SINTEGRA: ES, 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 | 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=true and destructiveHint=falsedurante. The description adds useful context: payment model (prepaid credits), lack of platform credentials, and LGPD compliance responsibility. However, it does not describe potential response format, pagination, or error behavior, so it's good but not exhaustive.
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, with a single paragraph covering purpose, authentication, payment, and legal note. It is front-loaded with the core query function. Slightly dense but acceptable.
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 zero schema descriptions, the description provides minimal context about the tool's behavior. It explains the data source and payment but omits details about what data is returned, parameter usage, and any limitations. This leaves significant gaps for the agent to understand how to use the tool correctly.
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 no descriptions (0% coverage), and the description does not explain the parameters 'ie' and 'cnpj' beyond their names. There is no elaboration on what each parameter does, whether they are mutually exclusive or optional, or any format requirements. This is a significant 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 this tool performs a consultation/query of official Brazilian data sources (SINTEGRA ES). It names the resource (official sources) and the action (consulta). It distinguishes itself from siblings by being a data query tool, but doesn't explicitly contrast with alternatives. The description is specific enough but could be clearer about what data is 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 context (official source, no platform credentials, paid per query with prepaid credits) but does not explicitly state when to use this tool versus alternatives, nor when not to use it. It implies usage for retrieving public official data, but lacks clear selection 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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