Certidão TRF

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

Annotations already provide idempotentHint=true and readOnlyHint=false. The description adds behavioral context by noting the permanent (non-expiring) nature of config-based auth versus the session-only nature of token-based auth, and it describes the two invocation modes (with/without token). It does not detail the return value or side effects, but the annotations cover 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 three sentences with no fluff. Each sentence adds valuable information: context, best practice for permanent auth, and the alternative for session-only auth. It is slightly dense but well-structured and front-loaded with the tool's purpose.

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 (one optional parameter, no output schema), the description covers the necessary aspects: the login flow, the two authentication modes, and the token format. It does not describe the response or confirm success, but this is not critical for a one-parameter auth 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?

The schema has only one optional string 'token' with no description (0% coverage). The description fully explains the parameter: it expects a JWT access token, and it specifies how to obtain and use it ('copy the access token', 'paste it here', 'call with { token: "<jwt>" }'). This provides complete semantic meaning beyond the bare 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: authenticate by logging in via browser, copying an access token, and then either adding it to the server config for a permanent connection or passing it as a JWT for session-only login. It distinguishes itself by explaining the exact authentication flow, unlike the generic sibling '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 explicit usage guidance: 'Best: add it to this server's config... for a permanent, non-expiring connection. Or paste it here for a session-only login... call with { token: "<jwt>" }... or with no args to get the link.' This clarifies when to use the token argument versus no arguments. However, it does not explicitly mention alternative tools or when not to use this 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 declare read-only and idempotent behavior. The description adds context about the output states: authenticated:true with empty pending[] when connected, and connect_url when credentials are missing. This goes beyond the annotations and clarifies the tool's conditional 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 two sentences long, front-loaded with the main purpose, and every clause provides meaningful detail. There is 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 zero parameters and no output schema, the description covers the two primary usage states (all connected vs credentials missing). A minor gap is the lack of detail about partial connection states, but for a simple status tool this is 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, so the schema fully covers parameter semantics. The description adds no parameter information, but the baseline of 4 is appropriate for a no-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 returns connection status and URLs, with specific output conditions for connected and missing credentials. This distinguishes it from sibling tools like authenticate, which performs authentication rather than checking status.

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: to check if providers are connected and retrieve connect URLs when credentials are missing. It uses conditionals ('when all providers are connected' vs 'when credentials are missing') to guide usage, though it does not explicitly name alternatives or exclusion criteria.

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 richly discloses behavioral nuances beyond the annotations, such as 'invoke works even when the MCP is NOT installed — it runs the tool pontualmente (one-off), without adding the MCP to the toolkit.' It also explains auth and payment fallbacks: 'invoke returns a connect link; if it is paid and the wallet is empty, invoke returns a checkout/top-up link (the user opens it, then you retry).' Permission requirements are also stated: 'Writes ... require workspace owner/admin.' This is comprehensive 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 dense paragraph, but it is information-dense and front-loaded with the primary purpose. Each sentence earns its place, covering search, describe, invoke, install, billing, permissions, and the prompt library. While it could benefit from bullet points or headings for readability, the content is efficient for the tool's complexity.

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 no output schema, the description explains key return behaviors for invoke (connect/checkout links) and publish_prompt (shareable link), but it does not explicitly describe the return format for search, describe, list_tools, or other actions. Still, the operational context, including auth, payments, and permission requirements, is thoroughly covered, making the tool actionable without needing additional schema documentation.

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, the description must compensate, and it does significantly by explaining action-specific parameters like 'mcp_id', 'tool_id', 'arguments', and the prompt-related fields ('prompt_body', 'prompt_vars', etc.). However, with 23 parameters, some remain unexplained (e.g., 'immediate', 'tier_slug', 'conversation', 'cancel_reason'), leaving minor gaps. The description covers the core workflow but not every parameter.

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 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them,' which clearly states the tool's core purpose as a hub for discovering and executing MCPs. It also distinguishes itself from sibling tools by covering both MCP management and the prompt library, making its role unmistakable.

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 outlines when to use each action via the 'Core flow' sequence: 'action=search discovers MCPs by intent → describe returns one MCP's full profile → invoke RUNS that tool.' It also provides direct comparison and preference guidance: 'Use install only to make an MCP PERMANENT in the active toolkit... prefer invoke for a single/occasional use.' This is exemplary usage 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 indicate readOnlyHint=false and destructiveHint=false, so the description does not need to restate those. It adds context about including the conversation array for reproduction, which is a behavioral nuance. However, it does not disclose other side effects like data transmission or ticket creation, but the annotation coverage reasonably covers 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 a single, focused sentence that front-loads the purpose and then gives a specific usage instruction. No unnecessary words or repetition of schema details.

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 simple with no output schema, and the description covers the core action and an important input guideline. It doesn't mention expected response or error handling, but for a bug-report tool, the essential context is present. The annotation hints (idempotent, not destructive) further round out the picture.

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 explicitly explains the conversation parameter's purpose ('Include the conversation array with recent messages for reproduction') and implicitly clarifies message as the report content. However, the 'context' parameter remains unexplained, leaving a gap in parameter understanding.

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: 'Report a bug, missing feature, or send feedback.' It distinguishes itself from all sibling tools, which are unrelated (authenticate, connect, marketplace, etc.), and includes an actionable instruction about including the conversation array.

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 (bug reports, feature requests, feedback) and gives a specific guideline: include the conversation array for reproduction. It does not explicitly mention alternative tools or exclusions, but since siblings are unrelated, the intended usage is unambiguous.

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 disclose readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds the scope of 'platform and adapter versions' but does not describe output format or further behavior, which is acceptable given 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 concise sentence that is front-loaded with the action and resource. Every word adds value and there is 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?

The tool is very simple: no parameters, read-only, idempotent, and non-destructive. The description sufficiently conveys its purpose and scope for an agent to select and invoke it without additional 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 tool has zero parameters and the schema has 100% coverage, so the schema is complete. The description correctly implies no parameters are needed, aligning with the baseline for parameterless tools.

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 shows current MCP platform and adapter versions, with a specific verb and resource. It does not explicitly distinguish from the sibling tool toolkit_info, which could overlap in 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?

No usage guidance is provided. The description states what the tool does but does not indicate when to use it versus alternatives like toolkit_info or other informational 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 and idempotentHint=true, covering the safety profile. The description adds the specific content of the return value (MCPs, connection status, accounts, tool counts), which goes beyond the structured annotations and gives the agent useful expectations.

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 states the output verb and resource, followed by a compact list of included details. Every word contributes value with no redundancy or jargon.

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 tool with no output schema, the description fully conveys the return contents and purpose. It adequately covers all necessary context for an agent to select and invoke it 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 the schema coverage is 100%. With no parameters to document, the baseline is 4, and the description correctly focuses on what the tool returns 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 specifies the exact verb 'Returns' and resource 'current toolkit state', then enumerates the contained information (installed MCPs, connection status, accounts, catalog tool counts). This clearly distinguishes it 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?

The purpose implies when to use: whenever the agent needs an overview of the toolkit's installed MCPs and their status. It does not explicitly mention alternatives or exclusions, but the context is clear enough given the sibling tools are for actions rather than state inspection.

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 (readOnly, idempotent, non-destructive), the description adds valuable behavioral context: no authentication needed, payment-per-query with prepaid credits, data is public access from official sources, and LGPD compliance responsibilities for the client. 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 four sentences long, each conveying essential information: the core function, platform/cost details, data classification, and legal responsibility. It is front-loaded with the main purpose and contains no redundant or filler 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?

The description covers the purpose, cost, access rights, and legal context, but it omits the return format (e.g., PDF, JSON) and fails to resolve the CPF/CNPJ required-parameter ambiguity. Given the lack of output schema and parameter descriptions, these are notable gaps for a tool with five parameters.

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, the description must compensate. It mentions CPF/CNPJ, region, and certificate types, but it does not explain the values for 'Tipo', the format of CPF/CNPJ, or the 'completo' boolean. Notably, it says 'CPF ou CNPJ' suggesting either/or, while the schema requires both, leaving ambiguity.

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: issuing civil, electoral, or criminal certificates from the Regional Federal Court using CPF/CNPJ and region. The verb 'emite' is specific, the resource is precise, and it distinguishes itself from the generic sibling utilities.

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 on when to use the tool: to query public official records for certificates. It also explains practical requirements (paid via prepaid credits, no credentials) and clarifies that it is not for private/confidential data. However, it does not explicitly compare against alternative tools, though no direct alternatives are present among siblings.

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