DETRAN GO: Gravame

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

Annotations indicate readOnly=false and idempotent=true, which are not contradicted. The description adds transparency by explaining the persistence of the token (permanent vs session-only) and that the token is a JWT. It doesn't explicitly mention side effects like modifying server config, but the description's mention of 'add it to this server's config' implies that. Given annotations exist, the description provides sufficient additional context.

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 slightly verbose but well-structured with 'Best:' and 'Or' to separate the two authentication paths. It conveys all essential information in a compact form without unnecessary fluff. The clarity outweighs the minor 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?

The description covers the tool's purpose, usage, and parameter semantics completely. It lacks explicit mention of what the tool returns (e.g., a success message or token), but given no output schema, this is not required. It adequately explains both authentication modes and how to initiate the process, making it complete enough for an authentication 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 single optional parameter 'token' is described thoroughly: it is a JWT that the user pastes after logging in, and passing it enables session-only login. The description also clarifies that omitting the parameter (no args) will return the login link. This exceeds the schema's bare type definition by explaining the value's purpose and optionality.

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: authenticating to MCP.AI for IDE agents. It distinguishes between two authentication methods (permanent and session-based) and is clearly distinct from sibling tools like connect or marketplace. The verb 'authenticate' plus specific instructions make the purpose 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 explicit step-by-step guidance: log in via browser, copy token, and either add to config for permanent access or pass token for session-only login. It also instructs to call with no args to get the link. This fully explains how and when to use the tool.

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, so the safety profile is known. The description adds valuable context about return states—authenticated:true with empty pending[] versus connect_url for the toolkit and per-install URLs—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 two focused sentences, with the core purpose front-loaded. Every sentence adds meaningful behavioral detail without redundant wording.

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 fully connected and missing-credentials states well, but it omits partial-connection behavior and the structure of pending[] or the returned URLs. Given no output schema exists, the description could slightly expand on these 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?

The tool has zero parameters, so there are no parameter semantics for the description to explain. Baseline 4 applies because there is nothing to add beyond the empty 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 states the tool returns connection status and URLs, with specific conditions for authenticated:true and connect_url responses. This distinguishes it from siblings like authenticate and toolkit_info by focusing on connectivity state.

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 contextual behavior ('When all providers are connected' vs 'When credentials are missing'), which implies when it is useful for checking connection state. It does not explicitly mention alternatives or exclusions, but the scenarios are clear enough.

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 readOnlyHint/idempotentHint/destructiveHint annotations, the description adds meaningful context: no platform credentials, prepaid-credit payment model, official non-confidential data source, and LGPD data-controller responsibilities for the client. These are valuable behavioral/legal traits not present in the annotations, with no contradiction.

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 three sentences are dense and purposeful: purpose first, then payment/access details, then compliance. Every sentence earns its place 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?

For a simple one-parameter, read-only tool with strong annotations, the description covers purpose, access, payment, and legal constraints. It doesn't describe the return payload, but with no output schema this is a minor gap; a note on the returned gravame information would make it 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?

Schema description coverage is 0% and the description never mentions the 'chassi' parameter, its format, or expected input. Although the parameter name is self-explanatory to Portuguese-speaking users, the description fails to compensate for the schema's lack of detail, leaving the agent with no additional guidance.

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 'DETRAN GO: Gravame, consulta em fonte oficial', which clearly identifies the action (consulta/query) and the specific resource (Gravame from DETRAN GO). This distinguishes it from unrelated siblings like authenticate or marketplace, making the tool's purpose 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 clear usage context: hosted by the platform, no platform credentials required, pay-per-query with prepaid credit, and that it queries official citizen-available data. It doesn't explicitly state exclusions or alternatives, but the sibling tools are not alternatives, so the context is sufficient for a 4.

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 side effects beyond the annotations (readOnlyHint=false, openWorldHint=true): invoke runs the tool one-off without installing it, install makes permanent changes, and writes require workspace owner/admin. It also details conditional behaviors, such as returning a connect link when credentials are needed and a checkout/top-up link when the wallet is empty.

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?

For a tool with 14 actions and two broad capabilities, the description is long but efficiently structured: overview, core flow, key invoke nuance, install-vs-invoke guidance, billing/feedback actions, and prompt library. It uses short sentences and bolding to emphasize critical distinctions. A few repetitive phrases could be trimmed, but the length is justified by 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 thoroughly covers the main workflows, auth requirements, and conditional outcomes, and it distinguishes installed_in_toolkit vs installed_in_workspace. With no output schema and 23 parameters, this is more complete than typical. Gaps remain for less-central parameters and prompt-library details, but the overall context is strong.

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, so the description carries the burden. It clearly explains the central `action` enum values and implied params like mcp_id and tool_id. However, many parameters (limit, immediate, tier_slug, prompt_vars, cancel_reason, etc.) are not individually described, leaving some inference required.

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,' clearly defining the tool's scope as both a catalog and execution hub. It names the core actions (search, describe, invoke, install, etc.) and even covers the secondary prompt-library function, so an agent can immediately understand what the tool does and how it differs from a generic utility.

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 an explicit core flow: 'action=search discovers MCPs by intent → describe returns one MCP's full profile... → invoke RUNS that tool.' It also gives precise when-to-use guidance, such as 'Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use,' and contrasts list_tools, subscribe/cancel, and request_mcp. It even explains the credential and payment edge cases, telling the agent to retry after the user completes a connection or checkout.

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, readOnlyHint=false, and destructiveHint=false, so the safety profile is covered. The description adds the behavioral expectation that the conversation array should be included for reproduction, which is useful beyond the annotations. However, it does not disclose any side effects, auth requirements, or return 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 a single sentence that immediately states the purpose and then provides a specific, actionable instruction. Every word earns its place, 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?

For a tool with three parameters and no output schema, the description covers the essential purpose, the required message, and the recommended conversation parameter. It does not explain the context parameter, but this is a minor gap. Given the simplicity of the tool and the sibling context, the description is adequately 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?

Schema description coverage is 0%, so the description must compensate. It adds meaning for 'conversation' by calling it an 'array with recent messages for reproduction,' but it does not explain the 'context' parameter, which remains ambiguous. 'message' is self-evident from the tool purpose. The description partially compensates but leaves gaps.

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.' The verb 'report' is specific and the resource (bug/missing feature/feedback) is defined. It distinguishes itself from unrelated siblings like authenticate and marketplace, making its purpose 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 clear context on when to use the tool ('Report a bug, missing feature, or send feedback') and adds a specific usage instruction: 'Include the conversation array with recent messages for reproduction.' It does not explicitly mention alternatives or when not to use it, but the sibling context implies this is the dedicated feedback channel.

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, which cover the safety profile. The description adds the object of the query (current platform and adapter versions) but no additional behavioral context beyond what the 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?

The description is a single, front-loaded sentence that says exactly what is needed without any redundancy or filler. Every word adds value.

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 parameterless version-inspection tool, the description is fully sufficient. It clearly states what information is returned (current MCP platform and adapter versions) and requires no additional context about parameters or output schema, given 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?

With zero parameters, there is nothing for the description to explain; the baseline for 0 params is 4. The schema coverage is trivially 100%, so the description is not required to compensate for undocumented fields.

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 resource ('MCP platform and adapter versions'), making the tool's purpose clear. It distinguishes itself from sibling tools that handle auth, connections, marketplace, and bug reporting, which are unrelated to version introspection.

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 (whenever version information is needed), and there are no sibling alternatives to exclude. Though it doesn't explicitly state when-not-to-use, the context is clear enough for this simple version-query tool.

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 context by specifying exactly what data is returned (MCPs, connection status, accounts, catalog tool counts), which goes beyond the annotations. No contradictions are present, and the description does not need to repeat annotation-provided traits.

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 action ('Returns') and packs in all necessary details without any filler. Every word contributes to explaining the tool's output, making it maximally efficient with no redundancies.

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 tool with no parameters and a clear, self-contained output purpose, the description is fully sufficient. It explains what the tool returns without needing an output schema, and the annotations cover safety and idempotency. There are no missing pieces from an agent's perspective to decide to invoke and interpret results.

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, the schema is trivially complete (100% coverage). The baseline for no parameters is 4, and since the description does not need to elaborate on any inputs, this score is appropriate. The description focuses solely on output, which is the only relevant semantic aspect here.

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 the current toolkit state' and enumerates exactly what that state includes (installed MCPs, connection status, accounts, catalog tool counts). This is a specific verb+resource description that distinguishes it from siblings like authenticate or connect, which are clearly actions rather than informational queries.

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?

While there is no explicit 'use this when' or alternative mention, the description makes the tool's purpose self-evident as a status checker. The content aligns with the readOnly/idempotent hints, and the sibling names (authenticate, connect, report_bug) imply different actions, so an agent can reasonably infer when to use this tool versus others without additional guidance.

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