DETRAN RJ: 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 |
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?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable operational context beyond these: 'sem credenciais da plataforma' (no platform credentials needed), 'pague por consulta com crédito pré-pago' (prepaid payment per query), and data-handling responsibility under LGPD. No contradiction with 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 front-loaded with the core purpose, but it includes redundant phrasing about official sources and a legal LGPD disclaimer that adds length without directly aiding tool invocation. It is still relatively compact, but not every sentence earns its place.
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?
With no output schema and no return-value description, the tool lacks information about what the response contains (e.g., vehicle model, status, fines). It adequately covers payment and credentials but omits plate format, output structure, and usage constraints. For a one-parameter tool, it is adequate but has clear gaps.
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 has one required string parameter 'placa' but no descriptions (0% coverage). The description never mentions 'placa' nor provides format guidance, such as expected plate format or normalization. The parameter name is somewhat self-explanatory, but the description does not compensate for the missing schema detail.
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 tool as a DETRAN RJ vehicle consultation from an official source ('Veículo, consulta em fonte oficial') and states it queries information from official Brazilian agencies. It is easily distinguishable from generic sibling tools like authenticate and marketplace, though it does not specify exactly which vehicle attributes are returned.
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—official source, no platform credentials, prepaid credit per query, and LGPD responsibility—but does not explicitly state when to use this tool versus alternatives. There are no exclusions or direct references to sibling lookup tools, so usage guidance is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.