DETRAN SP: Autenticidade de Certidão

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

Annotations already cover idempotency and non-destructiveness, and the description adds behavior beyond those hints: permanent header-based login, session-only token-based login, and no-args link generation. It could say more about the response shape or what happens when a token is invalid, but the added behavior is useful enough for the simple job.

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 compact and front-loaded, covering setup, permanent config, session-only token usage, and no-args behavior in three sentences. Every sentence contributes, though the opening 'MCP.AI for IDE agents (Cursor, etc.)' is a bit indirect and could be shortened.

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 optional-parameter tool with no output schema, the description is complete enough: it explains how to log in, what values are needed, and the permanent vs session-only options. It could add a sentence on the expected return format after no-args or token calls, but no major invocation gap exists.

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?

Scanning schema provides only token as a string, and the schema description coverage is 0%, so the description carries the entire parameter burden. It clearly explains that token is a JWT pasted by the user, that it can be omitted, and that no args returns the link, making invocation semantics unambiguous.

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 action, 'log in', and names the target resource MCP.AI, so the agent can tell this is an authentication tool. It stops short of a full 5 because it does not explicitly distinguish itself from sibling tools like 'connect' and opens with MCP.AI for IDE agents rather than a direct statement of function.

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 guidance: use the server config header for permanent access, or call the tool with token for a session-only login, or call with no args to get the login link. It does not explicitly discuss sibling tools, but the config-vs-call and with-token-vs-no-token alternatives are strong and actionable.

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 a read-only, idempotent, non-destructive operation. The description adds significant behavioral detail by explaining the varied return payloads (authenticated:true and empty pending[] vs. connect_urls), which is not inferable from annotations alone. No contradictions.

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, front-loads the core purpose, and uses conditional logic to explain edge cases. Every word earns its place with no repetition or fluff.

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 (zero parameters, rich annotations, no output schema), the description fully covers the operational states and return values. It also implicitly guides the next step (authentication) when credentials are missing, making it complete for an agent.

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 baseline for parameter semantics is 4. The description cannot add parameter meaning, but it does not need to; the schema is empty and the description focuses on output behavior, which 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 tool's function: 'Returns connection status and URLs.' It further specifies the two distinct output conditions (all providers connected vs. missing credentials), which adds valuable context and distinguishes it from sibling tools like 'authenticate' by focusing on status rather than mutation.

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 conditional context: when credentials are missing, it returns a connect_url, implying the agent should follow up with authentication. However, it does not explicitly say 'use this when' or mention alternatives, so it falls short of full guidance but is still useful.

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?

With annotations already indicating read-only, idempotent, and non-destructive, the description adds useful context: no platform credentials needed, pay-per-query with prepaid credit, and data protection responsibilities under LGPD. This goes beyond the annotation baseline.

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 paragraph with several useful pieces of information. It is front-loaded with the primary purpose and stays reasonably concise, though the legal and payment details add length.

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 4 parameters and no output schema, but the description does not mention expected return values or clarify the relationship between optional CPF/CNPJ and required password/certificate code. It provides some context but leaves significant gaps for an agent to invoke 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?

Schema description coverage is 0%, and the description provides no explanation of parameters like login_cpf, login_cnpj, login_senha, or codigo_certidao. It does not compensate for the lack of schema descriptions, leaving parameter semantics entirely unclear.

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: checking certificate authenticity ('Autenticidade de Certidão') from an official source. It distinguishes itself from sibling tools (authenticate, connect, marketplace, etc.) by specifying the resource and 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?

Usage is implied: the tool is for verifying official Brazilian certificate authenticity. It clarifies that it uses public data and requires prepaid credit, but it does not explicitly state when to use this tool versus alternatives or mention 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?

Beyond the sparse annotations, the description discloses critical behaviors: invoke works even when the MCP is not installed, it runs one-off without bloating the tool list, returns connect links for auth and checkout links for payment, and that install/uninstall/subscribe/cancel require owner/admin. This greatly exceeds the annotation hints.

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 and information-dense. It front-loads the core purpose and action flow, then covers key distinctions (invoke vs install), billing/auth, and the prompt library. Every sentence adds value, though a slightly tighter structure could improve scannability.

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?

Despite no output schema and high complexity, the description covers purpose, invocation flow, authentication/billing implications, ownership restrictions, and the separate prompt library subsystem. It provides enough context to select and invoke the tool for the most common scenarios, leaving only minor edge cases undocumented.

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 23 parameters and 0% schema coverage, the description compensates substantially by explaining the core flow and naming parameters like action, query, mcp_id, tool_id, arguments, and prompt_slug/vars. However, many secondary parameters (limit, immediate, tier_slug, cancel_comment, etc.) are not directly explained, leaving gaps for the full parameter set.

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 this is 'the official mcp.ai marketplace' catalog and runtime, with a well-defined core flow: search → describe → invoke. It distinguishes itself from siblings by naming its distinct capabilities (MCP discovery, execution, one-off runs, and a prompt library) and by contrasting with alternatives like report_bug and request_mcp.

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 guidance on when to use each action: 'prefer invoke for a single/occasional use', 'use install only to make an MCP PERMANENT', and explains when to use subscribe/cancel, report_bug, request_mcp, and the prompt actions. It also notes that writes require workspace owner/admin, which helps the agent decide based on permissions.

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-destructive, idempotent behavior. The description adds the useful behavioral instruction to include the conversation array for reproduction. However, it does not disclose what happens after reporting or how the message is processed, leaving some ambiguity.

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 and front-loaded: the first sentence states purpose, the second gives a critical usage hint. Every sentence earns its place with no 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?

For a simple bug-reporting tool with three parameters and no output schema, the description gives enough general guidance. However, the required 'message' parameter is not explicitly mentioned, and 'context' is entirely undocumented, leaving gaps for an agent deciding how to populate the 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 should compensate. It only meaningfully explains 'conversation' ('recent messages for reproduction'), but does not explain the required 'message' parameter or the 'context' parameter. It also refers to 'conversation' as an array while the schema types it as a string, which could mislead.

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 a specific purpose: 'Report a bug, missing feature, or send feedback.' It names the verb and resource, and the function is clearly distinct from the sibling tools like authenticate or 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 provides clear context for when to use the tool: when reporting a bug, missing feature, or feedback. It does not explicitly exclude alternatives, but none of the sibling tools overlap with this purpose, so no exclusion is necessary.

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, covering the safety profile. The description adds that it returns version info for both platform and adapter, which is beyond what annotations provide. It does not disclose return format or latency, but given the tool's simplicity and annotation coverage, 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 sentence with no wasted words. It is front-loaded and directly states the action and target. It is appropriately concise for a simple utility tool.

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 no-parameter, no-output-schema tool, the description is complete. It explains what the tool does (shows versions) and the scope (platform and adapter). Given its simplicity, the agent has enough information to invoke 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 zero parameters, so per the rubric baseline is 4. The description correctly does not mention any parameters, and the schema coverage is 100% with an empty properties object. No further param explanation is 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 explicitly states 'Show the current MCP platform and adapter versions' with a specific verb ('Show') and resource ('MCP platform and adapter versions'). It clearly distinguishes itself from sibling tools by focusing on platform and adapter versions, which none of the siblings directly address.

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 does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives like toolkit_info. However, the purpose is straightforward and obvious for a version-info tool, so usage is implicitly clear. Minimal guidance is missing but not critical for this simple read-only 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=true, idempotentHint=true, and destructiveHint=false, so the safety profile is well covered. The description adds value by specifying what the state includes (installed MCPs, connection status, accounts, catalog tool counts), which goes beyond the annotations. 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 description is a single, well-structured sentence that front-loads the purpose and lists the key return elements. 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?

Given the tool has no parameters, no output schema, and strong annotations, the description is complete enough. It clearly states what the tool returns, which is the main information an agent needs. It could mention that it's a read-only operation, but the annotations already cover that.

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 doesn't need to explain parameter semantics. The schema coverage is 100% (vacuously), and the description fully explains what the tool returns, which is sufficient for a no-parameter tool.

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 elements: installed MCPs, connection status, connected accounts, and catalog tool counts. This is a specific verb+resource and distinguishes it from siblings 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 implies this is a read-only informational tool for checking toolkit state, which is clear from the context. It doesn't explicitly state when to use it vs alternatives, but given the sibling tools are action-oriented (authenticate, connect), the usage context is clear enough.

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