Prefeitura GO Jataí: Certidão Negativa de Débitos, 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.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds that it is hosted by the platform, requires no platform credentials, and charges prepaid credits per consultation. This goes beyond annotations by explaining the business model and data privacy context, aligning with them.
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 moderate length, front-loaded with the main purpose. It includes necessary details about hosting, credentials, payment, and LGPD compliance. Slightly verbose but each sentence adds relevant context.
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 the tool's simplicity (two params, no output schema) and rich annotations, the description covers the essential purpose and business context. It doesn't explain parameter specifics but that's a parameter semantics gap. The description adequately sets expectations for a paid query service.
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 two parameters (cpf, cnpj) with no descriptions and 0% coverage. The description mentions the tool queries CND but does not clarify that either cpf or cnpj must be provided or their format (e.g., digits only, with or without punctuation). It also doesn't explain if both are required or optional, since required parameters are 0, leaving ambiguity.
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 the tool queries Certidão Negativa de Débitos from Prefeitura GO Jataí via an official source. It mentions the consultation is per-query with prepaid credits, distinguishing it from generic sibling tools like authenticate or marketplace, though it doesn't explicitly contrast with a similar query tool.
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?
It explains when to use: to consult official Brazilian source data, specifically CND from Jataí prefecture. It also notes it's not confidential data and the client is responsible for legitimate purpose under LGPD, implying compliance context. It doesn't discuss alternatives but siblings are not similar query tools.
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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