Prefeitura PB Mataraca: Certidão Negativa de Débitos

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

Beyond the annotations, the description discloses meaningful behavior: no args returns a login link, passing a token performs session-only authentication, and the config header option creates a permanent non-expiring connection. This adds valuable context about side effects and persistence that annotations alone do not convey.

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, using three sentences to cover purpose, permanent setup, and session-only flow. Every sentence adds essential information with no fluff 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 simple one-parameter schema, no output schema, and useful annotations, the description is complete enough for an agent to invoke the tool correctly in both modes. It explains how to obtain the token, how to persist it, and what happens with no arguments.

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 fully compensates by explaining the single 'token' parameter: it is a JWT obtained from the browser login, passed as { token: "<jwt>" }, and optionally omitted to get the link. This gives the agent complete operational understanding 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 states the tool's purpose: authenticating to MCP.AI for IDE agents by logging in via browser and obtaining an access token. It distinguishes itself by explaining the two auth modes (permanent config header vs session-only token) and is not a tautology of the title.

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: the 'Best' path for permanent setup and the alternative for session-only login, including how to call with or without a token. It does not explicitly discuss when not to use it or compare it to sibling tools like 'connect', so it stops just short of full alternative 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?

The description explicitly reveals what the tool returns in different states, adding value beyond the readOnlyHint and idempotentHint annotations. It does not contradict annotations; the read-only and idempotent behavior aligns with returning status information without side effects.

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 exactly two sentences, front-loaded with the primary purpose, and every clause adds meaningful detail about response conditions. There is no redundany or filler, making it highly 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 simplicity (0 params, no output schema) and the presence of safety annotations, the description is complete. It explains the output shape in both normal and missing-credential scenarios, which is sufficient for an agent to use the tool correctly and interpret results.

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 elaborate on parameter semantics. Per the rubric, a baseline of 4 is appropriate when there are no parameters, and the description adequately communicates the output without requiring parameter details.

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 distinguishes it from siblings like 'authenticate' or 'marketplace' by focusing on connection state. It even provides conditional details about the response, making the purpose unambiguous.

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 the tool (to check connection status) and explains the response scenarios (all connected vs missing credentials), giving clear context. However, it does not explicitly mention alternatives or when not to use it, so it falls 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?

Discloses side effects beyond annotations: invoke may return connect/checkout links, retry after user action; writes require workspace owner/admin; invoke performs an implicit one-off install. Annotations give readOnly=false, openWorld=true, etc., and the description adds operational details like permission requirements and retry semantics. 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 long but dense, covering many sub-actions and workflows. It is front-loaded with the primary purpose and flow, then elaborates. Some could be bulleted for readability, but every sentence adds value given the tool's complexity. Well-structured with logical progression.

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 23 params and no output schema, the description is remarkably comprehensive: it covers search, describe, invoke, install distinction, credential/payment handling, list_tools, billing, bug reporting, request_mcp, and the prompt library. It also mentions permission requirements. The agent gets enough context to correctly invoke actions and handle scenarios.

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%, so description carries the burden. It explains the meaning of the 'action' parameter thoroughly by describing each action in context, and references key params like mcp_id, tool_id, arguments, prompt_slug. However, not all 23 parameters are explicitly described; but the main workflow params are covered. This is good compensation for a complex 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 it's the official marketplace for discovering and running MCPs/tools, distinguishing it from siblings by describing its catalog and run capabilities. The verb 'marketplace' is vague, but the description specifies it as the platform for finding and executing tools, making purpose unambiguous.

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 provides a core flow (search → describe → invoke) and contrasts invoke vs install: 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT'. Also mentions list_tools for what's callable now, and distinguishes prompt library actions. Gives concrete when-to-use and when-not-to-us 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?

Beyond the annotations (readOnly, idempotent, non-destructive), the description discloses payment per consultation, no platform credentials, non-confidential data, and LGPD responsibility. This adds meaningful behavioral context that annotations do not cover.

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, front-loaded with purpose, and every sentence adds essential context (hosting, payment, data source, compliance). No wasteful 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 simple read-only query tool with no output schema, the description covers key aspects like payment and data sensitivity, but does not describe the expected result format or behavior on invalid input. It is adequate but not fully 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 input schema has no parameter descriptions and 0% coverage, so the description should compensate by explaining the parameters. It does not mention cpf or cnpj at all, although the names are self-explanatory. The lack of guidance on which parameter to use and whether one or both are required is a significant gap.

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 a consultation for a Negative Debt Certificate from the municipality of Mataraca, PB, using an official source. It specifies the verb 'consultar' and the resource, distinguishing it from generic sibling tools like authenticate 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 provides clear context for when to use the tool (for official Brazilian citizen-accessible data) and mentions payment requirements and lack of platform credentials. However, it does not explicitly state when not to use it or name alternatives, but siblings are unrelated, so the guidance is adequate.

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=false, destructiveHint=false, and idempotentHint=true, providing basic safety and idempotency information. The description adds context about including conversation data for reproduction, which is useful, but it does not elaborate on potential side effects or what happens after submission. Since annotations cover the core behavioral traits, the description's added value is moderate.

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 concise sentences: the first states the purpose, the second gives the key usage hint about the conversation array. No fluff or redundancy, and the most important information is front-loaded.

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 3 parameters and no output schema, the description is incomplete. It explains one parameter (conversation) but leaves the other two semantically undefined. It also does not indicate what kind of feedback is expected or how it will be used. Given the lack of schema descriptions, the description should compensate more fully.

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 compensate. It only mentions the 'conversation' parameter ('Include the conversation array'), while the required 'message' and the optional 'context' parameters are not explained at all. The description fails to clarify what 'message' (the actual bug report) or 'context' should contain, leaving room for misinterpretation.

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: 'Report a bug, missing feature, or send feedback.' This provides a specific verb and resource, and it naturally distinguishes itself from sibling tools like authenticate, connect, or show_version, 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 usage by stating the action ('Report a bug...') and adds a specific instruction ('Include the conversation array with recent messages for reproduction.'). However, it does not explicitly mention when not to use it or compare it to alternatives, leaving the use case somewhat implicit.

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 agent knows this is a safe, non-mutating operation. The description adds no extra behavioral context (e.g., whether it requires authentication or outputs a specific format), but given the zero-risk nature and no contradiction, a 3 is appropriate as it adds minimal value beyond 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 sentence with no filler. It front-loads the action ('Show') and specifies the exact subjects ('MCP platform and adapter versions'). Perfectly concise and structured.

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 informational tool with no output schema, the description is complete. There is no complexity to address, and annotations cover safety. No additional details are needed.

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 schema description coverage is 100%. The description does not need to explain parameters because there are none. This is a baseline 4 for no parameters, as the description accurately reflects the tool's scope.

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: 'Show the current MCP platform and adapter versions.' This is a specific verb-resource pairing that distinguishes it from its siblings (e.g., authenticate, connect, toolkit_info) by focusing on version display. It does not explicitly name alternatives but the purpose is unambiguous.

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 in contexts where version information is needed, but it does not explicitly state when to use it versus other informational tools like toolkit_info. It lacks explicit when-to-use/when-not-to-use guidance, but the use case is straightforward and obvious.

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, destructiveHint=false, and idempotentHint=true, so the safety profile is set. The description adds value by detailing exactly what state is returned (installed MCPs, connection status, accounts, catalog tool counts), which goes beyond the annotations and clarifies the read nature.

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 starts with the verb 'Returns' and immediately states the resource. Every detail is meaningful and there is zero fluff, earning a perfect score.

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 simple read-only tool with no parameters, no output schema, and clear annotations. The description fully covers what the tool does and what information it exposes, leaving no critical gaps. It is completely adequate for the tool's complexity.

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 schema coverage is 100%. Per guidelines, a zero-parameter tool receives a baseline of 4. The description correctly avoids unnecessary parameter explanations and focuses on the output.

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 the tool's function: 'Returns the current toolkit state' and enumerates the specific items returned (installed MCPs, connection status, accounts, catalog tool counts). This clearly distinguishes it from siblings like authenticate or connect, which are action-oriented.

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 implies usage for checking toolkit status, but does not explicitly state when to use it versus alternatives, nor does it mention exclusions. However, given the niche purpose, the context is sufficiently clear for an agent to select it over the action-oriented siblings.

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