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

The description goes beyond the annotations (readOnlyHint, idempotentHint, destructiveHint) by explaining payment model (pague por consulta com crédito pré-pago), that it uses official sources with no platform credentials, no confidential data, and LGPD compliance. This adds valuable behavioral context about authentication and data handling that is not inferable from 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 stays reasonably concise. It conveys the core purpose, payment model, data source, and legal note about LGPD in about 40 words. No redundant sentences, though some legal info (LGPD) might be secondary; it's still relevant for compliance. It is front-loaded with the key 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?

With 3 parameters and no output schema, the description should explain more about expected inputs and outputs. It explains the source, payment, and data privacy, but doesn't mention how to provide CPF/CNPJ/RENAVAM formats, whether all are required, or what the response looks like. Given the lack of parameter descriptions and output schema, this is a notable gap.

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% – the properties have no descriptions. The description provides no elaboration on the parameters (cpf, cnpj, renavam) beyond their names, which are self-explanatory but do not specify formats (e.g., with/without punctuation), which identifier to use, or if they are alternative or combined. The description does not compensate for the lack of schema documentation.

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 consulting 'Dívida Ativa' from the Rio de Janeiro State Attorney General's office. It specifies the action (consulta), the resource (Dívida Ativa), and the source (oficial). It is unmistakably distinct from the unrelated sibling tools (authenticate, connect, etc.), 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 does not explicitly mention alternative tools or when to avoid using this one. However, it clearly sets context: it's for consulting official public records, implying it should be used when such data is needed. There is no exclusionary guidance, but the purpose is so specific that usage is implied. This is adequate but not explicit.

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