MPT DF e TO: Certidão Negativa de Feitos

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

The description discloses the key behavior: calling with no args returns a login link, and passing a token enables authentication. It mentions the permanent vs. session-based nature, but does not explicitly state what happens to existing tokens or any side effects. Since annotations already indicate idempotent and non-destructive, the description adds some but not exhaustive 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 somewhat verbose and rambling, with a long second sentence that combines instructions and rationale. It could be more concise and better structured (e.g., bullet points for the two methods). However, it is not excessively long and contains no redundant 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?

Given the simplicity of the tool (one optional parameter, no output schema), the description covers the essential aspects: what it does, how to use it in two scenarios, and the parameter semantics. It does not mention error handling or return values, but these are not specified in the schema, so the description is adequate for the context.

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 provides no description for the 'token' parameter, but the tool description explains its meaning: it expects a JWT from the user, used for session-only login. It also clarifies that the parameter is optional (no args yields a link). This adds meaning to the parameter beyond the raw 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 clearly states the tool's purpose: to authenticate IDE agents like Cursor via MCP.AI. It specifies the action (log in, copy token) and the resource (MCP.AI), distinguishing it from siblings that handle other tasks like connecting or reporting bugs.

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 usage instructions: either add the token to the server config for permanent access or pass the token in the call for a session-only login. It also explains how to obtain the token (with no args) and when to use each method, giving clear when-to-use guidance.

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 idempotentHint=true, covering safety. The description adds useful behavioral detail about the response structure in different states (authenticated:true with empty pending[], or connect_url), which is not available from annotations. 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 two concise sentences, front-loaded with the main action ('Returns connection status and URLs'), followed by specific behavior. Every sentence adds value, 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?

Given the simplicity (no parameters, no output schema), the description covers the essential behavior for both normal and degraded states. It could mention partial connectivity or errors, but the coverage is sufficient for this simple read-only 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?

There are zero parameters, so the baseline is 4. The description does not need to add parameter semantics, and the schema provides full coverage (100%). No additional explanation 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's function with a specific verb ('Returns') and resource ('connection status and URLs'). It also distinguishes itself from siblings by describing the output under different conditions (all connected vs missing credentials), making it 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 implies usage (e.g., 'When all providers are connected', 'When credentials are missing') but never explicitly says when to use this tool instead of alternatives like 'authenticate'. It provides context but not definitive selection guidance.

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 several non-obvious behaviors not inferable from annotations: invoke runs a one-off install (even when the MCP is not installed), returns connect links for credentials and checkout links for payment, and requires workspace owner/admin for writes. It also explains the difference between installed_in_toolkit vs installed_in_workspace flags, adding rich context 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?

The description is a single dense paragraph but every sentence carries unique information. It is not front-loaded or bulleted, which could be improved, but it avoids fluff and uses clear, imperative language. The length is justified by the tool's complexity, though structure could be enhanced with line breaks.

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 with 23 parameters and no output schema, the description covers the primary workflows (search/discover, describe/select, invoke/run), permission requirements, error flows (auth/checkout links), and the separate prompt library feature. It omits the 'uninstall' and 'resume' action details and some parameter-specific behaviors, but these are minor for an agent selecting the right 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?

With 0% schema description coverage and 23 parameters, the description is the primary source of semantics. It explains the `action` enum values in prose (search, describe, install, invoke, list_tools, subscribe, cancel, report_bug, request_mcp, search_prompts, get_prompt, publish_prompt) and mentions prompt_vars by example. However, many parameters (e.g., limit, immediate, tier_slug, cancel_reason, conversation) receive no explanation, leaving gaps.

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 begins with 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them,' clearly stating its purpose. It details the core flow (search→describe→invoke) and distinguishes itself from sibling tools by describing its role as the central dispatcher and catalog.

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 guidance on when to use which action: 'Use install only to make an MCP PERMANENT...; prefer invoke for a single/occasional use.' It also contrasts list_tools, subscribe/cancel, report_bug, and request_mcp, and explains when to use the prompt library functions. This level of contextual direction goes beyond vague suggestions.

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 read-only and idempotent annotations are already provided, and the description goes beyond them by disclosing the paid-per-query behavior, the official-source nature of the data, the non-confidential classification, and the LGPD responsibility. It does not describe response/error behavior, but the main side effects are well covered.

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 front-loaded with the purpose and keeps the total length reasonable. Some repetition of 'official' and the platform context could be tightened, but the overall structure is easy to parse and relevant.

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 is complete enough for a simple read-only official lookup and includes payment and LGPD context, but with no output schema and no parameter guidance, the agent is still missing important expectations: what result format to expect and what the CPF/CNPJ requirements are.

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 0% description coverage and the description does not compensate for this. It does not explain that a CPF or CNPJ must be supplied, whether only one is accepted, or what formats are expected. The parameter names are self-explanatory to a Brazilian user, but the description adds no operational guidance about them.

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 resource: Certidão Negativa de Feitos, and the specific action: consulta em fonte oficial. It also differentiates this real lookup tool from the account/marketplace/tooling sibling tools, and adds context about the official Brazilian sources.

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 useful usage context: the tool is hosted by the platform, requires no platform credentials, consumes prepaid credits, and accesses data available to the public. It does not explicitly name when not to use it, but the operational and financial context is clear enough for correct selection.

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, non-destructive, and idempotent behavior. The description adds the useful context that conversation data is used for reproduction, but does not disclose side effects like ticket creation or data transmission. It neither contradicts nor significantly deepens the annotation-provided safety profile.

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 concise sentences with zero filler. The purpose is front-loaded in the first sentence, and the second sentence provides a direct actionable instruction. Every word earns its place.

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, but the description does not mention expected return values or confirmation of submission. It covers the core purpose and one key input pattern, yet lacks guidance on parameter semantics and result handling, leaving gaps for a tool with sparse structured metadata.

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 adds meaning to the conversation parameter but calls it an 'array' while the schema types it as a string, which could mislead. The required 'message' parameter and optional 'context' parameter receive no explanation, leaving most parameters underspecified.

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 ('Report') and explicitly covers bug, missing feature, and feedback, making the tool's scope unmistakable. It clearly distinguishes from siblings like authenticate, connect, and marketplace, none of which handle user feedback.

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 clear context (“Report a bug, missing feature, or send feedback”) and instructs to include the conversation for reproduction. However, it does not explicitly state when not to use it or name alternatives, though no direct alternative exists among the siblings.

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, destructiveHint=false, so the safety profile is covered. Description adds no extra behavioral context (e.g., output format, network access), but given the trivial nature, this is acceptable. No contradiction.

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 single sentence, front-loaded, no fluff. Perfectly concise.

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 zero params, good annotations (readOnly, idempotent, non-destructive), and clear purpose, the description is complete. It might benefit from noting the output is version strings but the output schema is absent, so the agent can infer from 'show versions'. Still 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?

The tool has zero parameters and the schema has full coverage (100%), so the description doesn't need to explain parameters. The baseline is 4 for no params, and the description adds no extra param info, but that's fine.

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 the tool's function: show current MCP platform and adapter versions. Specific verb 'show' with explicit resource (versions). Differentiates from siblings like connect, authenticate, 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 when-to-use or exclusions, but the purpose is self-evident for a simple version query. With no parameters, usage guidance is minimal; it's implied that it's used when you need version info.

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, but the description adds valuable context about what information is returned (installed MCPs, status, accounts, catalog counts). This goes beyond the annotations and gives the agent a clear understanding of the tool's output.

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, front-loaded sentence that lists exactly what is returned without any fluff. It is 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?

With no output schema, the description carries the full burden of explaining return values. It enumerates the key pieces of information (MCPs, connection status, accounts, catalog tool counts), which is sufficient for a read-only state inspection tool. No additional details seem necessary.

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 schema already reflects that. Per rubric, the baseline is 4 for no parameters, and the description adds no need for parameter explanation since none exist.

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 with specific details: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it from siblings like authenticate, connect, or show_version, which serve different purposes.

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 the tool is for inspecting toolkit state, providing clear context for when to use it. However, it does not explicitly mention alternatives or when not to use it, which prevents a 5.

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