merge_presets

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

No annotations are provided, so description must disclose side effects. It states 'Generated merges are automatically added to the library.' and mentions defaults, but does not detail whether the operation is destructive (e.g., overwrites existing presets) or describe other safety aspects like rate limits or required permissions.

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?

Three sentences: purpose, selection methods, default behavior. Front-loaded and no wasted words. Efficiently communicates key 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?

Description covers purpose, selection methods, and result handling (auto-add to library). However, it lacks details on error conditions, limits, or precise meaning of 'weighted random ratios.' For 7 parameters and no output schema, it is fairly complete but could be more precise.

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%, so baseline is 3. The description adds some context (e.g., 'weighted random ratios', auto-add to library) not present in parameter descriptions, but the marginal value is limited since schema descriptions already cover wildcards and filtering options.

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?

Description clearly states 'Merge multiple presets to create hybrid sounds using weighted random ratios.' This distinguishes from sibling tools like generate_random_presets (creates new presets) and randomize_presets (randomizes existing).

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?

Description explains how to select presets (via preset_names with wildcards or filters), but does not explicitly state when to use this tool versus alternatives like generate_random_presets or randomize_presets. This limits guidance for an AI agent.

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