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

Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint), the description adds critical behavioral context: the tool is hosted by the platform, requires no platform credentials, is paid with prepaid credits, returns non-confidential official data, and makes the client (not the platform) the LGPD controller. This substantially exceeds the annotations' coverage.

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 compact single paragraph that front-loads the tool's purpose and then adds meaningful context about official source, pricing model, and legal compliance. Every sentence contributes value, though the LGPD disclaimer could have been shortened; overall the structure is efficient and useful.

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 has three parameters, no output schema, and no parameter description, but it has strong behavioral context (credits, official source, legal roles). The main gap is the missing parameter semantics and the lack of any indication of return values. For a simple query tool, the current description is adequate but leaves some important operational details untouched.

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 property names (cpf, cnpj, nome) with string types and zero descriptive coverage. The description does not explain how these parameters are used, whether at least one is required, how they relate to CEAT, or any validation constraints. Although the names are self-explanatory, the description fails to compensate for the 0% schema coverage, leaving the agent without critical parameter 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 states the tool's function: consulting the CEAT (Certidão Eletrônica de Ações Trabalhistas) from TRT13 in an official source. It uses a specific verb 'consulta' and a specific resource, making it easy to distinguish from the sibling tools (authenticate, connect, marketplace, etc.).

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 usage context is implied by the domain: pay-per-query consultation of official labor court data. However, there is no explicit guidance about when to prefer this tool over alternatives, nor any when-not-to-use guidance. The description explains cost and data sensitivity but does not describe competing tools or selection criteria.

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