auto_master_music

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

No annotations are provided, so the description carries the full disclosure burden. It reveals async behavior, job_id returns, a six-step processing pipeline, noise reduction being off by default, no post-normalize, and loudness handling that only reduces peaks and never boosts.

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 purpose and async behavior are front-loaded, followed by a tight numbered pipeline, an Args block, and a final guardrail warning. Every sentence adds operational value with little to no filler.

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 two-optional-parameter async tool with no output schema, the description covers the full call contract: what happens, the processing order, parameter semantics, return behavior, and how to monitor or avoid duplicate calls. It is more than sufficient for an agent to invoke it correctly.

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%, but the description fully compensates: style is documented with six concrete preset values and its default, and noise_reduce is explained as gentle noise reduction with default False. This adds real meaning the schema alone does not provide.

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?

States a specific action—professionally master a music track—with genre-tuned settings, and the detailed pipeline makes it distinct from sibling cleanup, audiobook, and lofi tools. It goes well beyond restating the tool name.

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?

Explicitly tells the agent to monitor with check_pipeline_status and warns not to call again while a pipeline is already running, naming the exact alternative. It also clarifies that this is a background, async operation rather than a synchronous one.

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