MPT Unificada: Certidão Negativa de Feitos

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

The description discloses key behaviors: two login modes (permanent config vs session token), the non-expiring nature of the header approach, and the fact that no args returns a browser link. This adds context beyond the annotations (idempotentHint, destructiveHint), though it omits error cases or side effects.

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 logically flows from the overall purpose to the two invocation modes. It includes relevant audience context but every sentence contributes to understanding. It could be slightly shorter by removing the 'MCP.AI for IDE agents' preamble, but it remains 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?

For a tool without an output schema, it covers the essential behaviors: the two authentication paths, persistence characteristics, and the link-returning call. It does not detail the exact response for a token submission, but that is less critical given the tool's simplicity and the annotations' safety profile.

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 only a bare 'token' string, and the description fully compensates by explaining it is an optional JWT, demonstrating the exact usage pattern '{ token: "<jwt>" }' and clarifying that omitting it provides a link. This is a strong semantic addition beyond the 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's purpose: authenticating IDE agents with MCP.AI via browser login and token handling. It goes beyond a simple verb+resource by outlining two distinct authentication flows, making it clearly distinguishable from 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?

It provides clear 'how to use' guidance: either configuring a permanent header (best practice) or passing a token for session-only login, plus the no-args behavior to get a link. It does not explicitly mention when not to use it or compare with alternatives, but the context is sufficient for an agent to determine applicability.

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 read-only, idempotent, and non-destructive behavior. The description adds meaningful conditional context: all providers connected returns authenticated:true with empty pending[], while missing credentials returns connect_url and per-install URLs. This goes beyond what annotations convey.

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 with no filler. It front-loads the core purpose and then efficiently explains the two important output states.

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, parameterless, read-only status tool with no output schema, the description sufficiently covers the main return scenarios: connected state and missing-credentials state. No critical behavioral context is missing.

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 schema description coverage is 100%, so the schema carries full parameter information. Per the baseline for parameterless tools, the description is not required to add parameter 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 uses a specific verb ('Returns') with a clear resource ('connection status and URLs'), and distinguishes this tool from siblings by describing its output states. Unlike authenticate or show_version, this is explicitly the status/URL retrieval tool.

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 the tool: when you need connection status or connect URLs. However, it does not explicitly state when not to use it or mention alternatives like authenticate, so guidance is only 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 indicate non-read-only and non-idempotent behavior, and the description adds substantial context: invoke runs one-off without installing, missing credentials return a connect link, unpaid paid MCPs return a checkout link, and writes require workspace owner/admin. It also discloses the prompt library's shareable link 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 long but appropriately so for a multi-action dispatcher. It is front-loaded with the core flow and KEY invoke behavior, and each section adds distinct value. It could be improved with bullet points or clearer separation between the MCP marketplace and prompt library 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?

It covers the main flows, side effects, auth requirements, and several return behaviors (connect link, checkout link, shareable prompt link). However, with no output schema, it omits return shapes for search/describe, and it never mentions the 'resume' action or several action-specific parameters, leaving notable gaps for a tool of this complexity.

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 and 23 parameters, the description compensates by explaining the critical action parameter and the tool_id flow, plus prompt variables and slug concepts. However, many parameters (immediate, tier_slug, conversation, prompt_targets, report_context, request_details) remain unexplained, so it only partially bridges the 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 mcp.ai marketplace and the way to run MCPs, with an explicit core flow (search → describe → invoke). It distinguishes itself from siblings by covering catalog discovery, execution, 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?

It gives explicit when-to-use guidance: 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT'. It also explains when to use list_tools, request_mcp, report_bug, and the prompt library actions, providing clear 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?

Beyond the annotations (read-only, idempotent), the description adds behavioral details such as requiring prepaid credits and not needing credentials, which are useful. However, it does not describe potential error states, rate limits, or what happens with invalid inputs.

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 repetitive, stating the same information about official sources and non-classified data multiple times. It could be condensed into a single clear sentence, reducing 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?

The description lacks essential context about the expected inputs (parameter semantics), what the output looks like, and any restrictions (e.g., required fields, data format). It gives some background about the source and payment but is incomplete 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?

The input schema includes 'uf', 'cpf', and 'cnpj', but the description provides no explanation of these parameters. It does not clarify that 'uf' likely means state, or how CPF/CNPJ are used. This is a major gap since the schema descriptions are absent.

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 official sources for negative certificates (Certidão Negativa de Feitos) and is distinct from the sibling tools such as authenticate or report_bug. However, it could be more specific about the exact nature of the certificate and its use case.

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 state when to use this tool vs alternatives or provide any situational guidance. It mentions that it is hosted, pay-per-query, and uses no credentials, but these are contextual details rather than usage guidelines.

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 and destructiveHint=false, which are consistent with the description (no contradiction). The description adds context by instructing to include the conversation array for reproduction, which goes beyond annotations, aiding the agent in understanding what data to provide. No annotation contradictions 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 a single sentence, highly concise, and front-loaded with the purpose. Every word earns its place; no 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 simple tool with 3 params, no output schema, and moderate annotations, the description covers the essential usage (what to do, what to include). It could mention if there's a response or confirmation, but given the simplicity, it's nearly complete. The 'context' parameter remains vague, but that's a minor 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 coverage is 0%, so the description must compensate. It explicitly mentions 'conversation' array with recent messages, clarifying the 'conversation' parameter beyond the schema's bare type. It also implies 'message' is the bug/feedback text, but 'context' is not explained. Given the low coverage, the description provides significant added meaning for two of three 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 the tool's purpose: reporting bugs, missing features, or feedback. It distinguishes from siblings (no other tool does this) and mentions including conversation for reproduction. However, it doesn't explicitly name the resource (e.g., 'report to the development team') but the intent 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?

It suggests when to use (report a bug, missing feature, feedback) and implies including conversation for reproduction, but doesn't explicitly say when NOT to use or mention alternatives. Sibling tools like 'marketplace' or 'toolkit_info' are different, so context is clear but exclusions are absent.

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 safety profile is fully covered. The description adds the detail that it shows both platform and adapter versions, which is slightly beyond what the annotations provide. But it doesn't disclose behaviors like whether it makes network calls, whether it requires authentication, or any side effects. Given the annotations are strong, a score of 3 is appropriate.

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 that conveys the essential purpose without any wasted words. It is perfectly concise 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?

Given this is a simple query tool with zero parameters, strong annotations, and no output schema, the description is sufficient. It explains what the tool does (shows versions) and the annotations cover safety. The only minor gap is not explaining what the output looks like, but since there's no output schema and the tool is trivial, this is not a major issue.

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 there is no parameter semantics to explain. Per the rubric, with 0 parameters, the baseline is 4. The description correctly implies no inputs are needed.

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: showing the current MCP platform and adapter versions. It is specific and distinguishes itself from sibling tools like authenticate, connect, and report_bug, which have different purposes. However, it doesn't explicitly contrast with sibling tools like toolkit_info, which might also provide version information, but the focus on 'current MCP platform and adapter versions' 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?

The description implies when to use this tool (when you need version information), but it doesn't provide explicit guidance on when not to use it or mention alternatives. Given that there is a sibling tool 'toolkit_info' that might also return version info, the description could have mentioned that distinction. Still, the context is clear for a simple display 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?

Annotations already indicate readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is clear. The description adds that it returns 'current toolkit state' but doesn't disclose any behavioral specifics like rate limits or authentication needs. Given the strong annotations, this is adequate but adds little extra.

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 that efficiently enumerates the key components of the toolkit state. 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 zero-parameter tool with no output schema, the description provides a complete overview of return content. It could mention that it's a snapshot, but the existing text adequately covers the tool's purpose and output.

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 parametersaine schema coverage is 100% (trivially). The description adds value by detailing exactly what the output includes (installed MCPs, status, accounts, catalog tool counts), which helps the agent understand what to expect from the 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 verb 'Returns' with a specific resource 'current toolkit state' and enumerates the specific items returned (installed MCPs, connection status, accounts, catalog tools). This distinctly separates it from sibling tools like authenticate, connect, 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?

The description provides no guidance on when to use this tool versus alternatives. It simply states what it returns, with no context for use cases, preconditions, or exclusions.

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