Conselho Regional de Odontologia MT: 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?
Annotations already indicate read-only, idempotent, non-destructive. The description adds that the data is not confidential, the client is the controller for LGPD, and that no platform credentials are required. This goes beyond annotations and clarifies the legal framing and data nature, 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 well-structured paragraph, front-loading the core purpose. It includes necessary operational details (payment, LGPD) without being verbose. Each sentence adds information.
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?
The tool is simple (one parameter, no output schema). The description covers the nature of the data (public, not secret), commercial terms (prepaid credit), and legal responsibility. However, it does not elaborate on what the consultation returns or any prerequisites beyond the required parameter. Given the simplicity, it is adequate but not comprehensive.
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 one parameter 'inscricao' with 0% description coverage in the schema. The description does not explain what 'inscricao' refers to beyond its obvious meaning (registration number). It adds no semantic detail such as format, length, or examples. Since schema coverage is 0%, the description should compensate, but it does not.
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 is a 'consulta' (query) for registration data from the official Brazilian dental council in Mato Grosso. It identifies the resource (cadastro) and the action (consultar). It does not explicitly differentiate from sibling tools, but the siblings are meta-tools (authenticate, connect, etc.), so the purpose is distinct.
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 useful context: it is a paid consultation using prepaid credit, hosted on the platform without credentials, and the data is public/official. However, it does not explicitly state when to use this tool versus alternatives, nor any exclusions. The guidance is more about legal and operational aspects than about selecting between 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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