MPT PR: Certidão Negativa de Feitos

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

Annotations declare idempotentHint=true and destructiveHint=false, which the description does not contradict. The description adds behavioral context: calling with no args returns a login link (browser interaction), and passing a token performs a session login. It does not detail what happens after login (e.g., session persistence), but given the idempotent nature and non-destructive flag, the description provides sufficient extra 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, dense paragraph that front-loads the tool's purpose and immediately gives actionable instructions. Every sentence adds value: explaining the browser flow, proposing the best permanent setup, and offering the session-only alternative. 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 tool's simplicity (one optional parameter, no output schema) and the clear guidance in the description, the description is complete. It covers the two usage modes, explains the permanent vs. session options, and even mentions the header format. The lack of an output schema is acceptable because the tool's result is a connection state, not a data resource.

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 one optional parameter 'token' with no description coverage (0%). The description explains its semantics: it's a JWT to be pasted for session-only login. It also clarifies that calling without the parameter triggers a link generation. This fully compensates for the lack of schema description, though it doesn't detail token format beyond 'jwt'.

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: authenticate an MCP IDE agent by logging in via browser and providing a token. It distinguishes itself from sibling tools (connect, marketplace, etc.) by focusing on authentication, not connectivity or browsing. The verb 'authenticate' plus the token parameter make the resource and action explicit.

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 when-to-use and how-to-use guidance: for permanent connections, add token to server config; for session-only, pass token or call with no args to get a link. It explains the trade-offs between permanent and session-based login, which helps the agent decide which path to recommend.

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 readOnlyHint:true and idempotentHint:true, which the description complements by detailing the two output cases (authenticated:true vs connect_url presence). It adds value beyond annotations by explaining the conditional responses, so it's not a mere repetition.

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 consists of two sentences: the first immediately states what it does, and the second explains the two conditions. It is front-loaded, efficient, and contains no filler or redundancy.

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?

Despite having no parameters and no output schema, the description fully covers the tool's behavior for a simple status check. It explains both possible results (authenticated:true vs connect_url) and gives enough context for an agent to invoke it appropriately.

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 parameters, the schema coverage is 100% and the description adds nothing about parameters because there are none. Per rubric, a 0-parameter tool gets a baseline of 4, and the description doesn't need to elaborate.

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 a specific verb and resource. It distinguishes itself from sibling tools like 'authenticate' by focusing on status reporting rather than authentication actions, and it explains the two possible scenarios.

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 provides clear context on when this tool is appropriate—checking whether all providers are connected or retrieving connection URLs. However, it doesn't explicitly mention when not to use it or name alternative tools, so it lacks explicit 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 description adds substantial behavioral context beyond the annotations: invoke works even when the MCP is not installed, it runs one-off without bloating the toolkit, credential gaps return a connect link, empty wallets return a checkout link, and install/subscribe/cancel are writes requiring owner/admin. 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?

The description is long but front-loaded with the core flow and key caveats. It is dense with useful information, though the run-on style and lack of bullet structure make it harder to scan. Every sentence adds value, but formatting could be improved.

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 high complexity (23 params, 14 actions, no output schema), the description covers all major action families, auth requirements, one-off vs permanent behavior, and the prompt-library workflow. It lacks return-shape details and per-parameter formats, but is otherwise sufficiently complete for an agent to navigate the 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?

Schema description coverage is 0%, so the description carries the full burden for explaining 23 parameters. It explains the action enum and the core flow at a high level, but leaves many parameters undocumented: limit/query defaults, arguments format, prompt_vars shape, cancel_reason enum, prompt_targets, and others. This 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 marketplace as the official mcp.ai catalog and execution layer for MCPs, with a concrete search→describe→invoke flow. It distinguishes this tool from siblings by positioning it as the in-platform catalog/runner and covers the prompt-library sub-feature explicitly.

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 use, use install only for permanent toolkit membership, use list_tools for currently callable tools, and use request_mcp when nothing fits. It also states that writes require workspace owner/admin, which is a clear usage constraint.

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 declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, which align with the description of a query-only operation. The description adds value by disclosing that it requires prepaid credits, is hosted by the platform, and clarifies data privacy aspects (not confidential data, LGPD responsibilities). This goes beyond the annotations 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, dense paragraph but efficiently conveys the tool's purpose, data source, payment model, and legal compliance. It's a bit long but each sentence carries meaningful information. Could be more structured with line breaks, but it's far from verbose.

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 (two optional string params, no output schema, read-only), the description covers the essential context: what it does, where it gets data, commercial terms (prepaid), and legal framing. The main gap is not specifying if at least one parameter is required and lack of behaviour when neither is provided, but this is minor for an agent.

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. While it doesn't explain 'cpf' or 'cnpj' individually, it clearly indicates the tool is for consulting 'Certidão Negativa' using CPF/CNPJ (which are standard Brazilian identifiers). The parameter names themselves are self-explanatory and the description provides sufficient context for an agent to infer their usage. Could have been more explicit about whether at least one is required (required params: 0).

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 'Certidão Negativa de Feitos' (Negative Certificate of Court Records) and its purpose: to consult official sources for CPF/CNPJ data. It also differentiates itself by mentioning it is hosted on their platform, requires prepaid credits, and addresses LGPD compliance, which uniquely positions it among 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 explains when to use this tool: for consulting data from official Brazilian sources, emphasizing it's the same non-confidential info available to citizens, and that the client is the data controller. It does not explicitly name alternative tools, but given the sibling list (authenticate, connect, etc.), the usage context is clear. Lacks explicit 'do not use if...' but covers the main use case.

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 non-destructive, non-read-only behavior. The description adds valuable context by specifying that the conversation array should be included for reproduction, which is a behavioral detail not captured elsewhere. No contradictions 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?

The description is concise, with a clear two-sentence structure: one for purpose and one for an actionable tip. Every sentence earns its place without redundancy.

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 feedback tool with three params and no output schema, the description covers the essential purpose and provides a key usage hint (conversation for reproduction). It could explicitly mention the 'message' param as the main content, but the overall completeness 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?

Schema description coverage is 0%, so the description must compensate. It highlights the 'conversation' parameter and implies 'message' is the core content, but does not explain 'context' or add format/type details. It adds some value over the bare schema but does not fully compensate for all three params.

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: reporting bugs, missing features, or sending feedback. It uses specific action verbs and identifies the resource (bug/feature/feedback), effectively 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?

It provides clear context on when to use the tool (reporting any issue or feedback) and even includes an instruction about including the conversation array for reproduction. It does not explicitly mention alternatives, but siblings are unrelated, so the usage context 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=true, idempotentHint=true, and destructiveHint=false, so the agent knows it's a safe, read-only operation. The description adds clarity that it reports both MCP platform and adapter versions, which is useful context. No contradictions.

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?

One sentence, zero waste. Information is front-loaded: it immediately states what it shows.

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 version-check tool with no parameters and no output schema, the description is complete. It covers everything an agent needs to know: it shows versions. The annotations cover safety.

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 need not add parameter details. The schema already covers everything (100% coverage), and the description accurately conveys that it is a simple, no-argument call.

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: displaying current MCP platform and adapter versions. The verb 'show' is specific and the resource is well-defined, 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?

The description implies that the tool is used when the user needs to know versions, but it does not explicitly state when to use it versus alternatives. It's a straightforward informational tool, so the context is clear, but there is no mention of when not to use it or alternatives.

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, covering the safety profile. The description adds useful context by listing exactly what state is returned, but it does not disclose potential caveats like timing, error behavior, or performance. This matches the bar for a safe read operation with some added return-content detail.

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 entire description is a single well-structured sentence that front-loads the verb and resource, then expands with a concise list of returned details. Every phrase adds value with no redundancy or filler.

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 info tool with no output schema, the description adequately explains the return contents. It could be slightly more complete by noting whether the state is live or cached, but given the tool's simplicity, the description covers the essential information.

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, making schema coverage trivially 100%. The description correctly focuses on output rather than parameter semantics, so it meets the baseline of 4 for parameterless tools.

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 'returns' and clearly identifies the resource as 'current toolkit state,' followed by a concrete enumeration of contents (installed MCPs, connection status, accounts, catalog tool counts). This differentiates it from siblings like authenticate, connect, or show_version, which focus on actions or version details.

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 conveys clear usage context: it is the tool to inspect toolkit state, including installed MCPs and connections. It does not explicitly mention when not to use it or name alternatives, but its scope is obvious next to sibling tools, warranting a 4 rather than 5.

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