mcp_opendaw_apply_mix_preset

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

No annotations are provided, so the description carries the full burden. It discloses that the tool applies settings to all audio units, returns applied settings, and can use named presets. However, it does not mention prerequisites (e.g., units must exist), error handling (e.g., invalid preset keys), or side effects (e.g., overwriting existing settings). Given no annotations, this is adequate but not thorough.

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 well-structured with a lead sentence, bullet-like sections, and examples. It is reasonably concise but includes some redundancy (the example repeats the preset format already described). Overall, it earns its space and is front-loaded with the key purpose.

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 tool's complexity (applies mix to all units), no annotations, and low schema coverage, the description is quite complete. It covers the action, parameter format, built-in presets, and return value. Minor gaps: it doesn't explain behavior for non-existent units or invalid preset keys. But overall, it provides sufficient context for an AI agent to use the tool effectively.

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 fully explain the 'preset' parameter. It does so in detail: the parameter can be a JSON string with unit indices and settings (volume_db, panning, mute, solo) or a named preset string like 'lofi'. It provides concrete examples and even describes the built-in presets. This exceeds what the schema alone conveys.

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 starts with 'Apply a mix preset to all audio units in one call — volume, pan, mute, solo.' This clearly states the verb (apply), resource (mix preset to all audio units), and scope (volume, pan, mute, solo). It explicitly distinguishes from sibling tools like set_track_volume by noting it replaces 10-30 individual calls.

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 provides clear context on when to use this tool: when you want to apply a mix preset to all units and replace many individual set_* calls. It mentions alternatives (named presets vs custom JSON) and gives examples. It does not explicitly state when not to use, but the context is clear enough.

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