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 meaningful transparency beyond those: no platform credentials required, pay-per-query with prepaid credit, source is official public data, data is not confidential, and the customer is the data controller under LGPD. This is strong behavioral and contextual disclosure.

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 reasonably concise and front-loaded with the core purpose. It includes some extra legal/context sentences about LGPD and data controllership, which are relevant but slightly beyond the minimal necessary; still, each sentence adds some useful operational context and the overall length is appropriate.

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 single-parameter simplicity and rich annotations, the description covers purpose, access model, payment, and data sensitivity well. However, there is no output schema, and the description does not describe what the response contains or example result fields, leaving the agent without a clear picture of the query outcome. It is adequate but not fully complete.

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?

With only one parameter, 'inscricao', and 0% schema description coverage, the description needed to explain what this value is (e.g., the dental council registration number) and its expected format. It only vaguely references 'Cadastro' and does not clarify how to fill the parameter or what values are valid, so the description fails to compensate for the sparse 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 identifies the tool as a consultation/query for Conselho Regional de Odontologia AC registration data in an official source. It distinguishes the resource via the council name and the 'consulta' intent, though it is not as explicit or action-forward as a direct 'Consultar cadastro...' phrasing.

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 gives useful context about access (no platform credentials, prepaid credit) and the legitimate use case (official public data, LGPD compliance). However, it does not state explicit 'when to use this tool versus alternatives' or provide any exclusion criteria, leaving the usage guidance implied rather than direct.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.