DAP Pronaf PJ

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

Annotations already indicate idempotent, non-read-only, non-destructive. The description adds context about permanent vs session-only login, and that no-args returns a login link. It doesn't contradict annotations and provides useful behavioral nuance beyond 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 paragraph of about 60 words, front-loaded with purpose and then explaining two usage options. Every clause adds value, though it could be structured with bullet points for clarity.

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 (one optional param, no output schema), and the description covers the main use cases. However, it doesn't describe the response for token-based login (e.g., success/error) or any post-auth state, leaving some gaps given no output schema.

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 input schema only defines an optional token string with no description (0% coverage). The description fully explains the token's meaning (JWT) and both usage states: with token for session login, without for link retrieval, compensating entirely for schema 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 clearly states this tool is for login/authentication, explaining the flow: browser login, copy token, and call with token or without. It identifies the target (MCP.AI for IDE agents) but doesn't explicitly contrast with sibling 'connect', so clear but not fully differentiated.

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 usage guidance: it recommends adding the token to server config for permanent connection, and describes session-only login via the token argument. It also explains when to call with no args (to get the link), covering both modes. However, it doesn't 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 readOnlyHint=true and idempotentHint=true, so safety is covered. The description adds valuable state-dependent behavior, explaining the different responses for connected and missing credentials, 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?

The description is two concise sentences, front-loaded with the main purpose. Every sentence adds useful detail about state-dependent behavior, with no unnecessary 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 simple status tool with no parameters and no output schema, the description covers the key states and outputs. However, it omits behavior for partial connectivity (some providers connected, some missing), leaving a minor gap in completeness.

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 baseline is 4. The description does not need to explain parameter semantics because there are none, and the schema coverage for parameters is trivially 100%.

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: 'Returns connection status and URLs.' It also details two distinct output states, distinguishing it from the sibling 'authenticate' tool by focusing on status rather than action.

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 this over alternatives. It mentions the behavior when providers are connected or credentials are missing, which gives some context, but lacks explicit 'use this when' or 'instead of' 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?

As annotations já indicam readOnly e idempotent, mas a descrição acrescenta que a consulta é hospedada sem credenciais, paga com crédito pré-pago, e acessa apenas dados públicos de fontes oficiais, o que é relevante para custo e privacidade. Também atribui responsabilidade LGPD ao cliente, um comportamento importante.

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 descrição é direta e front-loads o propósito, seguida de informações cruciais sobre autenticação, custo e natureza pública dos dados. Nenhuma sentença é desperdiçada, embora a frase sobre LGPD seja extensa.

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?

Para um tool simples, cobre propósito, credenciais, custo e sensibilidade dos dados. Porém, não esclarece o parâmetro 'completo' nem o formato da resposta, e não há schema de saída. A ausência de explicação do booleano é uma lacuna.

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?

A cobertura do schema é 0% e a descrição não explica os parâmetros. Apenas CNPJ é mencionado; 'completo' (booleano) não é descrito, deixando ambíguo seu efeito (ex.: retornar todos os dados). Isso é uma lacuna significativa.

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?

A descrição usa verbo específico 'Consulta' e recurso claro 'Declaração de Aptidão ao Pronaf (DAP) de uma pessoa jurídica', informando a entrada CNPJ. Diferencia-se claramente dos irmãos (authenticate, connect, etc.) que são operações genéricas da plataforma.

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?

O contexto é claro: consulta de DAP de PJ por CNPJ, sem credenciais, com pagamento por consulta e dados públicos. Não há exclusões explícitas nem alternativas mencionadas, mas a especificidade do recurso torna o uso inequívoco.

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 reveals key behaviors beyond the annotations: invoke runs tools even when not installed, writes require owner/admin, and credential/payment failures return connect/checkout links. This adds substantial context to the readOnlyHint=false and openWorldHint=true annotations without 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?

The description is a dense paragraph covering many facets without wasted words. It is front-loaded with the core purpose, but could be structured with bullets or sections for easier scanning; however, every sentence contributes value.

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 14 actions and 23 parameters, the description covers the main flows (search/describe/invoke, install/remove, prompt library) and important edge cases like auth and payment. It omits details on some actions (e.g., resume, report_bug) and return formats, but overall it is quite complete for such a complex 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?

With 0% schema description coverage, the description must explain parameters. It explains high-level actions and flow, but does not map specific parameter names (e.g., mcp_id, tool_id, prompt_title) to each action. The names are intuitive but not explicitly documented for all 23 params, leaving gaps for an agent to infer.

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' that catalogs and runs MCPs. It uses specific verbs like search, describe, install, invoke, and explains the core flow, distinguishing 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?

Explicit guidelines are provided: 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT', and describes when subscription actions apply. It also explains how to handle capability requests like 'find an MCP that does X', and contrasts with list_tools for immediate callables.

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 idempotent and non-destructive behavior. The description adds the guidance that the conversation array should contain recent messages for reproduction, which is useful context but does not disclose other behavioral traits like rate limits or response format. 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?

Two sentences with no wasted words. The first sentence states purpose, the second gives a specific usage hint.

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?

While the description covers the main purpose and key usage detail, it omits explanation of the 'context' parameter and does not indicate what happens after submission (not required due to no output schema). Overall, it is adequate but has gaps for full standalone use.

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 the 'conversation array' and implies the purpose of 'message' through the verb, but leaves 'context' unexplained. This partial coverage is insufficient for a 3-parameter tool with zero schema descriptions.

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 'Report a bug, missing feature, or send feedback,' specifying the verb and resource. This distinguishes it from sibling tools focused on authentication, marketplace, and 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?

The description implies when to use the tool (for reporting issues) and provides a concrete instruction to include the conversation array for reproduction. It does not explicitly exclude alternatives, but the context is clear given the 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, fully covering the tool's safety profile. The description adds no extra behavioral context beyond 'show versions,' which is adequate but does not enrich the disclosure further.

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 conveys the complete purpose with no wasted words. 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?

The tool is extremely simple, and the annotations plus description together fully characterize its behavior. The return value (version information) is obvious from the verb 'show,' and no additional context is needed.

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 input schema is empty with 100% coverage. The description correctly implies no inputs are needed, and the baseline for zero-parameter tools is 4.

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 a precise resource ('current MCP platform and adapter versions'), clearly distinguishing it from sibling tools like authenticate, report_bug, or marketplace. It unambiguously states what the tool does.

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?

While it does not mention alternatives or exclusions, the purpose of displaying version information is self-explanatory and distinct from the sibling tools. Clear context is provided for when to use this tool, though no explicit when-not-to-use guidance is given.

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, so the safety profile is covered. The description adds valuable behavioral context by specifying the content of the return value (installed MCPs, status, accounts, catalog tool count), which is especially useful because there is no output schema.

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 states the verb first and lists the return contents in a compact, readable list. 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 simple, read-only informational tool with no parameters and no output schema, the description fully covers what the tool returns and the nature of the operation. It provides sufficient context for an agent to know what to expect and when to call it, even without additional structured schemas.

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 schema coverage is effectively 100%. The description need not explain parameters, and the baseline for a no-parameter tool is 4. 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 uses a specific verb ('Returns') and precisely states the resource ('current toolkit state') along with the exact information included (installed MCPs, connection status, accounts, catalog tool count). This clearly distinguishes it from sibling tools like authenticate or connect, which are action-oriented.

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 the tool is for checking toolkit state without touching anything, but it does not explicitly state when to use it instead of other tools. However, given the read-only nature and distinct purpose, the context is clear enough for an agent to select it appropriately.

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