DAP Pronaf PF

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

Annotations indicate idempotentHint=true and readOnlyHint=false. The description adds context about non-expiring vs session-only login and that calling with no args returns a link, which supplements the annotations. It does not contradict 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 it is front-loaded with the core purpose and includes necessary details. It could be split into clearer steps, but every sentence carries useful information, making it reasonably 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 one optional parameter and no output schema, the description sufficiently explains input behavior and expected outcomes (link or session login). It also mentions a permanent configuration option, which adds contextual completeness. Minor gaps: no explicit mention of error cases or response format.

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 'token' string with no description (0% schema coverage). The description compensates by explaining that token is a JWT pasted by the user for session login, and that omitting it yields a login link. This adds essential meaning 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 users for MCP.AI by either providing a login link or accepting a JWT token for session login. It distinguishes itself from siblings by explicitly mentioning IDE agents and authentication flow.

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 guidance on how to use the tool: call with no args to get a link, or call with a token for session-only login. It also recommends a permanent configuration via header, though it does not explicitly contrast with alternative tools like 'connect'.

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 readOnly, idempotent, and non-destructive hints. The description adds valuable scenario-specific output details, such as the 'authenticated:true' and 'pending[]' fields, and the behavior when credentials are missing, which goes 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?

Two sentences, no wasted words, the key information is front-loaded with the purpose stated immediately.

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 read-only status tool with no output schema, the description covers the main states (connected, missing credentials) sufficiently. It is complete enough for an agent to know what to expect.

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, and schema coverage is trivially complete. The description correctly does not mention parameters, and the baseline for 0 params is 4 since no compensation is 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 returns connection status and URLs, using the specific verb 'Returns.' It distinguishes itself from siblings like 'authenticate' by focusing on status rather than auth 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?

The description implies usage for checking connection status but does not explicitly state when to use it over alternatives. It describes conditional scenarios (all connected vs. credentials missing) but gives no direct comparison to 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 readOnly, idempotent, and non-destructive hints. The description adds valuable context beyond these: it is hosted, requires no credentials, involves prepaid credit, and accesses public information only. It also clarifies LGPD responsibilities, which is important for compliance-sensitive tools. 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 composed of three sentences and is relatively concise. The first sentence front-loads the core purpose, while the subsequent sentences provide cost, access, and legal context. The LGPD clause adds legal nuance but could be considered slightly verbose; nevertheless, it is relevant for a data-querying 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?

The tool is simple, but the description leaves gaps. It does not explain the meaning of the 'completo' parameter, and since there is no output schema, it also does not describe the return format. While annotations cover safety, the missing parameter detail and lack of response indication make it 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?

The schema has no descriptions (0% coverage), so the description carries the burden. It names the required parameters (CPF and DataNascimento) and explains their role in the query, but it completely omits the optional 'completo' parameter, leaving its meaning unknown. Partial compensation for the schema gap, but not complete.

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 action ('Consulta a Declaração de Aptidão ao Pronaf (DAP)'), the target resource ('de uma pessoa física'), and the required inputs ('CPF e data de nascimento'). This is specific and distinguishes it from the sibling tools, which are focused on authentication, marketplace, and system 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 important usage context: hosted platform, no credentials, prepaid credit per query. This tells the user how to invoke it and what to expect in terms of access and cost. It does not explicitly mention when not to use it or alternatives, but the sibling tools are unrelated, so no exclusion is needed.

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 critical behavioral details beyond annotations: writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin; invoke runs tools one-off without installing or bloating the toolkit; credential/payment issues return connect/checkout links. This is rich, non-obvious 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?

The description is long but every sentence earns its place. It uses a clear narrative flow with arrows and semicolons to pack dense information, and the length is justified by the tool's 14 actions and 23 parameters. There is no fluff 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?

For a tool with 23 optional parameters, 14 actions, and no output schema, the description is remarkably thorough: it covers the core flows, one-off invocation behavior, permanent installation trade-offs, billing/auth failure modes, and the separate prompt library. Minor gaps include missing explanations for 'resume', 'immediate', and cancel_reason enums, leaving some edge cases to infer.

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 compensates by explaining the roles of key parameters (action, mcp_id, tool_id, arguments, prompt fields) through the workflow narrative. However, it leaves many parameters (immediate, tier_slug, resume, cancel_reason, prompt_targets) undocumented, which is a notable gap for such a complex 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 is the official mcp.ai marketplace, serving as both the catalog of MCPs/tools and the way to run them. It enumerates distinct actions (search, describe, invoke, install, subscribe, etc.) and distinguishes itself from siblings by also covering the prompt library.

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 a explicit core workflow (action=search → describe → invoke), contrasts invoke vs install ('prefer invoke for a single/occasional use'), and clarifies when to use list_tools, subscribe/cancel, report_bug, request_mcp, and prompt library functions. It also covers billing/auth edge cases with instructions to retry after the user acts.

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 provide idempotentHint=true, readOnlyHint=false, and destructiveHint=false. The description adds valuable context by specifying the types of reports (bug, missing feature, feedback) and instructing to include the conversation array for reproduction. No contradictions with annotations are present.

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 with no wasted words. The action is front-loaded, and the extra instruction about the conversation array is directly relevant. It is efficiently structured and easy to parse.

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 no output schema, the description covers the main purpose and a key parameter. However, there is a gap: the schema defines 'conversation' as a string while the description calls it an 'array', which could lead to incorrect invocation. It also does not mention expected responses or error scenarios, leaving the description slightly 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 explains the 'conversation' parameter by mentioning the conversation array, but it does not clarify the meaning of 'message' or 'context' beyond general inference. The 'message' is implied as the report text, but 'context' remains unexplained, making the compensation only partial.

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 a bug, missing feature, or send feedback.' This distinguishes it from sibling tools like authenticate, marketplace, and show_version, which serve entirely different functions. The action and resource are 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 implies when to use the tool (when the user wants to report an issue or provide feedback) and provides context by mentioning reproduction with the conversation array. However, it does not explicitly state when not to use it or mention alternatives, so it falls short of a full 5.

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, covering the safety profile. The description adds that it shows platform and adapter versions, but does not detail output format or potential error behavior, nor is it necessary given 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 sentence, front-loaded with the verb and focus, with no unnecessary words. It is 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?

The tool is very simple, annotations are strong, and there is no output schema. The description states the core function adequately, though it does not explicitly mention return format; for a version check, this is sufficiently complete.

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 parameters, so there is no need for parameter documentation. Baseline for 0 params is 4, and the description does not need to compensate.

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 and resource: 'Show the current MCP platform and adapter versions.' It clearly distinguishes from siblings like authenticate/connect, which are about actions, not version 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?

No explicit when-to-use or when-not-to-use guidance is given, nor are alternatives mentioned. The purpose is self-evident, implying use when version information is needed, but the description does not explicitly differentiate from 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, idempotentHint, and destructiveHint. The description adds valuable behavioral information by enumerating exactly what the tool returns (installed MCPs, their statuses, accounts, and tool counts), which 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 a single, well-structured sentence that efficiently conveys all key information without any filler or redundancy. It is front-loaded with the main action ('Returns the current toolkit state') followed by specific 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?

For a simple, zero-parameter, read-only status tool with no output schema, the description fully covers what the agent can expect: installed MCPs, connection status, connected accounts, and catalog tool counts. No additional return format or behavior is 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 schema description coverage is 100%. With no parameters to document, the baseline of 4 is appropriate; the description does not need to add parameter details.

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, listing specific details (installed MCPs, connection status, accounts, catalog tool counts). This distinguishes it from siblings like connect or authenticate, which perform actions rather than report 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 makes clear the tool is for inspecting the current toolkit state, but it does not explicitly mention when to use it versus alternatives or any prerequisites. The context is transparent, and no exclusions are needed, so this gets a 4.

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