cuba_forget

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

No annotations are provided, so the description fully covers behavioral traits: it states the operation is 'cascading', 'hard-delete', 'IRREVERSIBLE', and lists affected areas (observations, relations, errors, sessions). No contradictions found.

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?

Two sentences, zero filler. First sentence states the action and scope; second sentence emphasizes irreversibility and a precondition. Every word is purposeful.

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 destructive tool with no output schema, the description provides ample context about the effect and prerequisites. It could mention the return value (e.g., success/error), but the warnings make it largely sufficient.

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 coverage is 100% with clear descriptions for both parameters. The description adds the safety requirement 'Requires confirm=true' but does not significantly enhance understanding beyond schema. Baseline score of 3 is appropriate.

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 uses specific verbs ('cascading hard-delete') and clearly identifies the resource ('entity and ALL references across observations, relations, errors, and sessions'). It distinguishes itself from sibling tools like 'cuba_receta' or 'cuba_archivo' by focusing on complete erasure.

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 mentions 'GDPR Right to Erasure' as a use case and highlights the need for 'confirm=true', but does not explicitly state when not to use it or compare it to alternatives among siblings. Clear context but lacks exclusions.

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