audio_profile

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

With no annotations provided, the description carries full burden and does well: it states the tool is free, local, numpy-based, lists returned data (tempo, energy curve, onset hits, loudness dynamics, brightness, music-vs-speech estimate), and explicitly notes what it does not provide (genre/mood/song-ID). No contradictions.

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 concise, uses bullet points efficiently, front-loads the key purpose, and every sentence adds value without redundancy.

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 has only one parameter and no output schema, the description thoroughly explains both the input (file path) and all outputs (tempo, energy curve, onset hits, etc.), along with limitations. It is complete for the tool's complexity.

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 required parameter 'path' with 0% description coverage. The description adds meaning by specifying it accepts audio or video file paths, which clarifies the parameter's purpose. For a single parameter, this is adequate, though it could provide more detail on supported formats.

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 clearly states the tool analyzes music/energy/rhythm of audio or video files, listing specific outputs like tempo, BPM, energy curve, onset hits, etc., distinguishing it from siblings like transcribe or audio_events which focus on speech or event detection.

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 implicitly indicates usage for music/energy analysis by listing what it returns and explicitly stating what it does not provide (no genre/mood/song-ID). It could be more explicit about when to use over alternatives, but the sibling tools have different purposes (ad analysis, audio events, transcription).

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