SEFAZ PR: Certidão Negativa de Débitos

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

Annotations already flag idempotent and non-destructive, so safety is covered. The description adds behavioral context by explaining the two modes (permanent via config, session via token) and the no-arg link retrieval. It does not detail session expiration or side effects, but is consistent with annotations and gives useful beyond-schema information.

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 long but every sentence serves a purpose, covering context, permanent token setup, session login, and argument handling. It is front-loaded with the tool's target audience, though the formatting could be slightly more compact.

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 an authentication tool with no output schema, the description gives enough context: how to authenticate (browser), token format (JWT), two usage modes, and the no-arg behavior. It does not mention response details or error cases, but these are not critical given the annotations and 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 schema has one undocumented optional string parameter `token`, but the description explains it fully: `token` should be a JWT pasted by the user, and calling with no args returns a login link. This completely compensates for the 0% schema description coverage.

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 indicates the tool handles authentication, explaining how to obtain and use access tokens for IDE agents. It distinguishes itself from siblings like connect or marketplace by focusing on login/token exchange, though the exact verb 'authenticate' is implied rather than explicitly stated.

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?

It provides clear usage guidance: use this tool for session-only login or to get a login link, and the 'best' alternative is to add a permanent token to the server config. It does not explicitly compare to sibling tools but offers a practical when-to-use versus when-to-use-config distinction.

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 valuable behavioral detail beyond that: it reports authenticated status, empty pending[], and provides connect_url when credentials are missing. This is sufficient context for a safe status-checking tool.

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, front-loaded with the core purpose, and every clause adds meaningful behavior. There is no redundant boilerplate or repetition of annotations.

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, read-only status tool with rich annotations, the description fully captures the relevant behavior: return values in both success and incomplete-credential scenarios. No output schema exists, but the description conveys the key return semantics well.

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 and 100% schema coverage, so the baseline is 4. The description correctly focuses on behavior rather than parameters, as there is nothing to document. No parameter-related gaps exist.

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 specific verb+resource: 'Returns connection status and URLs.' It also outlines conditional outcomes (authenticated:true vs pending[]), making the purpose clear. It doesn't explicitly differentiate from sibling 'authenticate', but the read-only status-check role is evident.

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 useful context by explaining what happens when providers are connected versus when credentials are missing, which implies when a user would call this tool. However, it does not explicitly state when to prefer this over siblings like 'authenticate' or mention any 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 description discloses important behavioral traits entirely beyond the annotations: invoke runs uninstalled MCPs one-off without bloating the tool list, returns connect or checkout/top-up links when credentials or payment are needed, and write actions require workspace owner/admin. This is rich behavioral context that annotations alone do not 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 long, but most sentences earn their place given the broad and complex functionality. It front-loads the core flow and then organizes the common actions, prompt library, and permission notes. It could be even tighter, but it is not padded or tautological.

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 high complexity, 23 optional parameters, open-world nature, and no output schema, the description provides a strong operational overview: core flows, auth/wallet side effects, ownership requirements, and the prompt library. It is still somewhat incomplete regarding return shapes, the full set of action-specific parameters, and edge-case behavior, but it is far above the minimum viable bar.

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 carries the full burden, and it does explain the central action parameter and many related fields (action=search/describe/invoke, mcp_id, tool_id, arguments, prompt_vars, etc.). However, several parameters are never mentioned (limit, immediate, tier_slug, prompt_targets, cancel_reason, report_context), so the mapping between prose behavior and the full 23-parameter schema is only partial.

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 the tool as the mcp.ai marketplace: an in-platform catalog of MCPs/tools and the execution path to run them. It explicitly names the core flow (search → describe → invoke) and the prompt-library sub-feature, which distinguishes it from the sibling tools.

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 one-off/occasional use, use install only to make an MCP permanent, list_tools shows what is currently callable, and subscribe/cancel/report/request have distinct purposes. It also spells out when NOT to use certain paths, like avoiding install unless persistence is needed.

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=false, idempotentHint=true, and destructiveHint=false. The description adds that the conversation array is for reproduction, implying data is sent for debugging. It does not contradict annotations, but it could be more transparent about the side effect of transmitting data externally. It adds some context beyond the annotations, but not extensively.

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 an additional imperative instruction. It is perfectly concise, front-loads the tool's purpose, and contains no redundant 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?

For a tool with three simple parameters and no output schema, the description adequately conveys the core function and a key requirement. However, it omits any detail about the required 'message' field, which is essential for the agent to use the tool correctly. A more complete description would briefly mention what message or context are for.

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 description explicitly references the 'conversation' parameter and explains its purpose ('with recent messages for reproduction'), which is valuable given 0% schema coverage. However, it does not mention the required 'message' parameter or the optional 'context' parameter, leaving room for ambiguity about 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 uses specific verbs 'Report' and 'send feedback' and clearly identifies the resource ('bug, missing feature, or feedback'). It also adds a distinctive usage hint about the conversation array, which goes beyond simply restating the tool name and differentiates it from unrelated siblings like 'authenticate' and '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 opening phrase gives clear context for when to use the tool, and the directive to 'Include the conversation array with recent messages for reproduction' is a practical usage guideline. However, it does not explicitly mention alternatives or any exclusions, so it stops short of a 5.

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 clear. The description adds context about being hosted by the platform, not requiring platform credentials, and involving per-query costs with prepaid credits. It also mentions LGPD compliance and data ownership. These are useful behavioral details beyond the annotations, though it doesn't discuss rate limits or exact response 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 paragraph of about 3-4 sentences, which is concise. It front-loads the purpose and then provides operational details. No wasted words, though it could be more structured (e.g., bullet points) for clarity, but overall it is 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?

Given the tool has no output schema and simple parameters, the description provides moderate context: it explains the data source, legal considerations, and payment model. It lacks explicit guidance on whether both CPF and CNPJ can be provided, what happens if none is provided, and what the response looks like. For a simple query tool, this 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?

Schema description coverage is 0%, meaning the description does not explain the parameters at all. While the parameter names 'cpf' and 'cnpj' are self-explanatory (Brazilian tax identifiers), the description does not clarify that they are optional (required: 0) or that one of them must be provided for a query. It also doesn't explain formats (e.g., with or without punctuation) or constraints. Since the description carries the burden and fails to compensate, this scores low.

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 that the tool consults a negative debt certificate from SEFAZ PR in an official source. It uses a specific verb ('consultar') and resource ('Certidão Negativa de Débitos'), which is clear. However, it could be more explicit about distinguishing from potential sibling tools (e.g., other certidão tools), but none are present in the sibling list, so it stands alone.

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 this is for consulting official Brazilian data and mentions it is not sensitive data, implying it is for legitimate purposes. It also notes payment requirements (prepaid credits). However, it does not explicitly state when to use this tool versus alternatives, nor when not to use it. Given the sibling list, no direct alternatives exist, but guidance on prerequisites (e.g., needing CPF or CNPJ) is implied but not explicit.

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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent already knows this is a safe, read-only operation. The description adds the specific scope ('MCP platform and adapter') but doesn't elaborate on output format or any potential constraints. With strong annotations, this is adequate.

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 front-loads the purpose without any superfluous words. It perfectly matches the tool's simplicity.

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, read-only tool with no output schema, the description is complete enough. It clearly states what the tool does, and the annotations cover safety. The only minor gap is not describing the output format, but that's acceptable 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?

The tool has 0 parameters, and schema coverage is 100% (trivially, since there are no properties). The description adds meaning by specifying what version info is shown (platform and adapter versions), which is useful 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's purpose: 'Show the current MCP platform and adapter versions.' It uses a specific verb ('show') and resource ('version'), and it distinguishes itself from siblings by being solely about version retrieval, unlike 'authenticate', 'connect', 'marketplace', 'report_bug', 'sefaz_pr_certidao_debitos_consultar', and 'toolkit_info' which serve 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 that the tool is for retrieving version information, which provides clear context for when to use it. It doesn't explicitly state when not to use it, but given the sibling tools, it's obvious this is for checking versions, not for performing actions like authentication or reporting bugs.

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 the tool's read-only nature implicitly by stating it 'returns' state, and annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds specific behavioral detail about the content (installed MCPs, connection status, accounts, catalog tool counts), which is useful 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 a single, front-loaded sentence that efficiently lists what the tool returns. No filler or repetition. Every clause adds information about the content of the response.

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 is simple with no parameters and no output schema. The description comprehensively covers what the tool returns: installed MCPs, connection status, connected accounts, and catalog tool counts. Given the simplicityches, this is 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?

With 0 parameters mice schema coverage is 100% (trivially), the description doesn't need to explain parameters. According to the rubric, 0 params = baseline 4. The description adds no parameter info but doesn't need to.

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 toolkit state, specifically enumerating installed MCPs, their connection status, associated accounts, and catalog tool count. This is specific and distinguishes it from siblings like show_version (version info) or marketplace (available MCPs).

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 its usage for checking current state but does not explicitly state when to use it versus alternatives. It provides clear context on what it returns (installed MCPs, status, accounts, catalog counts) without mentioning exclusions or alternative tools. This qualifies as clear context with no exclusions, rating a 4.

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