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

Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds substantial behavioral context beyond this: it clarifies hosting, the absence of credential requirements, the pay-per-query prepaid model, that data equals what's publicly available to citizens, and LGPD controller responsibility. This enriches the agent's understanding of side effects, trust, and legal constraints without needing the 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 fits into a single run-on sentence but remains compact, packing hosting, credentials, payment, data source, and LGPD into roughly 50 words. It's not structured with bullets or separate sentences, which slightly harms scannability, but every clause carries meaningful information, keeping it appropriately concise.

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 there is no output schema and zero parameter documentation, the description needed to explain the operational contract—such as how to structure a query, what response to expect, or error behavior—but instead focuses on legal and business disclaimers. It's functionally incomplete for an agent to invoke successfully without prior knowledge.

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?

With a schema description coverage of 0%, the description should have compensated for the three parameters (cpf, cnpj, rntrc), but it provides zero explanation of their meanings, formats, or optionality. The agent is left guessing whether any combination is required or how the parameters interact, a critical gap for a data-lookup tool.

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 uses the verb 'consulta' (query) and specifies the resource as 'Transportes' from official Brazilian sources, making it clear this is a read-only data lookup tool. It distinguishes itself from generic siblings like 'authenticate' and 'marketplace' by being the only data-query tool, and it clearly states the scope ('fonte oficial').

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 provides implicit guidance: it mentions the tool queries official sources and is prepaid with platform credits, implying use cases around compliance and legitimate data access. However, it never explicitly states when to use this over alternatives, names no alternative tools, and offers no exclusions or prerequisites beyond the absence of platform credentials.

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