analyze_audio

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

With no annotations, the description carries the transparency burden. It discloses dependencies ('Needs numpy+soundfile'), algorithm fallback ('loudness_method says whether LUFS came from pyloudnorm or the numpy fallback'), and implies read-only intent via 'listening step.' It also enumerates the full set of computed metrics, which is substantial behavioral disclosure.

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 front-loaded with the core purpose and then packs in detailed output information. While the output list is long, it is organized and every sentence adds value. It is appropriately detailed for a complex analysis tool, though some metric enumeration may be redundant with the output schema.

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?

The description covers prerequisites, dependencies, workflow, and algorithm fallback. Given the tool's complexity and the presence of an output schema, it is reasonably complete. It doesn't discuss error cases, but the core usage context is well covered.

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?

The schema has one parameter (wav_path) with zero description coverage. The description implies the path should be a rendered/captured audio file by saying 'Capture a track/section first (record_audio) or render via the export path, then analyze.' This adds context beyond the field title but lacks explicit format or examples.

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 opens with 'Analyze a rendered/captured audio file — the objective listening step.' This is a specific verb+resource combination and clearly distinguishes the tool from siblings like record_audio and record_and_analyze by framing it as the analysis-after-capture step.

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?

It provides explicit workflow guidance: 'Capture a track/section first (record_audio) or render via the export path, then analyze.' This names the prerequisite sibling tool and establishes temporal ordering. It doesn't explicitly exclude alternatives like compare_audio, 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.