Prefeitura GO Uruaçu: 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 already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds important context: it is a paid service requiring prepaid credits, hosted by the platform with no platform credentials, and returns public data. This goes beyond annotations by disclosing the commercial/operational aspect and legal compliance 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 description is a single paragraph with concise sentences covering purpose, source, payment model, and data privacy. It front-loads the core purpose and includes necessary operational details without excessive length.
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 has no output schema and no parameter descriptions, the description covers the main use case, the data source, payment requirements, and legal context. It could be more explicit about parameter usage (e.g., requiring CPF or CNPJ) but overall provides adequate context for an agent to understand what the tool does and the conditions of use.
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%, so the description must compensate for parameter meanings. The description names the tool as consulting a certificate via CPF or CNPJ, which implies these are the identification numbers, but it does not explicitly explain that either cpf or cnpj must be provided or their roles. The schema shows two string properties with no descriptions, so this is a minimal 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 states the tool consults Certidão Negativa de Débitos (negative debt certificate) for the municipality of Uruaçu, GO, from an official source. It specifies the resource (certificate) and action (consult), and distinguishes it from siblings by naming the specific municipality and certificate type.
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 explains this is a paid consultation using platform credits, hosted by the platform, and that it accesses official public data. It implies this is for legitimate compliance purposes (LGPD) and notes the client is data controller, but does not explicitly state when to use it instead of other tools or when not to use it.
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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