Prefeitura RS Canela: 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. 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, and destructiveHint=false. The description adds valuable context beyond these: payment per consultation with prepaid credits, no need for platform credentials, and LGPD-related responsibilities for the client as data controller. It also explicitly states the data is not confidential, which is relevant for compliance. No contradiction with 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 paragraph that covers purpose, payment model, data source, and legal responsibility. It is reasonably concise but not front-loaded; the core purpose appears first, which is good. Slightly more structure or brevity could earn a 5.
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?
For a simple two-parameter tool without an output schema, the description adequately explains the purpose, pricing, and legal boundaries. It lacks guidance on how to provide the CPF/CNPJ and what the returned certificate looks like, but the overall context is sufficient for an agent to understand the tool's role.
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 zero description coverage. The description does not explain the role of these parameters, whether at least one is required, or how to choose between them. Since the description must compensate for low schema coverage but fails to do so, 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 the tool consults a Certidão Negativa de Débitos (Negative Debt Certificate) from Prefeitura RS Canela, using the verb 'consulta' and identifying the specific resource and municipality. This distinguishes it from the generic sibling tools like authenticate, connect, and marketplace.
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 how the tool is used: it is hosted by the platform, requires no platform credentials, and charges per query with prepaid credit. It implies the use case is querying official Brazilian sources, but it does not explicitly state when to use this instead of an alternative or include exclusions, so it stops short of a 5.
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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