INMETRO: Cronotacógrafo, 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 | No | ||
| chassi | No |
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, idempotentHint, and destructiveHint false, but the description adds significant behavioral context beyond that: it is a paid service (prepaid credit), requires no platform credentials, returns non-confidential public data, and imposes LGPD compliance duties on the client. This provides operational and legal transparency not contained in 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 concise and well-structured. It opens with the core purpose, then provides payment, credential, and legal details in a single paragraph. Every sentence carries meaningful information without any redundancy or filler.
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, data source, payment model, and legal aspects, which are useful contextual details. However, it omits parameter usage guidance and does not describe the output format for the query, which is important for a tool without an output schema. The absence of parameter semantics makes the description incomplete for practical 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?
The schema has 0% description coverage for the parameters 'placa' and 'chassi', and the description does not mention or explain them at all. Given the low schema coverage, the description must compensate, but it fails to clarify whether these are optional, required, or how they relate to the query. This is a critical gap.
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 the tool performs a consultation (consulta) on official INMETRO tachograph data via an official source. The verb 'consulta' and the resource 'INMETRO: Cronotacógrafo' are specific, and the tool is distinct from sibling platform tools like 'authenticate' or 'marketplace'.
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 implies when to use the tool (for querying official Brazilian data) and provides important context such as prepaid credit, no platform credentials, and LGPD responsibilities. However, it lacks explicit 'when not to use' instructions or named alternatives, so it falls short of full usage guidance.
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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