consult_cnpj

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

With no annotations provided, the description carries the full burden. It discloses the data source (BrasilAPI/Receita Federal) and the returned fields, but does not mention error handling for invalid CNPJs, authentication requirements, rate limits, or any auxiliary behavior. This is adequate for a straightforward read-only lookup but leaves some operational unknowns.

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 compact and well-organized with a one-line purpose, an Args section, and a Returns section. Every line contributes essential information, and the key purpose statement is front-loaded. No wasted words.

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 single-parameter read-only tool, the description covers the essentials: the data source, input format, and the return contents including Razão Social, Sócios (QSA), Capital Social, Endereço, and Contatos. Minor gaps like handling of invalid CNPJs and explicit sibling differentiation are absent, but overall the agent has enough context to call the tool correctly.

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 provides only the parameter name 'cnpj' with no description (0% schema coverage). The description compensates fully by explaining the accepted format and giving two concrete examples: '00.000.000/0001-91' and '00000000000191'. This is exactly the semantic detail an agent needs.

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 opens with a specific verb and resource: 'Consulta dados oficiais de uma empresa brasileira na Receita Federal (BrasilAPI)'. This precisely identifies the tool's function and scope, and inherently distinguishes it from the sibling tools (scrape_website, hunt_person, etc.) which target different tasks.

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 establishes the use case: retrieving official Brazilian company data from a CNPJ. It does not explicitly name alternative tools or exclusion conditions, but the unique CNPJ-focused purpose makes the intended context unmistakable, so an agent can infer when to select this tool.

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