DETRAN AL: Veículo, consulta em fonte oficial. Hospedado pela plataforma, sem credenciais da plataforma, pague por consulta com crédito pré-pago. Consulta informação de fontes e órgãos oficiais brasileiros (a mesma disponível ao cidadão), não é dado sigiloso. O cliente é o controlador dos dados e responde pela finalidade legítima (LGPD).
| Name | Required | Description | Default |
|---|---|---|---|
| placa | Yes | ||
| renavam | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (read-only, idempotent, non-destructive), the description discloses additional behavioral traits: it is hosted by the platform, requires no platform credentials, incurs costs via prepaid credits, queries only non-confidential official data, and mandates LGPD compliance. This adds meaningful context about the tool's operational behavior.
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 somewhat verbose and repetitive, repeating the idea of querying official sources twice. While it is not excessively long, the structure could be tightened by removing redundancy and front-loading the core action more effectively.
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 description covers the tool's purpose, payment mechanism, and legal aspects, but it lacks details about the expected output or response format (since no output schema is provided). It also does not mention any preconditions or error scenarios, leaving some gaps in the operational context.
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 lists 'placa' and 'renavam' with no descriptions, and the tool description does not elaborate on these parameters. The description only mentions 'vehicle' generally, leaving the meaning and expected format of the parameters unexplained. This fails to compensate for the low schema coverage.
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 that this tool performs a vehicle query from an official Brazilian source (DETRAN AL). It explicitly mentions 'Veículo, consulta em fonte oficial' and distinguishes itself from generic platform tools like authenticate or connect.
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 does not provide guidance on when to use this tool versus alternatives. It mentions prepaid credits and lack of credentials, but there is no explicit indication of the appropriate use cases or scenarios where this tool should be preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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