ECRVSP Documentos: Impressão Baixa de Veículo

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

Annotations include idempotentHint=true and destructiveHint=false, but the description adds value by explaining that token-based login is non-expiring and session-only vs permanent. It also mentions the browser flow and token copy, which is behavioral context beyond annotations. No contradiction noted; the annotation hints align with the 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 concise, consisting of two sentences, and is front-loaded with the main purpose. It packs essential information about permanent vs session login, configuration, and token usage without redundancy. Slight improvement could be separating the config method from the call method for clarity, but it's generally 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 the simple schema (one optional token param) and no output schema, the description covers the main context: what authentication does, how to set it up permanently or for a session, and the token argument. It might mention what happens on success or failure, but that's not critical. The complexity is low, so 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?

The schema has 0% description coverage, so the description must add parameter meaning. It explains that 'token' is a JWT that can be passed for session login, and that calling with no args gets the link. However, it doesn't detail token format or required syntax beyond mentioning JWT. Baseline is low due to no schema description, but the description partially compensates; still, it's not fully explicit.

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 purpose: authenticate for MCP.AI IDE agents by either using a browser login or providing a token. It specifies the action (log in), the resource (MCP.AI server), and differentiates from siblings by focusing on authentication, while siblings like 'connect' or 'marketplace' likely 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 provides explicit usage guidelines: recommends adding the token to config for permanent access, or pasting it for session-only login. It explains both token and no-argument invocation with token input. This clearly indicates when to use and what to expect, with no exclusions or alternatives needed beyond the mentioned config method.

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, so the description goes beyond by explaining the response structure (authenticated flag, pending array, connect_url). It adds useful behavioral detail 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?

Description is two concise sentences that front-load the main purpose and then detail conditional outputs. No redundancy or irrelevant content.

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 has no parameters and no output schema, so the description must explain the return behavior. It covers the two key cases (connected vs. missing credentials) adequately, though it doesn't mention edge cases like partial connection states, but this is likely sufficient for the tool's simplicity.

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?

Tool has zero parameters, and schema coverage is 100% (empty schema). Baseline for 0 params is 4, and no additional parameter explanation is needed since there are none.

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 a specific verb ('Returns') and resource. It effectively distinguishes this from sibling tools like 'authenticate' or 'marketplace' by focusing on status 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 provides clear context on when to use it (to check connection status) and describes behavior under two conditions (all providers connected vs. missing credentials). It does not explicitly name alternative tools, but the scope is clear from the 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 declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds meaningful behavioral context beyond annotations: 'pague por consulta com crédito pré-pago,' 'sem credenciais da plataforma,' 'não é dado sigiloso,' and the LGPD controller responsibility. This helps the agent understand cost, authentication assumptions, and data sensitivity.

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 compact four-sentence paragraph with the purpose front-loaded in the first sentence. Each sentence adds relevant context: purpose, hosting/payment, official data source, and LGPD responsibility. It is not overly verbose, though the legal sentence is somewhat boilerplate.

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 six required parameters and no output schema, the description needed to provide parameter meanings and response expectations, but it does not. It gives good high-level context about official sources and payment, but an agent still cannot reliably construct a valid request or interpret the result.

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%, and the description does not explain any of the six required parameters (a3, a3_pin, login_cpf, login_senha, placa, renavam). It only indirectly suggests that credentials are not platform credentials, which is insufficient for an agent to know how to fill the fields correctly.

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 'ECRVSP Documentos: Impressão Baixa de Veículo, consulta em fonte oficial,' which names the specific resource (ECRVSP vehicle deregistration documents) and the action (querying an official source). This clearly distinguishes the tool from the generic sibling tools like authenticate, connect, and 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 gives practical usage context: 'sem credenciais da plataforma, pague por consulta com crédito pré-pago' tells the agent that platform auth is not needed and that prepaid credits are consumed per query. It also clarifies that the data comes from official Brazilian sources and is non-confidential, though it does not explicitly name alternative tools or exclusion conditions.

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 far beyond the annotations, disclosing that invoke runs MCPs one-off without installation, and that missing credentials or payment produce connect/checkout links requiring user action then retry. It also explains permission requirements and installed_in_toolkit vs installed_in_workspace flags, providing rich behavioral detail.

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 necessarily dense for a 14-action tool, and it is front-loaded with the core purpose and flow. Every sentence adds operational value, though a few phrases like 'without adding the MCP to the toolkit and without bloating the tool list' are slightly redundant.

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 complex tool with 23 parameters and no output schema, the description is remarkably complete: it covers discovery, one-off vs permanent execution, payment/auth fallbacks, permission constraints, installed-status flags, and the separate prompt library. This is sufficient context for an agent to decide which action to invoke.

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 compensates by explaining the central 'action' enum values in depth and clarifying the roles of tool_id, mcp_id, arguments, and prompt-related fields. It does not explicitly define all 23 parameters (e.g., limit, query, conversation), but the most decision-critical ones are contextualized.

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' and the way to run MCPs, immediately establishing its purpose. It explicitly lists the core flow (search, describe, invoke) and covers both MCP management and prompt library actions, making it distinct from the sibling tools.

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 gives strong internal action-selection guidance, such as 'prefer invoke for a single/occasional use' and 'use install only to make an MCP PERMANENT.' It also notes that writes require workspace owner/admin. However, it does not explicitly contrast with sibling tools like 'connect' or 'report_bug' even though the description mentions overlapping actions.

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, destructiveHint=false, and idempotentHint=true. The description adds the requirement to include a conversation array for reproduction, which is useful but doesn't disclose further behavioral aspects like potential confirmation or delayed processing. Given the annotation coverage, this is adequate but not rich.

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, immediately stating the purpose and the key procedural requirement (including conversation array). It is efficient and front-loaded with 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?

For a simple tool with 3 parameters and no output schema, the description gives an overview and hints at one parameter's use, but it omits details about the other parameters and expected outcome. While not a complex tool, the description could be more thorough about parameter expectations, especially since schema coverage is 0%.

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 description coverage is 0%, so the description must compensate. It mentions the 'conversation' parameter's purpose but does not explain 'message' or 'context' beyond the schema definitions. For a 3-param tool, this is insufficient compensation, leaving two parameters underspecified.

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 a bug, missing feature, or feedback. It also mentions the need to include the conversation array for reproduction, distinguishing it from the unrelated 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 clear context on when to use the tool (to report bugs, missing features, or feedback). While it doesn't explicitly state when not to use it or point to alternatives, the siblings are unrelated, so the usage 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 establish that the tool is read-only, idempotent, and non-destructive. The description adds that it covers both platform and adapter versions, but it does not disclose additional behavioral details such as output format or whether network access is involved. 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 a single, front-loaded sentence with no filler or redundant wording. Every word contributes to the tool's purpose.

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 low complexity, zero parameters, and strong annotations, the description is reasonably complete. It lacks an explicit mention of the return value structure, but the tool's purpose makes the output predictable.

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 does not need to explain parameter semantics. The input schema coverage is 100%, and the baseline for a parameterless tool is 4.

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 and resource ('Show the current MCP platform and adapter versions'), making the tool's function clear. It does not explicitly distinguish itself from the sibling 'toolkit_info', which could also be an informational tool, so it falls short of full differentiation.

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 usage context is implied: use this tool when you need current platform and adapter version information. However, it does not explicitly state when not to use it or mention alternatives like 'toolkit_info', so guidance is present but not strong.

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 this as read-only, idempotent, and non-destructive. The description adds value by disclosing the specific behavioral output: installed MCPs, their connection status, connected accounts, and exposed catalog tool counts. No output schema exists, so this return-content detail is useful, though it does not cover error cases or freshness semantics.

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 with front-loaded intent. It efficiently lists the key output categories without repetition or 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?

Given the tool's simplicity (no parameters, no output schema, strong annotations), the description sufficiently covers what the agent can expect: a state summary of MCPs, connections, accounts, and tool counts. It is complete for the tool's 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?

The tool has zero parameters and the schema is empty, so the baseline is 4 per the rubric. The description correctly implies that no input is required, and no parameter explanations 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 a specific verb 'Returns' and clearly identifies the resource: the current toolkit state. It enumerates exact content (installed MCPs, connection status, connected accounts, catalog tool counts), which also distinguishes it from siblings like show_version or authenticate.

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 this is the tool for inspecting toolkit/integration state, with no exclusion or alternative mentioned. While it does not explicitly state 'use this when you need to check connections', the context is clear enough for an agent to select it over action-oriented siblings.

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