Conselho Federal de Medicina: Estabelecimentos de Saúde, 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 |
|---|---|---|---|
| cnpj | Yes |
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 read-only, idempotent, non-destructive. The description adds valuable context: hosted by platform, no platform credentials needed, pay-per-query with prepaid credit, data is official and non-confidential, and LGPD compliance responsibilities. This goes beyond annotations and clarifies operational and legal behavior without contradiction.
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, succinctly covering the purpose, payment model, and legal notes. It is front-loaded with the core function and avoids unnecessary filler. Minor redundancy (e.g., 'fonte oficial' repeated) but overall efficient.
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 (one parameter) and lack of output schema, the description could be more complete. It does not describe the return value or what information is provided after a query (e.g., establishment name, address). It also omits any details on how the paid credit works or error handling. While it covers official source and LGPD, it leaves key operational aspects unexplained.
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?
Only one parameter, cnpj, is present and it's a plain string with no description in the schema (0% coverage). The description does not explain the parameter's format, expected pattern (e.g., CNPJ with punctuation), or purpose. While the name is self-explanatory, the description fails to add any semantic clarity beyond the raw schema.
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 consults health establishments from an official Brazilian source (CFM). The verb 'consultar' and resource 'estabelecimentos de saúde' are specific, and the tool is distinct from sibling tools like authenticate or marketplace, which serve different purposes.
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?
No explicit guidance on when to use this tool versus alternatives. It mentions it's a paid query with prepaid credit, but does not state criteria for choosing it over other tools or what the query is for (e.g., verifying registration). No exclusions or alternatives are given.
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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