Devedores da União (PGFN)

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

Beyond annotations (idempotentHint=true), the description discloses permanent vs session-only behavior, what calling with no args does, and how the token is used. It adds context about the two login methods, though it doesn't mention failure modes or token validation.

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 three sentences and front-loaded with the main purpose. It contains some run-on phrasing but every sentence adds meaningful information. It is concise enough for its content.

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, the description covers the main use cases and login modes. It doesn't describe the return value, but no output schema exists and the steps are clear. It is complete for an authentication tool with one optional parameter.

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 only defines 'token' as a string with no description. The description fully explains that the token is a JWT to paste for session-only login, and clarifies that omitting it returns the login link. This compensates completely for the 0% schema 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 clearly states this is for authentication ('log in in the browser, copy the access token') and gives specific usage modes. It distinguishes itself from sibling tools by focusing on IDE agent login flow, though it doesn't explicitly name alternatives.

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?

Provides clear usage instructions: best practice (config header for permanent connection), session-only paste, or no-args to get link. It explains when to use each approach, but does not explicitly contrast with 'connect' or other sibling 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 already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so transparency is largely covered. The description adds valuable behavioral detail by specifying exact return states (authenticated:true with empty pending[] and connect_url when credentials are missing) that are not present in annotations, fully aligning with the 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?

The description is two concise sentences that front-load the primary purpose ('Returns connection status and URLs') and then add conditional behavior. Every clause contributes meaning, 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?

As a simple read-only status tool with no output schema, the description fairly completely explains the return values in the two key states. It could go deeper (e.g., describing the exact shape of pending[]), but for this complexity level, it covers the essential what and when sufficiently.

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 coverage is vacuously 100%. The description does not need to explain parameter semantics, and it doesn't, so it meets the baseline for a no-parameter tool. No points lost for lack of 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') and resource ('connection status and URLs'), and clearly distinguishes itself from siblings by explaining the authenticated/pending states. It also mentions the alternative 'authenticate' implicitly by describing when credentials are missing, making its purpose 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 clear context for when to use the tool—checking connection status and obtaining URLs when credentials are missing. It does not explicitly name alternatives or exclusions, but the conditional logic ('When all providers are connected', 'When credentials are missing') serves as implicit usage guidance, which is adequate for a status-checking 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 minimal annotations, the description discloses key behaviors: invoke works without installation, credential/payment failures return connect/checkout links, and writes require owner/admin. It also explains installed_in_toolkit vs installed_in_workspace flags. This is rich behavioral context that helps an agent anticipate outcomes.

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 highly structured, using explicit markers like 'Core flow:', 'KEY:', and a natural segregation of the marketplace and prompt-library features. Every sentence adds operational detail; there is no filler or repetition, and the most important information is 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 tool with 23 parameters, no output schema, and high complexity, the description covers all principal workflows, edge cases (connect/checkout links), permission requirements, and the separate prompt library. It even notes status flags and one-off vs permanent installation, making it complete enough to drive correct selection and invocation.

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 coverage, the description compensates well for the central `action` parameter by explaining each action's purpose. It also gives meaning to `mcp_id`, `tool_id`, and `arguments` through the invoke flow. However, many auxiliary parameters (e.g., `limit`, `query`, `prompt_title`, `cancel_reason`) are not described, leaving some guesswork for less common actions.

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 opens with a precise statement of purpose: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It then details the core search→describe→invoke flow, making the tool's role unmistakable. It also distinguishes the prompt-library sub-feature, so the full scope is 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 explicitly maps actions to use cases: search to discover, describe to inspect, invoke for one-off runs, install only for permanent additions, and list_tools for currently callable tools. It provides decision rules like 'prefer invoke for a single/occasional use' and states that write operations require owner/admin permissions.

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. The description adds context about public data access, LGPD responsibility, and the payment model (prepaid credit). These go beyond the annotations and help the agent understand the tool's non-technical constraints and data sensitivity.

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 (three sentences) and front-loaded with the primary purpose. Every sentence adds meaningful information: purpose, access/payment method, and data classification. No filler 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?

The tool has no output schema, and the description does not mention expected return values. Combined with the unclear parameter requirements (both CPF and CNPJ required, unexplained 'completo'), the agent lacks complete information. However, the core operation is simple, and the annotations cover safety aspects, making this adequate but clearly incomplete.

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 mentions 'CPF ou CNPJ' but the schema requires both Cpf and Cnpj, creating ambiguity about which input(s) to provide. The optional 'completo' parameter is not explained at all. Without details on formats or semantics, the agent is likely to misuse the 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 with a specific verb and resource: 'Verifica se uma pessoa ou empresa consta na Lista de Devedores da União (PGFN) a partir do CPF ou CNPJ.' This exactly defines the tool's function and differentiates it from unrelated sibling tools like authenticate 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 useful usage context: 'Hospedado pela plataforma, sem credenciais, pague por consulta com crédito pré-pago' explains operational prerequisites. It implies when to use this tool (for checking debtors) but does not explicitly mention when not to use or name alternative tools. Since siblings are generic, this clarity 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=false, destructiveHint=false, and idempotentHint=true. The description adds the behavioral requirement of including conversation for reproduction, which is useful. However, it does not disclose what side effects occur (e.g., sending data to developers) beyond what annotations imply.

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 that efficiently conveys the purpose and a key usage instruction. It is front-loaded with the verb 'Report' and contains no wasted words 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?

The tool is relatively simple with 3 parameters and no output schema. The description covers the main purpose and one usage detail, but it leaves parameter semantics largely to the schema (which has no descriptions) and does not mention any side effects or limitations. It is adequate but has clear gaps in parameter clarity and behavioral expectations.

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 for all parameters. It only explains the 'conversation' parameter (as a reproduction aid) but does not clarify 'message' or 'context'. Additionally, it refers to 'conversation array' while the schema types it as a string (JSON), which could mislead the agent.

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 with a specific verb ('Report') and resource ('a bug, missing feature, or send feedback'). It uniquely identifies this as a feedback/bug reporting tool, distinguishing it from all sibling tools which have different 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 explicitly tells the agent when to use this tool (to report a bug, missing feature, or feedback) and gives a concrete guideline to include the conversation array for reproduction. It does not explicitly mention alternatives or exclusions, but given the sibling tools are unrelated, this is sufficient context.

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 known. The description adds the specific scope ('platform and adapter versions') but does not disclose any further behavioral details such as authentication requirements or failure modes. This adds some value beyond annotations but not rich context.

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, front-loaded sentence that precisely states the tool's function. Every word earns its place with no 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 trivial read-only version tool, the description is nearly complete. It states exactly what information is shown, and the annotations cover safety. A lighter description of return format would push it to 5, but for an informational tool this is sufficient.

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 (100% coverage). Baseline for 0 params is 4, and the description offers no parameter-specific guidance because there are none to describe.

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 ('show') and identifies the exact resource ('current MCP platform and adapter versions'). This clearly distinguishes it from sibling tools like authenticate 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?

The description implies usage (when you need version info) but provides no explicit 'when to use' alternatives or exclusions. For a simple utility this is acceptable, but it does not name any alternate tools or clarify when not to use.

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, openWorldHint, idempotentHint, and destructiveHint, establishing a safe, non-mutating operation. The description adds valuable context about the specific state elements returned (installed MCPs, connection status, accounts, catalog counts), going beyond annotation basics 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, efficiently worded sentence that front-loads the core action ('Returns the current toolkit state') and then lists the specific information included. Every word contributes to understanding, 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 tool with no parameters and no output schema, the description fully specifies what the tool returns. Annotations cover the safety and behavioral constraints, and the description covers the content scope, making it entirely complete for an agent to invoke and interpret the result.

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 takes zero parameters, so the description bears no burden of explaining parameter semantics. The baseline for zero-parameter tools is 4, and the description adds value by describing what the tool outputs, making the schema coverage complete and the tool self-explanatory.

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 a well-defined resource ('current toolkit state'), detailing what aspects are covered: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinctively differentiates it from siblings like authenticate or connect by focusing on a comprehensive overview.

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 clearly implies a read-only status query use case, appropriate for inspecting the toolkit's current state. While it doesn't explicitly name alternatives or exclusions, the context is unmistakable and sufficient for an agent to choose this tool over connection- or authentication-oriented siblings.

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