Polícia Rodoviária Federal: Débitos

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

Annotations only indicate idempotent/non-destructive/non-read-only; the description adds useful behavioral context: browser login requirement, permanent non-expiring vs session-only access, and token-based invocation. It does not contradict annotations and explains the underlying auth mechanism well.

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 dense but front-loaded with the core action ('log in in the browser, copy the access token'). Each sentence adds distinct value, though the final sentence is slightly run-on and could be clearer with tighter formatting.

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 one-parameter authentication tool with no output schema, the description covers the essential flow: browser login, token capture, permanent vs session-only options, and how to invoke. It could mention what exact response to expect, but the link-generation behavior is stated sufficiently.

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%, but the description compensates fully: it explains that the single optional 'token' parameter is a JWT, shows the exact call shape ({ token: "<jwt>" }), and clarifies that calling with no args returns the login link. This goes well beyond the bare 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 defines an authentication flow: log in via browser, retrieve an access token, and either configure it permanently or pass it for a session. It uses concrete verbs and describes the auth resource, though it does not explicitly distinguish itself from sibling tools like '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 gives explicit invocation guidance: add the token to server config for a permanent connection, or paste it for session-only login, with no args to get the link. It does not explicitly state when to use an alternative sibling tool, but it clearly covers the tool's own modes.

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, destructiveHint=false, so the description adds value by explaining what the response contains (fields like authenticated, pending, connect_url) and differentiates between two states. There is 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?

Two sentences, zero filler. The description is front-loaded with 'Returns connection status and URLs' and then clarifies states. 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?

Given no parameters, no output schema, and strong annotations, the description fully captures the tool's behavior. It explains the two possible outcomes (connected or missing credentials) and what each returns, which is enough for an agent to use it correctly.

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 0 parameters, and schema description coverage is 100% (since no properties). The description adds meaning by explaining the return values and state semantics, which is helpful even without 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 returns connection status and URLs, and describes the difference between connected state (authenticated:true, empty pending[]) and missing credentials (connect_url and per-install URLs). It distinguishes from siblings like authenticate which likely initiates connection, though it doesn't explicitly name it.

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: to check connection status before proceeding. It contrasts states when credentials are missing versus connected. It doesn't explicitly name alternatives (e.g., authenticate), but the semantic is clear for an agent deciding whether to check or initiate.

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 only say readOnlyHint=false, openWorldHint=true, idempotentHint=false, destructiveHint=false; the description adds substantial behavioral context: invoke runs one-off without installing, returns connect/checkout links on auth/payment failures, and writes require workspace owner/admin. It also discloses installed_in_toolkit vs installed_in_workspace flags. 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 long but well-structured: purpose first, then 'Core flow', 'KEY', install-vs-invoke guidance, permissions, and prompt library. It is dense and front-loaded, though it could be slightly more scannable with bullet points.

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 14-action, 23-parameter tool with no output schema, the description covers the main workflows, auth requirements, billing edge cases, and the prompt library. It omits the 'resume' action and some parameter details, but is complete enough for an agent to select and invoke correctly.

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 compensates by explaining the central action enum and core parameters (mcp_id, tool_id, arguments via 'params', prompt_slug/prompt_vars via the prompt library flow). However, it leaves several fields undocumented (limit, query, immediate, conversation, cancel_comment, report_context, request_details, prompt_title/description/category/targets), so it doesn't fully cover the 23-parameter surface.

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 'official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them' and enumerates specific actions (search, describe, invoke, install, list_tools, prompt-library actions). It clearly distinguishes this meta-tool from siblings by framing it as the catalog/execution layer rather than a domain-specific 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?

Explicitly prescribes a core flow (search → describe → invoke) and gives when-to-use guidance: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT'; also distinguishes list_tools ('what is callable right now') and request_mcp ('when nothing fits'). This is strong alternative-selection 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 already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds useful behavioral context: payment via prepaid credit, official source, non-confidential nature, and LGPD responsibilities. It goes beyond annotations without contradicting 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 a single compact paragraph, front-loaded with the core purpose ('PRF: Débitos, consulta em fonte oficial'). It covers purpose, hosting, payment, data source, and legal notes without excessive verbosity. However, it could be slightly more structured with explicit parameter guidance.

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 4 parameters, no parameter descriptions, and no output schema, the description is incomplete. It does not explain expected inputs (e.g., plate format, renavam numeric), what the query returns (e.g., list of fines, amounts, payment status), or any error conditions. The legal and payment context is useful but does not compensate for missing functional details.

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 tool description does not explain any of the parameters (ait, placa, renavam, ignora_boleto). Even required fields like placa and renavam are only implied by the domain (PRF debts), not explicitly described. Optional parameters like 'ait' and 'ignora_boleto' are completely unexplained, leaving the agent to guess their meaning.

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 queries debts ('Débitos') from the Polícia Rodoviária Federal (PRF) official source. This is specific about the resource (vehicle debts) and the action (query). It distinguishes from siblings 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 provides clear context: it is a paid per-query service hosted by the platform, requiring no platform credentials. It implies usage when checking PRF debts, though it does not explicitly mention alternatives or when not to use it. The mention of LGPD and data controller status adds situational 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=true, idempotentHint=true, and destructiveHint=false, which fully cover the safety profile. The description adds minimal extra behavioral context (e.g., that it shows 'current' versions), but does not describe return format or other nuances. It does not contradict the annotations, so a middle score is appropriate.

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 conveys the essential information without any waste. It is perfectly concise and well-structured for a tool with no parameters.

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 parameters, no output schema, clear annotations), the description is fully complete. It tells the agent exactly what the tool does, and the annotations cover behavioral safety. There are no missing pieces that would hinder correct invocation.

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, and the schema coverage is trivially 100%. Per rubric, 0 parameters warrants a baseline of 4. The description does not need to explain parameters; it simply states the tool's purpose, which is sufficient.

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 clear verb ('Show') and specifies the resource ('current MCP platform and adapter versions'), making the tool's purpose unambiguous. It is specific enough to distinguish it from sibling tools like authenticate or connect, which have entirely different functions.

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 the tool is used when version information is needed, but it does not explicitly state when to use it versus alternatives or provide any exclusion criteria. Since the tool is trivial, the context is clear enough, but it lacks explicit guidance on when or when not to use it.

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 valuable transparency by spelling out what state is returned: installed MCPs, connection status, accounts, and catalog tool counts. It does not describe return formatting or potential staleness, but it does not contradict 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 well-structured sentence. It front-loads the verb and resource, then lists concrete details. Every clause earns its place with no filler 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?

This is a low-complexity, stateless info tool with no parameters and strong annotations. The description fully specifies the returned information categories, so the tool is adequately documented even without 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?

The input schema has zero parameters, so the baseline is 4. The description has no parameter details to provide, and no missing parameter information needs compensation since the tool takes no arguments.

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?

Description opens with the specific verb 'Returns' and names the resource: 'the current toolkit state'. It enumerates the exact content (installed MCPs, connection status, connected accounts, catalog tool counts), making it clearly distinct from siblings like show_version 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 clearly indicates when to invoke the tool: whenever an agent needs an overview of installed MCPs, their status, accounts, or exposed tool counts. It does not explicitly contrast with sibling tools, but the detailed content makes the use context obvious and no exclusions are needed.

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