GIT Cidadão (PR): Multas

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

Beyond the annotations, the description discloses that config-based auth is permanent and non-expiring, while pasted tokens are session-only, and that no-args returns a login link. This adds meaningful behavioral context without contradicting the idempotentHint or destructiveHint 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 three sentences, front-loaded with the target audience and core action, and every sentence adds a distinct piece of guidance. It is compact yet complete.

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 single-optional-parameter auth tool with no output schema, the description covers the login flow, token handling, persistence options, and invocation patterns. No critical context appears missing.

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 the optional 'token' parameter: it should contain the JWT for session-only login, and omitting it triggers link generation. This is more useful than a bare schema property.

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: logging into MCP.AI for IDE agents by browser login and access token. It is specific about the authentication flow, but it does not explicitly distinguish this from sibling tools like 'connect', so it falls short of full sibling 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 description provides explicit usage modes: permanent config via Authorization header, session-only login by pasting a JWT, and no-args to retrieve the login link. It also indicates the recommended approach ('Best') and when to use each variant.

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=true and idempotentHint=true, so the description does not need to cover those. It adds valuable context about the response format: when all providers are connected, it returns authenticated:true and empty pending[]; when credentials are missing, it returns connect_url and per-install URLs. This goes beyond the annotation coverage and clarifies the tool's 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 exceptionally concise: two sentences that directly state the main output and the two possible scenarios. It front-loads the primary purpose and avoids any unnecessary words 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?

Given the tool's simplicity (no parameters, no output schema), the description is complete. It covers the primary return value (connection status and URLs) and explains the two main states (all connected vs. missing credentials). No additional information is needed for an agent to use this tool effectively.

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 cannot add parameter-specific meaning. The schema is trivially complete (100% coverage with no properties). With 0 params, the baseline is 4, and the description correctly avoids inventing 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: it returns connection status and URLs. It specifies the resource (connection status) and the verb (returns), and distinguishes itself from siblings like authenticate by focusing on status rather than the authentication action.

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 context for when the tool is useful (checking connection status and retrieving URLs when credentials are missing), but it does not explicitly compare with alternatives or state when not to use it. It implies usage but lacks explicit exclusions or alternative recommendations.

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 cover readOnlyHint, idempotentHint, and destructiveHint. The description adds context about no sensitive data and LGPD compliance, but omits behavioral details like what happens on invalid credentials or whether the prepaid credit can be exhausted.

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 packs essential context into a few dense sentences, but the LGPD legal caveat adds length and may be less critical for an AI agent being asked to invoke the tool. It remains reasonably compact despite this.

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 read-only query tool with provided annotations and schema, the description covers source authenticity and legal aspects, but falls short on specifics like pagination, response format, or rate limits. It handles core—but not complete—context for this 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?

Schema coverage is 0%, with four required parameters—'placa', 'renavam', 'pkcs12_cert', and 'pkcs12_pass'—and the description gives no parameter descriptions beyond their names. Given the low coverage, the description fails to explain the expected data formats for the certificate path and password, or what 'placa' (license plate) and 'renavam' represent.

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 gives a specific verb+resource combination ('Multas, consulta em fonte oficial') clarifying this is a ticket/fine consultation tool accessing official Brazilian data. It adds scope by noting official government source and LGPD data controller context, though it doesn't explicitly reference sibling tools for distinction.

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 conveys usage context with payment-per-consultation prepaid credit and official source access, which implies appropriate quick-consultation scenarios. However, it never explicitly states when to use this over alternatives or mentions the sibling tools in its connected ecosystem.

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?

Goes far beyond the minimal annotations (readOnlyHint=false, openWorldHint=true, destructiveHint=false) by disclosing the one-off invoke behavior that doesn't bloat the toolkit, the connect-link and checkout/top-up retry flows, the admin requirement for writes, and the 'ran without installing' execution model. Nothing contradicts the annotations — the write operations align with readOnlyHint=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 ~230-word body packs dense, valuable information with almost no wasted sentences, but it's delivered as one undifferentiated wall of text. Sections covering the core flow, auth/payment handling, install-vs-invoke, admin rules, and the prompt library could be segmented with bullets or headers for scannability. Content earns its place; structure does not.

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?

Impressive coverage for a 14-action, 23-param tool with no output schema: the flow, one-off semantics, credential/payment handling, admin constraints, and sibling relationships are all described. Minor gaps remain — the 'resume' action is never explained, prompt-library mechanics (variable filling, share links) are only lightly sketched, and cancel_reason semantics are absent — but these are small relative to the overall thoroughness.

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 but only partially does. It thoroughly explains the action enum (the central parameter) and implies mcp_id/tool_id usage through the describe→invoke flow, yet leaves the prompt_* params (prompt_vars, prompt_targets, prompt_category), cancel_reason/comment, arguments JSON format, message, and request_details semantically undocumented. The core actions are covered; the periphery params are not.

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 "The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them," with a specific verb+resource identity. It enumerates all 14 sub-actions (search→describe→invoke flow, install, subscribe, prompt library ops) and distinguishes it from siblings by covering the full MCP lifecycle, whereas siblings like authenticate/connect/toolkit_info handle narrower concerns.

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?

Provides explicit when-to-use guidance: "use install only to make an MCP PERMANENT in the active toolkit... prefer invoke for a single/occasional use," and names alternatives (report_bug, request_mcp when nothing fits, list_tools for current callables). The search→describe→invoke workflow is spelled out with clear branching on auth (connect link) and payment (checkout/top-up link) states.

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 non-read-only, non-destructive behavior. The description adds value by specifying that the 'conversation' field should be included for reproduction, which is useful behavioral context beyond the annotations. It 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?

Two short sentences, front-loaded with the purpose and a direct instruction. No unnecessary words; every phrase 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?

Given the simple parameter structure and lack of output schema, the description covers the essential points: what to do and what to include. It could mention response handling, but that's not needed here. A score of 4 reflects good completeness without being excessive.

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, the description carries the burden of explaining parameters. It explains the purpose of the 'conversation' parameter ('for reproduction') but does not clarify 'message' or 'context'. It adds some meaning but only for one of the three parameters, so a score of 3 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 action ('Report a bug, missing feature, or send feedback') with a specific verb and resource. It is easy to understand what the tool does, though it does not explicitly differentiate from sibling tools, which are largely unrelated.

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 by saying 'Include the conversation array with recent messages for reproduction,' which hints at how to use the tool, but it does not explicitly state when to use this tool over alternatives or provide exclusion criteria. This fits the 'implied usage' category.

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, fully covering the safety profile. The description adds minimal extra behavioral context beyond stating what it displays; it doesn't provide additional insights like side effects or prerequisites, but for a zero-parameter read tool, this is sufficient.

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 directly conveys the tool's function with no wasted words or repetition. It is well-structured and front-loaded with the action.

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 zero-parameter tool with no output schema, the description fully explains what the tool returns (platform and adapter versions). No additional details are necessary, making the description complete for its 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, so the parameter semantics baseline is 4. The description doesn't need to add parameter information, and the schema confirms no parameters exist. The description correctly focuses on the tool's action 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 the tool's purpose: showing current MCP platform and adapter versions. The verb 'show' is specific, and the resource is well-defined. It distinguishes from siblings by focusing on version information, though not explicitly contrasting with toolkit_info.

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 a straightforward use case for checking versions. It doesn't explicitly mention when to use this tool over alternatives like toolkit_info, but given its simplicity and the context of siblings, the guidance is adequate for a version-checking 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?

The description 'Returns the current toolkit state' clearly indicates a read-only, idempotent operation, which aligns perfectly with the readOnlyHint and idempotentHint annotations. No contradictions. It also clarifies what state is returned, making behavior transparent.

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?

Single, well-structured sentence that is front-loaded with 'Returns the current toolkit state' and then enumerates the details. No fluff, every part 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 simple info tool with no parameters and no output schema, the description is sufficiently complete. It covers the main content of the return value. However, it doesn't specify how the information is structured (e.g., nested objects), but that might be self-evident from the tool name and sibling tools. Given the simplicity, it's near 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?

Tool has zero parameters, so per calibration baseline is 4. The description adds context by explaining what the tool returns, which is more than the empty schema provides but not needed for parameters. Thus, a solid 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 explicitly states that the tool returns the current toolkit state and lists the specific components (installed MCPs, connection status, accounts, and catalog tool counts). This leaves no ambiguity about the tool's purpose, which for a read-only info tool is exactly what is needed.

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 for checking toolkit state but does not explicitly state when to use it (e.g., before connecting). However, given the function name and zero parameters, the context is clear enough. It could benefit from a note about typical usage scenarios.

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