SINTEGRA: RJ, 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 | ||
| cpf | 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, idempotentHint=true, destructiveHint=false, and the description adds substantial behavioral context: it's hosted on the platform, doesn't require platform credentials, requires prepaid credits per query, and queries official non-confidential data. It also clarifies LGPD compliance and that the client is the data controller. This goes beyond the annotations by explaining the authorization/billing model and legal context, while not contradicting the 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 a single, information-dense paragraph in Portuguese that covers purpose, hosting, credentials, billing, data source, legal compliance, and data controller responsibilities. Every sentence earns its place, no fluff, and it's front-loaded with the tool's identity. While it's longer than the examples, it packs necessary compliance and operational info efficiently.
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?
Given this is a read-only query tool with no output schema and only 3 optional params, the description fully satisfies completeness. It explains what data is queried, the legal basis, payment model, and who owns compliance responsibility—critical for a tool handling Brazilian personal data. The lack of output schema is fine because the description focuses on the query purpose; return value is inherently the SINTEGRA consultation result. For the tool's complexity, nothing is missing.
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 input schema provides only parameter names (ie, cpf, cnpj) with no descriptions or types beyond string. The description doesn't detail each parameter, but schema coverage is 0%, so the description was expected to compensate. The description's strength lies in context (SINTEGRA RJ, official source, LGPD) rather than parameter-level detail. However, given the parameters are self-explanatory Brazilian taxpayer IDs (CPF, CNPJ, IE) and the tool name indicates SINTEGRA consult, the semantics are partially implied. The description could have provided more explicit parameter guidance, so a 4 is fair given the strong contextual compensation.
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 consulting SINTEGRA RJ in an official source, specifying it queries information from official Brazilian sources. It distinguishes itself by noting it's hosted on the platform, requires no platform credentials, and is paid per query with prepaid credits, which differentiates it from sibling tools. However, it doesn't explicitly name a sibling alternative, so it doesn't fully distinguish from siblings like authenticate or marketplace, but the verb 'consultar' plus 'fonte oficial' provides specific action and resource.
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 context on when to use the tool: for consulting SINTEGRA RJ official data via the platform, with no need for platform credentials. It mentions it's the same data available to citizens and addresses LGPD compliance, implying appropriate use cases. It doesn't explicitly state when not to use this tool versus alternatives, nor name alternatives, but the context is clear enough for an agent to decide.
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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