MPT BA: Certidão Negativa de Feitos

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

Annotations indicate idempotent and non-destructive behavior. The description adds context by explaining the permanent vs. session-only nature of the login, which implies state changes but does not explicitly disclose side effects. Given the annotations already cover safety, the description provides sufficient transparency.

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 yet informative, covering both usage methods and invocation syntax without unnecessary verbosity. It is well-structured, though slightly dense with multiple clauses.

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 enough context to successfully use the tool, including two workflows and the meaning of the token parameter. It does not mention return values, but the lack of an output schema makes that acceptable. Overall, it is complete for its purpose.

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 single optional 'token' parameter is explained: it is used for session-only login when pasted, and its absence triggers retrieval of the login link. This clarifies its role, even though the schema lacks a description, so the description compensates well.

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: authentication for MCP.AI IDE agents, with explicit instruction to log in and copy an access token. It distinguishes from sibling tools like connect or show_version by focusing solely on authentication.

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 concrete usage alternatives: adding the token to config for a permanent connection, or passing it as a parameter for session-only login. It also explains how to invoke with or without arguments, giving clear guidance on when to use each method.

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 readOnly/idempotent annotations, the description explains behavior in both success ('authenticated:true') and failure/missing-credential cases, including the returned URLs. This provides clear insight into tool 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 two concise sentences with no redundant information, clearly structured 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?

Without an output schema, the description fully explains the return value (connection status and URLs) and covers the key edge case of missing credentials, making it 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?

There are no parameters, so the baseline is 4. The description does not need to explain parameters, and the schema already covers 100% of them (none).

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, with specific details about two output scenarios. This distinguishes it from siblings like 'authenticate' which likely performs a different 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 implies usage for checking connection status but does not explicitly state when to use it over alternatives. No direct comparison to sibling tools like 'authenticate' or 'marketplace' is 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 discloses key behavioral traits beyond annotations: invoke runs uninstalled MCPs one-off without bloating the tool list, returns connect links for missing credentials, returns checkout/top-up links for empty wallets, and requires owner/admin for writes. These details are consistent with annotations; 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 long but dense and well-organized, front-loading the core purpose and then flowing through discovery, invocation, installation, billing, and the prompt library. Every sentence adds useful information, though the single-block structure could benefit from clearer sectioning.

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 complex 14-action, 23-parameter tool with no output schema, the description is unusually complete: it covers the main flows, auth requirements, billing edge cases, and prompt library behavior. It stops short of a 5 because some actions (e.g., resume) and parameters (e.g., arguments format, immediate) are not addressed.

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 adds meaning to the action enum and key parameters like tool_id, mcp_id, prompt_slug, and prompt_vars by embedding them in the workflow. However, with 23 parameters and 0% schema coverage, many parameters (limit, query, arguments, immediate, tier_slug, cancel_reason, conversation, request_details, etc.) remain unexplained, so the description only partially compensates for the schema 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 'the official mcp.ai marketplace' and explains its dual role as catalog and execution layer. It specifies the core search→describe→invoke flow and distinguishes its scope from siblings by covering MCP discovery, running, installation, billing, 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?

The description gives explicit when-to-use guidance: prefer invoke for one-off/occasional use, use install only for permanent toolkit membership, use list_tools for what is callable right now, and use subscribe/cancel/report_bug/request_mcp for their respective purposes. It also explains the prompt library actions and when they apply.

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 notes 'não é dado sigiloso' and implies read-only through 'consulta', but does not explicitly state that no modifications occur or what happens on errors. The annotation already indicates read-only, so the description adds some transparency but not full.

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 somewhat repetitive, repeating 'consulta' and 'informação', but overall it is relatively short. It could be streamlined without losing 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?

It covers purpose, payment, and data responsibility, but omits output format, error handling, and any additional constraints. Since there is no output schema, this description is incomplete for a full understanding.

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 lists the parameters 'cpf' and 'cnpj' but provides no explanation of their format, requiredness, or semantics. This is minimal coverage, leaving users guessing.

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 'consulta em fonte oficial' with the specific resource 'Certidão Negativa de Feitos' from MPT BA, distinguishing it from sibling tools like 'authenticate'. It lacks a bit of detail on the exact nature of the certificate but is clear enough.

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 mentions payment via prepaid credits, that the data is not confidential, and that the client is the data controller per LGPD. It does not mention when to use this vs alternatives, but these usage guidelines are helpful.

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 idempotentHint: true, which is a key behavioral trait. The description does not mention idempotency or any other behavioral details like whether the action is persistent or reversible. It does not contradict the annotations, but it adds minimal behavioral context beyond what the annotations already state. For a tool that likely sends a report and might have side effects (even if idempotent), more transparency (e.g., that the report is stored, that it does not modify user data) would be beneficial. Since annotations already cover some aspects, the score is 2, not 1.

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 sentences and concise. The first sentence states purpose, the second gives critical usage instruction about including the conversation array. It front-loads the purpose and adds the essential parameter hint. No extra fluff. It could arguably be slightly more structured (e.g., bullet points for params), but it earns a high score for efficiency.

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 3 parameters and requires at least a message, the description provides the core purpose and a key detail about the conversation parameter. However, it does not explain the expected format of 'message' (e.g., should it be a formal report with steps?) nor the role of 'context'. There is no output schema, so the description might need to mention expected outcome, but it's not always required. The completeness is partial; it's enough for a simple bug report but leaves gaps for effective 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?

Schema description coverage is 0%, and there are 3 parameters. The description only hints at the 'conversation' parameter by saying 'Include the conversation array with recent messages for reproduction.' It does not explain the 'message' or 'context' parameters. The schema has defaults and types, but without description, the agent may not know the expected content of 'message' (e.g., should it include title, steps, etc.) or how 'context' should be used. The description does not compensate for the low coverage, providing only minimal guidance for one parameter.

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 primary purpose: 'Report a bug, missing feature, or send feedback.' It uses a specific verb ('report') and resource ('bug/feedback'), and it adds the nuance of 'missing feature' and 'feedback' beyond just bug reports. It does not explicitly differentiate from sibling tools, but none of the siblings seem to handle bug reporting, so the purpose is clear.

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 a clear indication of when to use the tool: when reporting a bug, missing feature, or sending feedback. However, it does not explicitly mention situations when NOT to use it or direct to alternative tools for other types of support. Given the sibling list (authenticate, connect, marketplace, etc.), there's no obvious alternative for feedback, so the guidance is adequate but not explicit about 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 annotations already indicate read-only and idempotent behavior; the description does not add additional behavioral context, such as potential side effects or authentication requirements.

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, clear sentence with no unnecessary detail.

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 lack of parameters and output schema, the description fully specifies what the tool does.

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 no parameters, and the description does not need to explain any because the schema is empty.

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: showing the current MCP platform and adapter versions. It also distinguishes 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?

The description does not provide guidance on when to use this tool relative to others, such as when to check versions or if there are prerequisites.

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 behavior, covering safety. The description adds what information is returned (installed MCPs, status, accounts, tool counts) but does not add behavioral traits like auth requirements or rate limits. Given annotation coverage, this is acceptable but not outstanding.

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 core purpose (returns toolkit state) and lists specific contents without unnecessary fluff. Perfectly sized.

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?

No output schema exists, so the description carries the burden of explaining return values. It lists the key components (installed MCPs, connection status, connected accounts, catalog tool counts), which is sufficient for an agent to understand the output. It could mention format or structure, but for a zero-parameter, read-only info tool, this is adequate.

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 zero parameters intended for this toolaine, so semantic coverage is trivially 100%. The description adds value by detailing the output structure (installed MCPs, connection status, accounts, catalog tool counts), which is useful for interpretation 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 explicitly states the tool returns the current toolkit state and enumerates the specific contents: installed MCPs, connection status, accounts, and catalog tool counts. This is a specific verb+resource construction that clearly distinguishes it from sibling tools like show_version (version info) and connect (establishing connections).

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 when to use this tool (to inspect toolkit state) by enumerating its outputs against the context of sibling tools like authenticate, connect, and marketplace. However, it does not explicitly state when not to use it or name alternatives, so it misses the full 'when-not' guidance.

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