analyze_mix

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

No annotations, so the description carries the full burden and does well: it discloses the disk-read side effect, the 16-stem cap error behavior, and the per-stem missing-file error shape. Missing only details on failure modes for other errors or expected runtime.

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?

Front-loaded with the purpose, then side effects, example, and edge cases in four tight, information-dense blocks. No filler sentences.

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 one-parameter analysis tool with no output schema, the description covers purpose, side effects, example, and error behavior. What remains unsaid is how to interpret the returned LUFS/masking values and typical performance, but the essentials for correct invocation are present.

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 0% and there is one parameter, so the example call ('stems=[...]') and the edge-case note (>16 raises error, missing files reported per-stem) supply the semantics the schema lacks. This meaningfully compensates for the absent schema descriptions.

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 verb (run) and resource (per-stem analysis and pair-wise masking across local audio files), with a concrete example call. Distinguishes itself from audio tooling siblings like analyze_audio and find_frequency_masking by naming the exact outputs (LUFS, masking scores).

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?

Provides an example that implies usage (batch stems of a mix), but never explicitly says when to use this versus find_frequency_masking or analyze_audio. No exclusion criteria or prerequisite context beyond the 16-file limit.

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