Prefeitura AP Macapá: Certidão Negativa de Débitos

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

Discloses behavioral traits beyond annotations: config-based login is permanent/non-expiring, pasting is session-only, and no-args returns a link. This adds useful context that annotations (idempotent, non-destructive) don't capture.

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 purpose and concrete usage. The second sentence is long but information-dense, covering both authentication modes. 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?

For a simple one-parameter tool, it covers both usage modes (config vs session) and the no-arg link. No output schema exists, but description gives enough context. Slight gap: doesn't state what happens after successful authentication (e.g., confirmation message or session state).

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 only defines 'token' as a string with no description. The description explains it's a JWT to paste, and that omitting it yields a link. This fully compensates for the 0% schema coverage by adding semantic 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?

Description clearly states this authenticates MCP.AI for IDE agents, with a specific login flow. It distinguishes from siblings by targeting IDE agents (Cursor, etc.) and the action is concrete: log in and copy access token.

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?

Provides explicit usage instructions: best practice is adding token to config for a permanent connection, or pasting token for session-only login. Also explains no-args call yields a link. However, it doesn't explicitly mention when to use this over sibling 'connect'.

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 elaborates on the behavior by detailing the two response cases (authenticated:true with empty pending, or connect_url for missing credentials). This adds transparency beyond the readOnly/idempotent annotations, though it does not discuss potential side effects or errors.

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, using two sentences to convey the core functionality and edge cases. It is well-structured and free of redundant 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?

The description covers the main purpose and key behaviors. It mentions the output fields (authenticated, pending, connect_url) and the two scenarios, but does not specify the full response structure or error handling, which is reasonable given the 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?

There are no parameters in the schema, so the description does not need to explain them. The absence of parameters is adequately covered, and no additional meaning is required.

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 between two scenarios (all providers connected vs. missing credentials). This is specific and 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 explains what the tool does but does not explicitly indicate when it should be used relative to alternatives like 'authenticate' or 'show_version'. No usage context or exclusions are provided.

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 goes well beyond annotations by detailing that invoke runs one-off without installing, returns connect/checkout links, requires owner/admin for writes, and that search/describe flag installation status. It also covers the prompt library behavior. No contradiction with readOnlyHint=false or destructiveHint=false.

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, dense paragraph that front-loads the core purpose, then sequentially covers the flow, key behaviors, permissions, and the prompt library. Every sentence adds essential information without redundancy; it earns its length by covering a multi-action tool thoroughly.

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 (14 actions, 23 params, auth, billing, prompt library), the description is remarkably complete. It explains the full workflow, edge cases (invoke without install, connect/checkout flows), permission requirements, and even the prompt publishing link behavior. No output schema exists, but the description adequately explains expected returns for each major 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?

The schema has 23 parameters with 0% description coverage, but the description compensates by explaining the core action parameter's values (search, describe, invoke, etc.) and their purposes. It also indirectly clarifies tool_id for invoke, mcp_id for describe, and prompt_slug for get_prompt. It doesn't explicitly detail limit or other minor params, but the high-level flow is well covered.

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 is the official mcp.ai marketplace, capable of discovering and running MCPs. It names the primary actions (search, describe, invoke, install) and distinguishes the tool from siblings by its role as the in-platform catalog and execution layer.

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?

Explicit guidance is provided: 'prefer invoke for a single/occasional use' vs 'use install only to make an MCP PERMANENT', plus when to use list_tools, subscribe/cancel, report_bug, request_mcp, and prompt library actions. It also notes auth requirements for write operations and the workflow for credential/payment handling.

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 cover safety (read-only, non-destructive). Description adds useful behavioral context: hosting model, payment requirement, data governance (LGPD) and that data is not confidential, which goes beyond the structured 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 efficient and front-loaded with the core purpose, though the legal/payment details add length. It remains reasonably 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?

Given 3 undocumented parameters and no output schema, the description explains the purpose and payment model but leaves parameter semantics and expected response ambiguous. Adequate for a simple lookup 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?

Schema has 0% description coverage and the description does not explain any of the three parameters (cpf, cnpj, tipo_certidao). No semantic meaning is added beyond the bare property names, which is insufficient for correct invocation.

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?

Description states the specific action ('consulta' for CND), the specific resource (Prefeitura AP Macapá Certidão Negativa de Débitos), and clearly distinguishes from generic sibling tools like authenticate or 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?

Provides context on how to use (paid per query, no platform credentials needed) and what data source is queried (official Brazilian sources). Does not explicitly mention when not to use, but the specificity makes it clear it's for this particular certificate.

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, covering basic behavioral expectations. The description adds the useful instruction to include the conversation array for reproduction, but does not disclose further side effects or requirements beyond what annotations 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 two short sentences, front-loaded with the action and purpose. Both sentences provide necessary information without filler, making it highly concise and well-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 low-complexity tool with one required parameter and supportive annotations, the description covers the core purpose and key parameter instruction. It could mention the 'context' parameter and expected outcome, but the current description is adequate for a basic reporting tool.

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 descriptions cover 0% of parameters, so the description must compensate. It clarifies that 'conversation' should contain recent messages and implies 'message' is the report text, but 'context' remains unexplained. This partial compensation results in a middle score.

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 specific verb 'Report' and clearly defines the scope: bug, missing feature, or feedback. It is not a tautology and distinguishes itself from unrelated sibling tools by stating the action and content.

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 use (reporting bugs or feedback) and instructs to include a conversation array for reproduction, but it does not explicitly exclude any scenarios or mention alternatives. Since no sibling tool serves a similar purpose, this level of guidance is sufficient.

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 and idempotentHint, so the safety profile is covered. The description adds the 'current' status and specifies that both platform and adapter versions are returned, providing useful context 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, efficient sentence with zero wasted words. It states exactly what is shown without elaboration.

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 read-only, parameterless version tool, the description is fully sufficient. No output schema exists, but the output is self-evident from the description. Complexity is minimal, and no additional details are required.

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 the description correctly implies no inputs are required. With no params, the baseline is 4, and the description adds no unnecessary overhead.

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 shows current MCP platform and adapter versions, using a specific verb ('show') and resource ('MCP platform and adapter versions'), distinguishing it from sibling tools 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?

Though not explicitly alternative-excluding, the purpose is unambiguous for a version-information tool. The description implies use when version details are needed, and no conflicting tools exist for this 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 and destructiveHint=false, so the safety profile is known. The description adds valuable context about the returned data (installed MCPs, connections, accounts, catalog tool counts) beyond just saying 'returns state', providing useful behavioral details.

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, well-structured sentence that front-loads the purpose and enumerates what is returned. 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?

For a zero-parameter read-only tool with no output schema, the description adequately explains what is returned (installed MCPs, connection status, accounts, catalog counts). It is complete enough for an agent to understand the tool's purpose and typical usage without ambiguity.

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 is 4. The description correctly implies no parameters are needed by describing a read-only state query. No additional parameter explanations required.

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 components (installed MCPs, connection status, accounts, catalog tool counts). This is a specific verb+resource with a clear scope, and it distinguishes 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 when to use it (to get an overview of toolkit state) without needing complex exclusions. It doesn't explicitly name alternatives, but the sibling names make it obvious this is the informational read tool. Clear context, no misleading guidance.

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