aya_modelo_privacidade_avaliar

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral burden and does disclose meaningful logic: it is provider-agnostic and considers local/remote model, data training, and context sensitivity. However, it does not state whether the tool is read-only, whether it produces a decision/recommendation, or whether it has side effects.

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?

A single sentence that front-loads the core purpose, adds the key provider-agnostic nuance, and lists the decision criteria without waste. Every clause earns its place.

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 tool with no annotations and no output schema, the description is incomplete: it does not explain what the tool returns, how the rule is applied in practice, whether it can block/allow, or what happens with missing inputs. The logic criteria are helpful but not sufficient for confident invocation.

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?

Schema description coverage is 0%, so the description must compensate. It partially does by mapping its concepts to parameters: local/remote to 'local', training with data to 'treinaDados', and context sensitivity to 'dadosSensiveis'. It does not clarify the 'modelo' string format or explain defaults/required behavior beyond the 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 states a specific action ('Aplica a regra de privacidade') and names the relevant resource/scope (model privacy evaluation, provider-agnostic). It is clear enough to differentiate from the broader sibling set, though it does not explicitly name or contrast a sibling alternative.

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 guidance is given about when to use this tool versus alternatives such as aya_modelo_perfil_execucao or aya_politicas_planejar. The description implies a privacy-evaluation context but provides no exclusions, prerequisites, or routing conditions.

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