SEFAZ PR: CADIN, 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 |
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 indicate read-only, idempotent, and non-destructive behavior, and the description confirms it is a query that does not modify data. It also transparently mentions the cost per query and that the client is responsible for data legitimacy under LGPD, adding useful behavioral context beyond 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 somewhat repetitive, reiterating that it is official, non-confidential, and from official sources. It could be more concise and better structured, but it is not excessively long. The legal disclaimers add bulk without enhancing clarity.
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 lacks essential details about the tool's functionality: it does not specify what data is returned, how to interpret results, or what the parameters represent. Since there is no output schema and no parameter descriptions, the description alone is insufficient for an agent 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 parameters 'cpf' and 'cnpj' have no descriptions in the schema, and the description does not mention them at all. With 0% schema description coverage, the description provides no additional meaning about what these parameters are for or their format, leaving the agent with no guidance.
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 it is a query (consulta) for CADIN information from official sources. The verb 'consultar' in the tool name and the explicit mention of official sources make the purpose fairly clear, though it does not specify the exact nature of the data returned (e.g., debt status).
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 indicates it is a paid service using prepaid credits and that no platform credentials are needed, which gives some usage context. However, it does not explicitly state when to use this tool versus alternatives, nor does it provide conditions like 'use when checking CADIN status' or 'avoid if unnecessary'. The sibling tools are not similar, so no explicit differentiation is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.