suggest_moveset

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'sugiere moveset' but does not explain how the suggestion is generated, whether it's based on algorithms or data, what the output format might be, or any constraints like rate limits or permissions. This is inadequate for a tool with no annotation coverage, leaving significant gaps in understanding its behavior.

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, efficient sentence in Spanish, making it concise and front-loaded. However, it could be more structured by clarifying key terms like 'STAB' and 'cobertura' for non-experts. Overall, it avoids unnecessary verbosity but lacks depth.

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 complexity of moveset suggestion with 3 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It does not explain the tool's logic, output expectations, or how parameters affect results. This is insufficient for effective tool invocation by an AI agent.

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%, meaning parameters are undocumented in the schema. The description does not add any meaning to the parameters (name, version_group, role). It does not explain what 'name' refers to (e.g., Pokémon name), what 'version_group' options entail beyond the default, or how 'role' influences the moveset suggestion. This fails to compensate for the low coverage, providing minimal value 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 the tool 'sugiere moveset (STAB + cobertura) usando tipos de cada movimiento,' which translates to 'suggests moveset (STAB + coverage) using types of each move.' This provides a vague purpose: it suggests a moveset based on types, but it's unclear what 'STAB + cobertura' specifically entails or how it differs from sibling tools like 'validate_moveset' or 'get_learnset.' It does not clearly distinguish from siblings, making it somewhat ambiguous.

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 offers no guidance on when to use this tool versus alternatives. With sibling tools such as 'validate_moveset' and 'get_learnset,' there is no indication of context, prerequisites, or exclusions. This lack of guidance leaves the agent unsure about appropriate usage scenarios.

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