SEFAZ MG: Débitos de IPVA, 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 |
|---|---|---|---|
| cpf | No | ||
| cnpj | No | ||
| 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?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false. The description adds valuable behavioral context beyond annotations: no platform credentials required, prepaid credit pay-per-query, official/non-confidential data source, and LGPD responsibility. It does not mention rate limits or response details, but the annotation coverage lowers the bar.
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 main purpose is front-loaded in the first sentence. The subsequent sentences add relevant context about hosting, payment, and legal compliance, though the LGPD statement is slightly boilerplate-heavy. The description is compact and not redundant.
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 source, payment, and data-privacy context well, but it does not describe what the response contains (e.g., debt amounts, due dates) nor the parameter semantics. Since there is no output schema, the description should provide more detail about expected results, making it incomplete for a paid query tool.
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 description does not explain the role of renavam, cpf, or cnpj, nor the required/optional relationships beyond what the schema states. The parameter names are self-evident, but the description fails to compensate for the missing schema documentation.
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's verb and resource: 'consulta' for 'Débitos de IPVA' via 'SEFAZ MG'. It also distinguishes the tool from the generic sibling tools by naming the specific official Brazilian 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 clear operational context: the query is against an official source, the same data available to citizens, and the client is responsible for legitimate LGPD use. It does not explicitly mention alternatives or exclusions, but the context is sufficient for an agent to decide when this tool applies.
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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