SINTEGRA: AM, 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 |
|---|---|---|---|
| ie | No | ||
| cnpj | 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 indicate read-only, idempotent, non-destructive behavior. The description adds meaningful context beyond that: queries are paid per consultation via prepaid credit, no platform credentials are required, data is public and non-confidential, and the client is the LGPD controller. This is useful behavioral and operational context.
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 text is front-loaded with the core purpose and is only three sentences, but the legal and commercial details (LGPD, controller responsibility, payment conditions) could be condensed. It is acceptable but not maximally concise.
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?
For a simple two-parameter read-only tool, the description covers payment, official source, and data privacy obligations reasonably well. However, with no output schema present, it does not explain the return value shape, potential error cases, or how the optional IE parameter behaves, leaving noticeable 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?
Schema description coverage is 0%, and the description does not mention the 'cnpj' or 'ie' parameters at all, nor their formats, constraints, or relationship to SINTEGRA queries. The required parameter is left completely implicit, so the description adds no value beyond the raw schema.
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 identifies a specific query operation ('consulta') against SINTEGRA AM, an official Brazilian source, and clearly differentiates it from sibling platform management tools like authenticate, marketplace, and report_bug. However, it does not explicitly state what data is returned, relying on prior knowledge of SINTEGRA.
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 commercial and legal context (prepaid credits, no credentials, LGPD) but gives no explicit guidance on when to use this tool versus alternatives or when not to use it. Sibling tools are unrelated, so there is no differentiation or exclusion 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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