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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, but the description goes well beyond that by disclosing payment requirements (prepaid credit), authentication (no platform credentials), data classification (not confidential), and legal responsibilities (LGPD). This gives the agent critical operational and compliance information not captured in 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 reasonably concise and front-loaded with the core purpose, followed by payment and legal details. While the LGPD clause adds length, it is relevant to data handling. The structure is clear, with each sentence adding distinct information, but it could be slightly tightened without losing essential context.

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 schema and lack of output schema, the description provides useful context about the official source, cost, and legal obligations, but it omits guidance on how to combine parameters (e.g., CPF vs CNPJ) and what type of response to expect. The tool is not overly complex, but the missing parameter details and return value information leave the description incomplete for smooth 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?

The input schema has four parameters (cpf, cnpj, data_nascimento, data_abertura_empresa) with 0% description coverage, and the tool description provides no explanation of these parameters. The description does not compensate for the lack of schema descriptions, leaving the agent to infer parameter usage solely from their names. This is a significant gap in guidance.

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 a query tool for the Banco Central do Brasil's 'Valores a Receber' program, using the specific verb 'consulta' and specifying the official source. It distinguishes itself from the platform-level sibling tools (authenticate, connect, etc.) by focusing on a concrete Brazilian government data service.

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 usage context: it is a paid consultation using prepaid credits, requiring no platform credentials, and it queries official Brazilian sources. It does not explicitly mention when not to use it or name alternatives, but the context is clear enough that the agent can decide to use it for fetching BCB 'Valores a Receber' data. No exclusions are needed given that sibling tools are unrelated.

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