INMETRO: Cronotacógrafo (Detalhes)

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

Annotations (readOnlyHint=false, destructiveHint=false, idempotentHint=true) are supplemented by the description's explanation of side effects, such as permanent config changes vs session-only login. It clarifies that calling with no args provides a link, but it doesn't detail error conditions or rate limits. The description adds useful behavioral context beyond the truth values.

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 rambly, mixing setup advice ('Best: add it to this server's config') with usage instructions. While every sentence contributes value, the structure could be more front-loaded and to the point, potentially dividing usage from configuration to improve clarity.

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 without an output schema, the description covers the essentials: how to trigger both modes and what to expect (a link). It mentions the return value in passing ('get the link') and gives details on the server config alternative. It omits error handling but remains adequate for typical 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 schema's 'token' parameter has no description (0% schema coverage), so the description fully compensates by explaining that { token: '<jwt>' } is used after the user pastes a token, and that calling with no args retrieves a link. This clearly defines the parameter's purpose and expected format.

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 MCP.AI for IDE agents by logging in and obtaining an access token. It uses an action verb ('log in', 'authenticate') and specific resources, though it doesn't explicitly differentiate from sibling tools. The flow is understandable, but a direct statement of 'use this to authenticate' would be clearer.

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 instructions on how to use the tool: paste a token for session login, omit args to get a link, or add a config for permanent access. It implies when to use it (when authentication is needed) but does not explicitly mention alternatives or when not to use it. Context is present without exclusions.

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 annotations already declare read-only, idempotent, and non-destructive behavior, which the description aligns with. The description adds detail about the output structure without contradicting the annotations, so it meets the lower bar for adding behavioral 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 concise, consisting of two sentences that clearly explain the tool's function and output variations. It avoids unnecessary elaboration and is well-structured for an AI agent 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?

Even without an output schema, the description adequately explains the return values (authenticated, pending, connect_url) and the conditions under which they appear. This provides sufficient context for an agent to understand what to expect from the 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 no parameters, so schema coverage is 100%. The description correctly avoids mentioning any parameters, and there is no gap to fill, making this dimension fully satisfied.

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 specifies that the tool returns connection status and URLs, and it differentiates the output based on whether providers are connected or credentials are missing. This is specific and distinguishes it from sibling tools like 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 provides conditional behavior (when all providers are connected vs. when credentials are missing), giving clear expectations of what the tool returns. However, it does not explicitly state when to prefer this over alternatives, though the context implies it is for status checking rather than authentication.

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), the description discloses that the operation requires prepaid credits, has no platform credential requirement, and clarifies that the data is non-confidential and subject to LGPD. This adds useful behavioral context about cost, authentication, and data handling.

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 moderately concise but includes redundant legal and business phrases (e.g., repeated references to LGPD and official sources). It is a single paragraph with several sentences, which could be tightened. The structure is acceptable but not highly 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?

The description covers cost, data nature, and hosting, but it does not explain return values or error handling. Since there is no output schema, it would be helpful to mention what the query returns (e.g., certificate details). For a simple read-only query, it is adequate but not 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 input schema lists two required string parameters ('placa' and 'renavam') with no descriptions. The description does not mention or explain these parameters, leaving the agent with no information about their meaning or expected format. Coverage is zero and no compensation is provided.

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 for querying official INMETRO tachograph certificate details from official Brazilian sources. It specifies the resource (cronotacógrafo) and the action (consulta), distinguishing it from sibling tools like authentication or 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 indicates it is a paid query requiring prepaid credits and notes that no platform credentials are needed, but it does not explicitly state when to use this tool versus alternatives or provide exclusions. It implies usage for certificate lookups but lacks direct 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?

The description adds substantial behavioral context beyond the annotations: invoke runs tools one-off without installing or bloating the toolkit, credential/payment gaps surface as connect/checkout links, and writes (install/uninstall/subscribe/cancel and the hidden install behind invoke) require workspace owner/admin. No contradiction with readOnlyHint=false or destructiveHint=false.

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 front-loaded with a clear one-sentence definition and then organized around the core flow, auth/payment behavior, install vs invoke, and the prompt library. It is dense and run-on in places, but every sentence contributes necessary information for a tool with this many sub-actions.

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 complexity—14 actions, 23 parameters, no output schema, and no required params—the description covers the most important operational contexts: discovery, profiling, one-off invocation, persistence, permissions, billing/auth fallbacks, installed-state flags, and prompt publishing. It provides enough return semantics (profiles, links, callable tools) without requiring 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?

Schema description coverage is 0%, so the description must compensate. It explains the action enum values (search, describe, invoke, install, etc.) and the role of tool_id in selecting a tool, plus prompt-related fields like prompt_vars and prompt_slug. However, with 23 parameters, many fields (immediate, tier_slug, request_name, report_context, prompt_title, etc.) are never explicitly mapped, leaving significant 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 opens with a clear definition: "The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them." It then maps the core search → describe → invoke flow, which makes the tool's role unambiguous and distinguishes its catalog/run capabilities from 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?

Usage guidance is explicit and actionable: "prefer invoke for a single/occasional use" vs "use install only to make an MCP PERMANENT," and it explains when connect/checkout links require a user retry. It also partitions sub-actions such as list_tools for currently callable tools, report_bug for feedback, and request_mcp for new MCPs.

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 idempotentHint=true, readOnlyHint=false, and destructiveHint=false, but the description adds no behavioral context beyond that. It does not mention what happens after reporting (e.g., whether the bug is logged, if the user gets a confirmation, or if there are rate limits). Since annotations are present, the description could add value by describing the reporting outcome, but it does not. The description does not contradict annotations, but it provides minimal transparency.

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 very concise (two sentences) and front-loaded with the main purpose. It adds a second sentence about the conversation parameter, which is useful but could be more concise by integrating parameter guidance. Overall, it is efficient with minimal waste.

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 (3 params, no nested objects, no output schema), the description is relatively short but still leaves important gaps. The 'message' parameter is required but not described, and the tool is a reporting action with no indication of the outcome or any prerequisites. The description covers the 'conversation' parameter but misses 'message' and 'context', making it incomplete for an agent to know what to provide.

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. The description mentions 'conversation array' but not the 'context' or 'message' parameters. It adds partial meaning for the 'conversation' parameter (used for reproduction) but leaves 'message' and 'context' unexplained. This is better than nothing but incomplete.

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 specific verbs ('report', 'send') and identifies the resource (bug/missing feature/feedback). It is distinct from sibling tools like 'authenticate' or 'marketplace', which serve completely 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 implies when to use this tool (when encountering a bug, missing feature, or needing to provide feedback) but does not explicitly state when not to use it or mention any alternatives. There are no sibling tools that are similar, so exclusion is not critical, but the guidance is only implicit.

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 adds no behavioral context beyond that, but it does not contradict the annotations. It provides no extra details about return format or error behavior, though for a version tool this is minimal.

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, direct sentence with no fluff. It is perfectly concise and front-loaded with the essential verb and 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?

For a zero-parameter, no-output-schema tool, the description sufficiently conveys its purpose. It might have added a hint about what 'versions' includes, but given the simplicity and annotations, it 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?

There are zero parameters, so the description does not need to elaborate on parameter meanings. The schema coverage is trivially 100%, and with no params, the baseline is 4. The description adds no parameter info because none exists.

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 ('current MCP platform and adapter versions'), clearly distinguishing it from sibling tools like 'authenticate' or 'connect'. It unambiguously states 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?

No explicit guidance is given on when to use this tool versus alternatives like 'toolkit_info'. However, for a simple version check, the intended usage is implied and the lack of exclusions is not a significant gap.

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 annotations already declare readOnly and idempotent, so the description does not need to repeat side effects. The description accurately reflects the tool's behavior without omitting any observable 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 a single, concise sentence that conveys all necessary information without fluff. It is well-structured and directly states what the tool does.

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 no parameters and no output schema, the description fully covers what the tool returns. It lists all the major components of the toolkit state, making the scope 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 tool has no parameters, so there is no need for parameter documentation. The description correctly implies that no input is required, making this dimension trivially satisfied.

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 the current toolkit state, listing specific components: installed MCPs, their connection status, connected accounts, and catalog counts. This is a precise and unambiguous purpose.

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 the description does not explicitly mention when to use the tool, its purpose is self-evident and no special instructions are needed for a simple read-only state retrieval. Slight deduction for lacking explicit context like 'use this to check status'.

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