SEFAZ PR: Dívida Ativa, 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 |
|---|---|---|---|
| ano | 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?
Annotations already state readOnlyHint=true and idempotentHint=true, but the description adds valuable context: payment model ('pague por consulta com crédito pré-pago'), no platform credentials needed, and LGPD data control responsibilities. This goes beyond what annotations provide.
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 a single paragraph of four sentences, each serving a distinct purpose: primary function, hosting/payment, data source/confidentiality, and LGPD responsibility. It is front-loaded with the core purpose and contains no unnecessary words.
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 tool has only two parameters and no output schema; annotations cover safety. The description covers payment, auth context, and legal aspects. However, it omits any hint about the response format or edge cases, and lacks parameter definitions, leaving some gaps for a simple 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 coverage is 0%, so the description must compensate for parameter explanations, but it does not explain 'renavam' or 'ano'. While the names suggest vehicle registration and year, the description provides no explicit definitions, leaving the agent to infer meaning.
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 query ('consulta') for SEFAZ PR Dívida Ativa information from official Brazilian sources. The specific resource and action are stated, and it stands apart from sibling tools which are platform-level utilities (authenticate, connect, etc.).
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 usage for when SEFAZ PR active debt information is needed and explains important conditions: it's hosted by the platform, requires no platform credentials, and costs prepaid credits per query. While it doesn't explicitly compare to alternative tools, the siblings are unrelated, so the context is clear enough.
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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