Conselho Regional de Odontologia RR: Cadastro, 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 |
|---|---|---|---|
| inscricao | 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?
The description adds valuable behavioral context beyond the annotations: it mentions payment via prepaid credit, lack of platform credentials, and data sensitivity (non-confidential, LGPD compliance). Annotations already mark it read-only and idempotent, so these additions are complementary and non-contradictory.
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 compact paragraph with each sentence contributing distinct information: purpose, hosting/credentials, payment model, data nature, and legal compliance. It is front-loaded with the core purpose and avoids redundancy, though it could be tightened slightly.
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 (single parameter, no output schema) and the presence of readOnly/idempotent/destructive annotations, the description covers essential operational aspects: cost model, credential requirements, data sensitivity, and legal responsibilities. It does not discuss result format or error handling, but that is acceptable for a straightforward query tool.
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 0% description coverage for the sole parameter 'inscricao', and the description does not explicitly explain this parameter. While the field name is somewhat self-explanatory to Portuguese speakers, the description neither defines it nor provides usage examples, failing to compensate for the lack of schema documentation.
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 registration data from the Regional Council of Dentistry of Roraima (RR) via an official source. It distinguishes itself from generic sibling tools by specifying the domain (dental registration) and source credibility, though it could be more verb-specific.
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 context on how to use (prepaid credit, no platform credentials) and when it's appropriate (official Brazilian data, non-confidential). However, it does not explicitly compare to alternative tools or state when not to use it, leaving usage guidance implied rather than explicit.
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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