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 clearly states the tool's function: 'Returns connection status and URLs.' It specifies the resource (connection status) and provides detail on outcomes (authenticated:true, empty pending[], connect_url). It distinguishes itself from siblings like 'authenticate' and 'marketplace' by focusing on status/URLs.

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 use for checking connection status, but does not explicitly state when to use it versus alternatives. It gives context (when credentials missing vs all connected) but lacks exclusions or comparisons to sibling tools like 'authenticate' or 'toolkit_info'.

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: it is a paid consultation, the data is not confidential, and the client is the data controller per LGPD. It also notes the absence of platform credentials, which clarifies authentication. However, it omits details about error handling, rate limits, or the exact nature of the returned data, which could be expected in a complete description.

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 relatively concise, consisting of a short paragraph with relevant details. It communicates the essential points without unnecessary verbosity, though it repeats the idea of official source consultation twice. The structure is acceptable and easy 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?

The description provides some context such as the official source, payment model, and data classification, but it lacks critical information about expected output, error conditions, and prerequisites like having a prepaid balance. It also does not clarify the meaning of several parameters, leaving the user without a complete understanding of how to invoke the tool successfully.

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 six parameters, but none have individual descriptions, and the tool description does not explain them. While placa (plate) and chassi (chassis) are self-explanatory, fields like a3 and a3_pin are unclear. login_cpf and login_senha are recognizable but their purpose is not elaborated. The lack of semantic explanation for these parameters significantly reduces usability.

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 the tool performs a consultation of vehicle liens (gravames) from an official source. It explicitly identifies the resource and action, and the tool name reinforces this. No ambiguity exists about what the tool does.

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 guidelines such as the payment model (prepaid credit), the official nature of the data, and LGPD compliance, implying when it might be used. However, it does not explicitly state when to use this tool over alternatives, though the sibling tools are unrelated and no direct alternatives exist.

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 sparse annotations, the description discloses key behavioral traits: invoke runs one-off without bloating the tool list, credentials produce a connect link, empty wallet produces a checkout/top-up link, writes require workspace owner/admin, and search/describe flag installation state. These are meaningful operational details that go well beyond the annotations and help the agent anticipate 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 long but densely informative, and every sentence adds operational value for a 14-action, 23-parameter tool. It is reasonably front-loaded with 'Core flow:' and 'KEY:' signposts, though it remains a wall of text that could benefit from bulleted structure and avoids the unnecessary Portuguese insertion 'pontualmente'.

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, no output schema, and sparse annotations, the description covers most of the important workflow: search/describe/invoke, install vs. permanent, billing, permissions, and the prompt library. Still, it does not specify return shapes for search/describe/list_tools, nor clarify actions like resume or parameters like immediate/tier_slug, leaving some gaps for an agent hitting edge cases.

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 and 23 parameters, the description carries a heavy burden. It effectively explains the central 'action' parameter, key identifiers like tool_id and mcp_id, and prompt-related variables such as prompt_slug and prompt_vars. However, several parameters—limit, immediate, tier_slug, cancel_reason, conversation, and request_details—receive no semantic explanation, so it does not fully compensate for the schema gap.

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 a specific definition: 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It clearly explains the core search → describe → invoke flow and distinguishes this meta-tool from siblings like report_bug, authenticate, and connect by enumerating its catalog, installation, billing, and prompt-library responsibilities.

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 an explicit decision path: search discovers MCPs, describe returns profiles, invoke runs one-off, and 'use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use.' It also separates prompt-library actions from MCP actions and explains when report_bug or request_mcp should be used, providing strong when/when-not 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 indicate readOnlyHint=false, idempotentHint=true, and destructiveHint=false. The description adds context about including the conversation array for reproduction, but does not disclose more about side effects (e.g., ticket creation, email sending). It neither contradicts annotations nor provides deep behavioral insight beyond the minimal instruction.

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. However, it omits essential parameter details that could be included without much verbosity. Overall, it is appropriately brief but could be more informative without becoming lengthy.

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 has 3 parameters, one required, and no output schema, the description is insufficient. It does not explain how to craft the 'message' field (the core input) or the role of 'context'. The instruction about the conversation array is helpful, but the description fails to cover the full scope of inputs and what happens after the report.

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 mentions the 'conversation' parameter ('Include the conversation array with recent messages for reproduction'), but does not clarify the required 'message' parameter or the optional 'context'. This leaves most parameters under-specified.

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: reporting bugs, missing features, or sending feedback. It uses a specific verb ('Report') and resource ('a bug, missing feature, or send feedback'), which is distinct from sibling tools like 'authenticate' or 'ecrvsp_veiculos_gravames_consultar'.

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 a usage hint ('Include the conversation array with recent messages for reproduction') but does not explicitly state when to use this tool versus alternatives or when not to use it. The purpose is implied, but no explicit exclusions or alternatives are mentioned.

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 readOnly and non-destructive behavior. The description adds no additional behavioral context beyond the action itself, but does not contradict 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, concise sentence that conveys all necessary information without any redundant words or 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 absence of parameters and an output schema, the description fully covers the tool's purpose and usage context. There is no missing information that a user would need.

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, so schema coverage is trivially 100%. The description does not need to elaborate on parameter semantics, aligning with the baseline for high 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's function: showing current MCP platform and adapter versions. It is specific and unambiguous, leaving no doubt about what the tool does.

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 (to check versions) and there are no competing alternatives, so no exclusions are needed. It could explicitly mention that it's for version retrieval, but the intent 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds value by specifying exactly what state information is returned (MCPs, status, accounts, tool counts), providing transparency about the output 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 a single, front-loaded sentence that immediately states the purpose and enumerates return contents. Every word is informative, with no fluff or repetition.

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?

As a simple, zero-parameter, read-only tool with no output schema, the description sufficiently explains the return value by listing its four key components. It is complete for an agent to understand what the tool provides.

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 accepts zero parameters, so the baseline is 4. The description correctly omits parameter details because there are none, and the schema coverage is 100% (empty properties). No additional parameter semantics are 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 uses the specific verb 'Returns' and identifies the resource as 'current toolkit state', listing concrete components (installed MCPs, connection status, accounts, catalog tool counts). This clearly distinguishes it from sibling tools like authenticate or connect, which serve different purposes.

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 states what the tool returns and implies it should be used when an overview of toolkit state is needed. While it does not explicitly mention alternatives or when-not-to-use scenarios, the context is unambiguous and sufficient for an agent to select it appropriately.

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