MPT RN: Certidão Negativa de Feitos

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

Annotations indicate this is a mutating, idempotent operation with no destructive side effects. The description adds meaningful behavioral context beyond annotations, such as the two modes (permanent vs. session-only) and the outcome of calling with no args (generates a link). It does not explicitly state what happens when a token is provided (e.g., success/error messages), but it aligns with the annotations and provides sufficient operational 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 description is efficient—two sentences with no filler—but it is slightly dense and could benefit from clearer separation of the two usage modes. However, it is front-loaded with the core purpose and provides all necessary details 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 authentication tool with one optional parameter and no output schema, the description is complete. It covers both invocation patterns, explains the token's role, and situates the tool within the IDE-agent context. Given the low complexity, nothing essential 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 schema has a single 'token' property with no description and 0% schema coverage. The description fully compensates by explaining that 'token' is a JWT access token and illustrating how to use it ('call with { token: "<jwt>" }'), while also making clear that passing no args retrieves a login link. This goes beyond the schema to clarify the parameter's purpose and optionality.

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 what the tool does: it authenticates an IDE agent by logging in via browser and obtaining an access token. It specifies the resource (MCP.AI server) and the action (authenticate), and distinguishes it from sibling tools like 'connect' or 'marketplace' by its authentication-oriented 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 explicitly explains when to use this tool: it provides two usage modes—permanent configuration via a header or session-only authentication via token pasting. It also tells the agent when to call with no args (to get a login link) and when to pass a token, making the decision process clear without ambiguity.

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 establish readOnly, idempotent, and non-destructive behavior. The description adds valuable behavioral detail about exact return states: 'authenticated:true and empty pending[]' when connected, and 'connect_url for the toolkit and per-install URLs' when credentials are missing. 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 two sentences, front-loaded with the main purpose, and uses the second sentence for conditional detail. Every clause adds meaningful information about the return value, with no filler or redundant restating of the tool name.

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 status tool with strong annotations, the description is sufficiently complete. It explains the main return conditions (all connected vs. missing credentials) and what fields will be present. No output schema exists, so the description's job is to convey return behavior, which it does clearly.

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 is empty, so there is no parameter semantics to document. Per the baseline for 0-parameter tools, the description does not need to add parameter detail. It appropriately focuses on the result behavior instead.

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: 'Returns connection status and URLs.' It goes beyond a generic label by describing the two main conditional outcomes (authenticated state vs. missing credentials). It does not explicitly name a sibling alternative, but the content makes it evident this is the connection-status check among tools like authenticate and toolkit_info.

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 contextual scenarios—when all providers are connected vs. when credentials are missing—so an agent can infer when to call this tool for status and URLs. However, it does not explicitly say when NOT to use it or mention alternatives like authenticate, so guidance on tool selection 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?

Beyond the annotations, the description discloses key behaviors: invoke works even when the MCP is not installed, credential gaps return a connect link, empty wallets return a checkout link, and writes require workspace owner/admin. It also explains installed_in_toolkit vs installed_in_workspace flags and the prompt-library 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 densely packed with useful information and is front-loaded with the core marketplace purpose and flow. It is structured around the main action sequence and key caveats, though a single large paragraph makes scanning harder than bullet points would.

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 23-parameter, multi-action tool with no output schema, the description covers the major flows, permissions, auth/payment edge cases, and prompt-library behavior. It is not fully exhaustive — return shapes and several parameter details are missing — but it is remarkably complete for the tool's 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?

Schema description coverage is 0%, so the description must compensate. It explains the action enum and core params like mcp_id, tool_id, arguments, prompt_slug, and prompt_vars, but many parameters (limit, query, immediate, tier_slug, cancel_reason, request_details, report_context, prompt_targets, etc.) are left undocumented. The description adds meaning for the main flow but not for the full parameter surface.

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: an in-platform catalog of MCPs/tools and the mechanism to run them. It distinguishes itself from siblings by covering search, describe, invoke, install, billing, and prompt-library actions in one coherent statement.

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 guidance: use search to discover, describe to inspect, invoke for one-off runs, install only for permanent toolkit additions, and list_tools for currently callable tools. It also names alternatives like report_bug, request_mcp, and the prompt-library actions, making when-to-use 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 readOnlyHint, idempotentHint, and destructiveHint. The description adds valuable context beyond annotations: prepaid credit cost, no platform credentials needed, non-confidential data, and LGPD compliance. This enriches the agent's understanding of side effects and constraints.

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, beginning with the core purpose. Each sentence adds distinct information: purpose, hosting/payment, data nature, and legal responsibility. No redundant fluff is present, though a bit more structure could improve readability.

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 query tool with no output schema and two basic parameters, the description covers essential operational aspects like cost, authentication-free access, and legal obligations. However, it omits expected return format and parameter details, making it slightly incomplete but not severely lacking.

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 the description does not mention 'cpf' or 'cnpj' parameters at all. It fails to explain whether these are alternative identifiers, whether one is required, or how to use them, leaving a significant gap for a two-parameter tool.

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: 'consulta em fonte oficial' and names 'Certidão Negativa de Feitos' (Negative Certificate of Court Records). It specifically identifies Brazilian official sources, which distinguishes it from unrelated sibling tools like 'authenticate' and '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 usage by describing the query nature and payment requirement ('pague por consulta com crédito pré-pago'), but it does not explicitly state when to use this tool versus alternatives or provide exclusions. There is no direct comparison to sibling tools, so context is present but not explicit.

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 are present and consistent: readOnlyHint=false matches the write nature of reporting, and destructiveHint=false indicates no destructive action. The description adds value by mentioning that conversation data is used for reproduction, which hints at how the tool behaves with input data. No contradictions or missing critical behavioral disclaimers were 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 two sentences long, front-loads the purpose, and includes a valuable usage hint without any fluff. Every word earns its place, making it 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?

Given the tool's simplicity (3 flat string parameters, no output schema), the description provides basic context but leaves room for improvement. It covers the 'conversation' parameter's role but says nothing about expected behavior of 'context' or response/error handling. It is adequate but not exceptional for the tool's 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?

Schema coverage is 0%, so the description must compensate. It explicitly references the 'conversation' parameter and its purpose for reproduction, which is helpful. However, it does not clarify 'context' or 'message' parameters, leaving their meaning to inference. The added explanation partially bridges the coverage gap but is not comprehensive.

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: 'Report a bug, missing feature, or send feedback.' It uses a specific verb ('report') and resource (bug/feedback) and offers a practical hint about including the conversation array. This differentiates it from sibling tools like 'authenticate' or 'marketplace' which have distinct functions.

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 there's a bug, missing feature, or feedback) and provides a concrete usage tip ('Include the conversation array with recent messages for reproduction'). However, it doesn't explicitly state when not to use it or mention alternatives, though the context is clear enough given the sibling names.

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 this is a safe, non-mutating operation. The description adds the specific scope (platform and adapter versions) but doesn't disclose any additional behavioral traits like output format or potential errors. With annotations covering the safety profile, a 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, concise sentence that fully conveys the tool's purpose. There is zero waste, and it's front-loaded with the action verb. Perfectly sized for a simple tool.

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 (no parameters, no output schema, clear annotations), the description is complete enough. It tells the agent exactly what the tool does. The only minor gap is not describing the return format, but since there's no output schema and the tool is trivial, this is acceptable. The description fully compensates for the lack of structured output 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, and schema description coverage is 100% (vacuously). The description doesn't need to explain parameters since there are none. The baseline for 0 params is 4, and the description correctly implies no inputs are needed. No additional parameter semantics are 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 purpose: showing current MCP platform and adapter versions. It uses a specific verb ('Show') and resource ('MCP platform and adapter versions'), which distinguishes it from sibling tools like 'authenticate' or 'connect'. However, it doesn't explicitly differentiate from 'toolkit_info', which might also provide version information, so it's not a perfect 5.

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: call this tool when you need to know the current versions. It doesn't explicitly state when not to use it or mention alternatives, but given the simple nature of the tool and the sibling list, the context is clear enough. No exclusions or alternative guidance is provided, so it's adequate but not explicit.

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 destructiveHint=false, so the safety profile is established. The description adds meaningful behavioral context by specifying exactly what state is returned (installed MCPs, connection status, accounts, catalog counts), which is not present in the annotations. 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?

The description is a single, front-loaded sentence that covers all necessary details without redundancy or fluff. Every word contributes to explaining the tool's function.

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 simple no-parameter signature and clear informational output, the description fully covers what the tool does and what it returns. No output schema is present, but the enumeration of the return content is sufficient for an AI agent to understand the tool's capability.

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 coverage is 100% (vacuously). The baseline for 0 params is 4, and the description doesn't need to add parameter details. It correctly focuses on the output rather than inputs.

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 a specific verb ('Returns') and resource ('current toolkit state') with a clear enumeration of the returned data (installed MCPs, connection status, accounts, catalog tool counts). This clearly distinguishes it from sibling tools like authenticate or connect, which handle actions rather than reporting state.

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 by describing the informational nature of the tool, but it does not explicitly state when to use it over alternatives or provide exclusions. The sibling tool names hint at context, but the description itself lacks direct guidance.

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