Prefeitura RN Touros: Certidão Negativa de Débitos

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

The description discloses the return behavior (no args gives a link) and the side effects (permanent vs session login). It complements the annotations (idempotent, non-destructive) by explaining the practical implications. It doesn't explicitly mention failure cases (e.g., invalid token), but this is not critical for usage.

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 despite covering multiple scenarios. It uses clear separators (e.g., 'Best:', 'Or') to structure the instructions, making it easy to follow without unnecessary verbosity. Slightly longer than minimal, but every sentence 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?

The description provides sufficient context for both usage patterns, including outcomes and configuration options. It does not describe the exact output format (e.g., JSON structure), but since no output schema is defined, this is acceptable. It fully addresses the tool's purpose and parameter behavior.

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 only parameter 'token' is fully explained: it is the access token to be used for authentication. The description specifies that providing it completes the login, while omitting it returns a link. This adds meaning beyond the schema's bare type definition.

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: to authenticate a user by providing a login link and accepting an access token. It distinguishes itself by explaining the two modes (permanent config vs. session-only) and the args behavior, which is more specific than sibling tools like 'connect' 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 explicitly explains when and how to use the tool: call with no args to get a login link, or with a token to authenticate. It also clarifies the difference between permanent and session-only authentication, giving clear instructions for both scenarios.

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 non-destructive. The description adds clarity about the response structure (authenticated, pending, connect_url) and the behavior when credentials are missing. This adds value beyond annotations, though it doesn't detail error cases or side effects (which are likely none given read-only).

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, two sentences, and directly relevant. It front-loads the primary purpose and then gives conditional details. 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's simplicity (no parameters, no output schema), the description covers the essential behavioral aspects. It explains the state-based output and what URLs are returned. Could be slightly more explicit about error conditions, but overall complete for practical use.

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?

This tool has zero parameters, so the description does not need to compensate for schema gaps. The description fully explains the output and the conditions under which different output appears, which is more relevant than parameter semantics.

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 returns connection status and URLs, with specific details about the response when all providers are connected versus when credentials are missing. It distinguishes from siblings like 'authenticate' (which likely initiates the connection) by focusing on status retrieval.

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 for checking connection status, but it does not explicitly state when to use it versus alternatives. However, the context of returning status and URLs is clear, and given the sibling tools, it is evident that this is for checking rather than initiating authentication.

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, it discloses write-permission requirements ('Writes ... require workspace owner/admin'), one-off invoke behavior that avoids installing or bloating the toolkit, and the connect/checkout link-retry behavior. The description is rich in behavioral context and does not contradict 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 dense and front-loaded with the core flow, key distinction between invoke and install, and permission notes. It is a single long paragraph that could benefit from bullets or sections, but almost every sentence carries meaningful information.

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—14 actions, 23 parameters, no output schema—the description covers the main decision paths well: search/describe/invoke, install vs one-off use, billing, authentication failures, permissions, and the prompt library. It omits 'resume' and some return-value details, but the essential operational behavior is present.

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 prose does substantial compensating work: it explains the action enum, the mcp_id/tool_id/arguments relationship via describe→invoke, and the prompt_* parameters via the prompt-library section. However, several parameters like limit, immediate, resume specifics, and cancel_reason details are left mostly to inference, so it is not exhaustive for all 23 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 it is 'the official mcp.ai marketplace — in-platform catalog of every MCP/tool, and the way to run them,' which is a concrete resource plus its core actions. It differentiates itself from sibling connection/auth tools by outlining the search → describe → invoke flow and the prompt library.

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 gives explicit decision rules: 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT.' It also contrasts list_tools with search/describe and explains retry flows for missing credentials or empty wallet, so the agent knows when to use which sub-action.

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?

Adds valuable context beyond annotations: mentions hosting, no platform credentials, pay-per-query, and data privacy (LGPD). These are not in the schema or annotations徒 independently useful for the agent's decision-making. No contradictions with the readOnly hint.

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 with the core purpose, followed by practical details. Each sentence adds meaningful information without fluff. Slightly verbose but still clear and easy to parse.

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 query tool with read-only, idempotent annotations and no output schema, the description covers all essential aspects: purpose, official source, payment mechanism, and data privacy. No additional information is needed for correct usage.

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?

Input schema has two string fields (cpf, cnpj) with no descriptions taskra. The tool name and description make it obvious these are Brazilian taxpayer identifiers for querying the certificate, so the description compensates adequately despite 0% schema 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 states the tool queries a Negative Debt Certificate (Certidão Negativa de Débitos) from the Prefeitura RN Touros, distinguishing it from the generic sibling tools (authenticate, connect, etc.). The verb 'consulta' plus specific resource makes 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 implicitly indicates this tool is for querying a specific certificate, and the payment/prepaid credit hint sets expectations. It doesn't explicitly contrast with alternatives, but the highly specialized purpose and distinct siblings make the usage context clear enough.

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 indicate readOnlyHint=false and destructiveHint=false. The description adds context about including conversation for reproduction, but doesn't disclose what happens after submission or any side effects. This is adequate but not comprehensive.

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 purpose and provides essential guidance without any 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?

For a tool with 3 parameters and no output schema, the description is insufficiently detailed. It leaves 'context' unexplained and doesn't clarify return behavior or submission effects. The tool is simple, but the lack of parameter guidance is a clear gap.

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 has 3 parameters with 0% description coverage. The description mentions the 'conversation array' and 'recent messages' but doesn't explain the 'context' parameter or that 'message' is required. It also calls 'conversation' an array while the schema defines 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 'Report a bug, missing feature, or send feedback' with a specific verb and resource scope. This distinguishes it from siblings like authenticate and marketplace, which serve entirely 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?

It implies usage when the user needs to report issues or feedback and gives context by instructing to include the conversation array for reproduction. It doesn't explicitly name alternatives or exclusions, but sibling tools are obviously different in function.

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 that the tool is read-only, idempotent, and non-destructive. The description adds no further behavioral context (e.g., authentication requirements, side effects, or rate limits), which is acceptable for this simple read-only operation but credits only minimal extra value.

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 is front-loaded with the verb 'Show' and contains no unnecessary words or repetition. It is maximally 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's simplicity—no parameters, no output schema, and straightforward read-only behavior—the description fully conveys what the tool does and what information it returns (current platform and adapter versions). No additional context is necessary.

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, triggering the baseline score of 4. The description does not need to define parameter semantics since none 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 clearly states the tool's action ('Show') and its specific resource ('current MCP platform and adapter versions'), distinguishing it from sibling tools like authenticate or connect. It's not a mere restatement of the tool name and leaves no ambiguity about its purpose.

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?

No explicit usage guidance or alternatives are mentioned. The tool's purpose implies when it should be used (when version information is needed), but the description does not provide any comparative context or exclusions, so the guidance remains 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 and idempotentHint=true, so the safety profile is clear. The description adds value by detailing what information is returned (installed MCPs, connection status, accounts, tool counts). This goes beyond the annotations, providing substantive behavioral context 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, well-structured sentence that lists all key outputs without any fluff. It is appropriately sized and front-loaded with the main purpose ('Returns the current toolkit state'). Every word contributes meaning.

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 (0 parameters, no output schema), the description fully explains what the tool returns and implies its read-only nature. It is complete for an informational tool, and the annotations reinforce its safety. No additional information is 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 0 parameters, so the schema is fully covered with no parameter documentation needed. The description explains the output content in detail, which is the relevant semantic information here. A baseline of 4 is appropriate for a no-parameter tool that delivers useful information via its description.

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 what the tool does: returns the current toolkit state, including installed MCPs, connection status, connected accounts, and the number of catalog tools each exposes. This is a specific verb ('Returns') with a clear resource ('current toolkit state') and distinguishes it from sibling tools like authenticate, connect, marketplace, 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 implicitly indicates when to use this tool (to query current toolkit state), and the context signals show it has no parameters. However, it does not explicitly mention when not to use it or alternatives. Given its simple read-only nature and clear purpose, a clear usage context is provided, but exclusions are not specified.

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