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

The description adds meaningful context beyond the readOnlyHint annotation by clarifying the nature of the data (public, not confidential), the payment model, and the client's LGPD responsibilities. This reassures the agent of safety and legality. It doesn't contradict the readOnlyHint or idempotentHint 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 packed with useful information: purpose, hosting, payment model, data source, legal basis, and compliance note. Every sentence contributes value. It is front-loaded with the most critical information.

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 parameter set (4 scalars, no enums) and no output schema, the description covers the operational context well by explaining the payment model and the data's public nature. It could improve by hinting at response format or error conditions, but it is complete for a straightforward query tool.

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%, so the description should compensate, but it doesn't explain any of the four parameters. However, the parameters themselves (cpf, cnpj, data_pedido, numero_pedido) are self-explanatory from their names, and the schema enforces the required ones. This is a case where the schema structure does most of the work, but the description could still add value by indicating, for example, that cpf/cnpj are mutually exclusive.

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 specifies the tool's purpose (Conferência de Certidão, consulta em fonte oficial) and names the resource (Tribunal TJMS). It could be clearer by matching the exact tool name, but it effectively communicates a verification query for official court records. It doesn't explicitly distinguish from sibling tools, which are unrelated.

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 indicates this is a pay-per-query service against official Brazilian sources, implying when to use it (need for official certificate validation). It does not explicitly list alternatives, but the unique context of pre-paid credits serves as a clear usage signal. It lacks explicit when-not-to-use guidance, which is the only gap.

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