MPT AC e RO: Certidão Negativa de Feitos

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

Beyond the annotations, the description discloses what a no-arg call does, what a token-bearing call does, and that a configuration header gives a permanent non-expiring connection. It aligns with idempotentHint=true and does not contradict readOnlyHint=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 concise and front-loaded with the auth flow while separating the permanent-config and session-only paths using 'Best:' and 'Or:'. It is slightly dense but every clause contributes meaningful guidance.

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 an auth tool with one optional parameter and no output schema, it explains both invocation modes and the underlying login concept well. It does not describe exact success/failure result content, but the practical behavior is sufficiently 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 only defines an optional token string with no description, but the tool description compensates by showing the expected call shape { token: "<jwt>" } and the no-arg behavior. This covers the parameter semantics despite 0% schema description 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 states with specific language that this tool authenticates an MCP.AI server for IDE agents, via browser login and JWT/access token passage. It also clearly distinguishes the behavior from the sibling tools such as connect, marketplace, and report_bug.

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 usage guidance: use the server config header for permanent auth, paste a token for session-only auth, or call with no arguments to get the login link. It does not name alternative sibling tools or exclusions, but the intended usage is clear.

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 readOnly, idempotent, and non-destructive behavior. The description adds meaningful output details (authenticated true, empty pending, connect_url scenarios), enhancing transparency 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 concise, consisting of two clear sentences with no redundancies or extraneous information. It is well-structured and directly to the point.

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 there is no output schema, the description sufficiently explains the return behavior in both defined scenarios. It covers the main outcomes, though it does not elaborate on error cases or other potential edge states, leaving slight room for completeness.

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 schema coverage is complete. There is nothing to add about parameters, so the baseline score of 3 applies.

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: 'Returns connection status and URLs.' It distinguishes itself from sibling tools like authenticate and show_version by focusing on connection status, making its purpose 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 provides conditional behavior (when all providers are connected vs. credentials missing) but does not explicitly instruct when to use this tool over alternatives. It implies usage for checking connection status but lacks direct guidance on when not to use it or use a different tool.

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, the description discloses important behaviors: invoke works without installing, one-off runs don't bloat the tool list, credential/payment flows return links, writes require workspace owner/admin, and search/describe flag installation status. 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 densely packed and well-structured, front-loading the core flow and key differentiators. Every sentence adds meaningful context, though it could be tightened by separating the prompt-library section.

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, 23 parameters, and no output schema, the description covers the main flows, permissions, and billing behavior well. However, it does not fully specify parameter usage or return shapes for many actions, so an agent would still face uncertainty when constructing calls.

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% with 23 parameters, so the description must compensate. It explains the action enum and the role of tool_id, but most parameters (query, limit, mcp_id, arguments, immediate, tier_slug, prompt_*, request_*, cancel_*) are left unexplained, leaving significant ambiguity 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?

The description clearly identifies the tool as the official mcp.ai marketplace and run mechanism, with a specific core flow (search → describe → invoke). It distinguishes itself from siblings by covering catalog search, one-off invocation, installation, billing, and prompt library actions.

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: prefer invoke for one-off use, use install only for permanent toolkit additions, use list_tools for currently callable tools, use request_mcp when nothing fits, and subscribe/cancel for billing. It also explains when invoke returns connect or checkout links and that writes require owner/admin.

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 read-only and idempotent annotations, the description adds valuable behavioral details: it notes that no platform credentials are required, that each query is paid via prepaid credit, and that the data is not confidential and sourced from official Brazilian outlets. It also mentions LGPD compliance, enriching 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 a single paragraph that is concise yet informative. It begins with the main purpose, then adds relevant details about hosting, payment, and data privacy. The structure is acceptable, though it could be slightly more organized with bullet points or sections.

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?

While the description provides context about the source, payment, and data sensitivity, it does not describe the return format or what the certificate contains beyond being 'negative'. It also omits error handling or edge cases. Given the lack of an output schema, this leaves some ambiguity about the response.

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 lists 'cpf' and 'cnpj' as string parameters but provides no description, and the tool description does not explain their purpose or requirements. It is left to inference that they are identifiers, but no clarification on when each is used or required is given, so the description fails to compensate for the schema's lack of detail.

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: it queries an official source for a Negative Certificate of Feitos (Certidão Negativa de Feitos) specifically for MPT AC and RO. The mention of 'consulta em fonte oficial' and the specific certificate type provides a unambiguous 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?

The description does not explicitly instruct when to use this tool versus alternatives or mention any related tools. It implies the use case (checking for legal cases) but lacks explicit guidance or differentiation from other possible tools.

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 idempotent and non-destructive behavior, but the description does not elaborate on side effects or outcomes beyond 'reporting.' It adds little beyond the annotations, and does not contradict 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 concise—two sentences that directly state the action and the key required input. No fluff 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?

Given the three parameters, the description is incomplete. It does not explain the meaning or format of each parameter, nor does it describe any return value or side effects (though there is no output schema).

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 only mentions the 'conversation' parameter, leaving 'context' and 'message' unexplained. The schema has no descriptions, so these parameters are insufficiently documented.

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 a bug, missing feature, or sending feedback. This is specific and distinct 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 a specific instruction to include a conversation array for reproduction, which suggests when to use the tool (when reporting an issue that needs context). However, it lacks explicit 'when not to use' guidance 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 indicate read-only and idempotent behavior; description adds no extra behavioral context beyond showing versions, which is consistent.

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 concise sentence with clear subject and action, no unnecessary 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 version display, the description fully conveys purpose; no output schema is given but it's implicit.

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?

No parameters exist, so schema coverage is complete; description adds no parameter info.

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?

Clearly states it shows versions, distinguishing it from sibling tools which are about authentication, connectivity, marketplace, etc.

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 guidance on when to use this tool versus alternatives; it's assumed for version checks but not stated.

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 destructiveHint, and the description adds useful context by specifying exactly what state is returned (MCPs, accounts, catalog counts). It does not introduce contradictions and provides a bit more behavioral detail beyond 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?

A single, concise sentence that immediately states the purpose and enumerates the returned data points, with no wasted words. It is well-structured and 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 info tool with no parameters, no output schema, and annotations covering safety, the description is complete. It tells the user exactly what kind of information will be retrieved, making it sufficient for an agent to use correctly.

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 100% schema coverage, so there is nothing to document. The baseline of 4 for a parameterless tool applies; the description didn't need to add parameter semantics, and it didn't.

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 elements: installed MCPs, connection status, connected accounts, and catalog tool counts. This specific inventory of resources distinguishes it from sibling tools like connect or authenticate.

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 makes it clear that the tool is for retrieving an overview of the toolkit state, implying use when an agent needs an inventory or status check. However, it does not explicitly mention alternatives or when not to use it, lacking explicit exclusion criteria.

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