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

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds value beyond annotations by disclosing the payment model, the official-source nature, that the data is citizen-accessible rather than confidential, and the LGPD data-controller responsibility. It does not contradict 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 is compact and front-loaded with the core purpose. The legal and payment notes are relevant to safe use, though some wording is slightly redundant. Overall, it is appropriately sized for the high-level content it conveys.

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?

This is a complex tool with 34 parameters, 13 required, no output schema, and no parameter descriptions. The description covers purpose and legal framing but omits essential invocation details such as what each required field means, how to format inputs, and what result the agent should expect. It is not complete enough for reliable selection and invocation.

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%, and the tool has 34 string parameters with no per-parameter documentation. The description mentions no parameter meanings, required fields, formats, or relationships. Since the schema itself provides only names like 'a3', 'chassi', and 'tipo_restricao', the description completely fails to help the agent invoke the tool correctly.

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 operation as a consultation ('consulta') against a specific official Brazilian source for first-time vehicle licensing ('Primeiro Emplacamento'). It also differentiates the tool from generic sibling tools like authenticate, connect, and marketplace by naming the exact domain and data source.

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 useful context about when this tool is relevant: official-source consultation for first vehicle registration, with no platform credentials needed and prepaid per-query billing. It does not explicitly name excluded cases or alternative tools, but the sibling set is general platform tooling, so the guidance is reasonably clear.

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