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

The description explicitly notes the data is not confidential ('não é dado sigiloso'), confirms it's the same data available to citizens, and addresses LGPD compliance responsibilities. It also discloses the payment model (prepaid credits) and hosting context. While annotations declare the operation read-only, the description adds significant context about data sensitivity, legal compliance, and usage costs beyond what annotations capture.

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 block of text providing substantial information, but it is not front-loaded with the most critical information first and covers multiple unrelated topics (data source, payment model, LGPD compliance) in one paragraph. A more structured approach with shorter sentences or bullets would improve scanability.

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 purpose, data source, legal compliance, and access requirements, which is comprehensive for a simple tool with a single parameter. It doesn't need to explain return values since there is no output schema, and the information about data ownership and legitimate purpose expectations adds valuable context beyond the basic query function.

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% coverage for the 'cnpj' parameter, meaning the description must compensate. The description implies the tool queries based on company identification but doesn't explicitly explain the CNPJ format, validation rules, or how to handle formatting. The description is about the data source and compliance, not the parameter itself, missing the opportunity to provide necessary format or usage details for the 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 clearly identifies the tool as querying ANVISA for national company operation status ('Funcionamento de Empresa Nacional'), specifying the official source ('consulta em fonte oficial') and data type. While it clearly states the resource and verb, it doesn't emphasize sibling differentiators because siblings like 'authenticate' or 'report_bug' are distinctly different tools, making the purpose strong but not perfectly scoped to distinguish between similar query tools.

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 mentions it's hosted on the platform, paid per query with prepaid credits, and that credentials are not required from the platform. However, it doesn't explicitly say when to use this tool over alternatives or when not to use it, leaving an implied usage context at best.

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