Prefeitura RJ Duque de Caxias: Certidão Negativa de Débitos

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

Annotations already declare idempotentHint=true and destructiveHint=false, and the description doesn't contradict these. The description adds useful context (browser flow, token expiration semantics for session vs permanent). However, it does not clarify potential side effects like initiating a browser session or whether calling with token validates it immediately. The behavioral transparency is adequate but not exhaustive.

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 relatively compact but packs a lot of information. It front-loads the most important instruction (browser login). However, it could be slightly more structured: the sentence about 'Best: add it to config' is somewhat tangential to the tool's direct use. Overall, it is concise without padding.

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 (multi-step authentication flow) and lack of output schema, the description covers the key steps and alternatives. It explains the two usage modes, but lacks details on error handling or what happens on invalid token. For a tool with no output schema, this is reasonably 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 schema has 0% description coverage for the 'token' parameter, so the description must compensate. It mentions token is a JWT pasted by the user, and for session-only login. However, it does not specify the token format beyond `<jwt>` or any requirements (length, validity). The description covers the parameter's purpose but not its constraints or behavior when invalid.

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 identifies the tool as an authentication mechanism for MCP.AI, explaining the two login options (browser-based token generation and token paste). It distinguishes the use case (permanent config vs session-only) and is specific about the 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 explicit instructions on when to use the tool: to obtain a login link or paste a token. It contrasts with permanent configuration via header, which is a clear alternative. However, it does not explicitly say when not to use it versus other tools like connect or marketplace, but the context is implied from the authentication-specific purpose.

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 behavioral safety is covered. The description adds details about response states (authenticated:true, empty pending[], connect_url). It doesn't describe any other behaviors, but given annotations handle safety, this is acceptable. 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?

Two sentences, front-loaded with the main purpose. Each sentence adds value: first states primary output, second explains conditional states. No wasted words, appropriately concise 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 tool has zero parameters, no output schema, and annotations providing safety info, the description explains the two likely response scenarios (all connected vs. missing credentials). Enough for an agent to understand what to expect. Could mention pending[] details more, but for a status tool, this is sufficient.

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?

No parameters are present, schema coverage is 100% with zero parameters, so there is nothing to add. Baseline for zero params is 4, and the description accurately reflects this by not mentioning any parameters. It adds meaning by describing the response states, which is helpful.

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, distinguishing it from siblings like authenticate and marketplace. It specifies what the tool does (return status/URLs) and differentiates it from other tools by focusing on connection status, not authentication actions.

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: when you need to check connection status or retrieve URLs, use this tool. However, it doesn't explicitly contrast with alternatives like authenticate, which might be relevant for connecting. It provides context on what responses look like in different scenarios, but no explicit when-not to use.

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 several important behavioral traits beyond annotations: invoke runs tools one-off without adding them to the toolkit, credential needs return a connect link, empty wallets return a checkout/top-up link, and writes require workspace owner/admin. This goes well beyond the minimal annotations and gives the agent realistic expectations about side effects and prerequisites.

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 densely informative, with no filler. It front-loads the core marketplace purpose and workflow before covering edge behaviors and the prompt library. A clearer structure (e.g., bullets or action-group headings) would improve scannability given the 14 action enum values, but every sentence adds useful content.

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 parameters, 14 actions, billing, auth, and prompt-library features) and the absence of an output schema, the description is notably complete. It explains the search/describe/invoke flow, install vs. one-off execution, billing and auth handling, workspace-owner restrictions, and the prompt-related return values. It gives the agent enough context to select and invoke the correct sub-action.

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 carry the parameter-semantics burden. It successfully explains the central action values (search, describe, invoke, install, subscribe/cancel, prompt actions) and key parameters like tool_id, arguments, and prompt_vars. However, several params such as immediate, tier_slug, prompt_category, and report_context remain undocumented, so compensation is strong but not complete.

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 official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them," which is a specific action-focused statement. It further distinguishes its role by explaining the core search → describe → invoke workflow and its prompt-library feature, making its purpose unmistakable relative to 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 usage guidance: "prefer invoke for a single/occasional use" vs. "Use install only to make an MCP PERMANENT," and it names when to use report_bug, request_mcp, and list_tools. It also explains when invoke is appropriate even when the MCP is not installed, providing clear when-to and when-not-to 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=true, idempotentHint=true, destructiveHint=false. The description adds valuable behavior: it costs money per query, the data is not confidential, and the client is data controller per LGPD. This goes beyond annotations and informs the agent of pricing and legal responsibilities.

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, moderately dense paragraph. It front-loads the main purpose and covers essential context (payment, hosting, legal) without unnecessary fluff. It is well-structured and 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?

For a simple tool with two optional parameters and no output schema, the description covers purpose, payment, and legal context. However, it omits key usage details: that at least one identifier (CPF or CNPJ) should be provided, and what the output looks like. This gap makes the description incomplete for an agent to use correctly without additional knowledge.

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% (no descriptions for 'cpf' or 'cnpj'). The description mentions no parameters at all. It does not explain that the tool expects either a CPF or CNPJ identifier. The description fails to compensate for the missing schema info, leaving the agent without guidance on how to fill the input.

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 it's for 'Certidão Negativa de Débitos' (negative debt certificate) consultation from an official source. The verb 'consultar' and resource are clear, and it does not overlap with generic sibling tools like authenticate or report_bug.

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 notes it's a paid, pre-paid consultation and hosted on the platform, which implies usage context. However, it doesn't explicitly state when to use it (e.g., 'when you need a CND for Duque de Caxias') or mention alternatives. Since there are no similar siblings, this lack of differentiation is acceptable, but explicit usage guidance would be stronger.

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 this is not read-only and not destructive, but the description does not disclose the actual side effects, such as creating a ticket or sending a report. It only mentions including conversation data for reproduction, and the idempotentHint=true seems questionable for a tool that submits user-reported issues.

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: the purpose appears in the first sentence, and the second sentence adds a relevant reproduction hint. There is no filler or repetition of structured fields.

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 side-effecting tool with no output schema, the description leaves important gaps: no indication of what happens after submission, no authentication or rate-limit context, and no guidance on message or context content. The conversation tip helps, but the overall definition is not self-sufficient for an agent to confidently invoke it.

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% across three parameters, so the description must compensate, but it only addresses the conversation parameter. It does not explain the required message field, the optional context field, or how the conversation should be serialized—especially since the schema types conversation as a string, not an array.

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 action and scope: 'Report a bug, missing feature, or send feedback.' This distinguishes it from sibling tools like authenticate, marketplace, and show_version, though it could be more explicit about the exact destination or resulting 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 intended use is implied by the first sentence, but there is no explicit guidance on when to use this tool versus alternatives or when not to use it. The instruction to 'Include the conversation array' is a how-to detail rather than a selection guideline.

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, covering safety. The description adds that it shows both platform and adapter versions, but provides no further behavioral details (e.g., output format, error conditions). No contradiction found.

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 that front-loads the verb and object. It has no filler, repetition, or unnecessary words, making it maximally concise.

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 extremely simple: no parameters, no output schema, no side effects. The description fully explains what it does in one sentence, providing complete context for an agent to invoke it successfully.

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 schema coverage is trivially 100%. The description doesn't need to explain parameters, and the baseline for 0 params is 4. No additional parameter context is needed or omitted.

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 the verb 'Show' and specifies the resource exactly: 'current MCP platform and adapter versions.' It clearly distinguishes the tool from siblings like toolkit_info and report_bug, which likely cover other functionality.

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 no explicit guidance on when to use this tool vs alternatives. There is no mention of checking versions before troubleshooting or any exclusions. With sibling toolkit_info possibly overlapping, the agent has no stated basis for choosing this 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 read-only and safe behavior is already declared by annotations (readOnlyHint, idempotentHint, destructiveHint false). The description adds useful context about the exact informational content returned, though it does not mention error behavior or data freshness. 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?

A single, front-loaded sentence conveys the tool's purpose and return contents without redundancy. Every word earns its place.

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, has no parameters or output schema, and the description fully specifies what is returned. No additional context seems necessary for an agent to invoke and interpret this tool 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 the description does not need to explain parameter meanings. Per the rubric, a no-parameter tool receives a baseline of 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 uses a specific verb ('Returns') and identifies the exact resource ('current toolkit state'), enumerating its contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly differentiates it from sibling tools like authenticate, connect, and show_version.

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 use for inspecting toolkit state, but it does not explicitly say when to use this tool versus alternatives such as show_version. There is no when-not-to-use guidance or naming of alternative tools.

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