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media_audio_to_midi

Convert audio from video or standalone files to MIDI note data, returning a MIDI file and note summary for music production and analysis.

Instructions

Transcribe audio to MIDI using basic-pitch (ML audio transcription).

Converts audio (from video or standalone) into MIDI note data. Returns the MIDI file path and a summary of detected notes.

Requires basic-pitch: pip install basic-pitch

Args: path: Path to audio file (wav, mp3, flac) or video file output_path: Where to save MIDI (default: same dir, .mid extension)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
output_pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries full burden. It mentions the dependency (basic-pitch) and that it returns a MIDI file path and note summary. However, it does not disclose potential failure modes, performance characteristics, or limitations beyond the dependency. Adequate but could be more thorough.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is structured with a clear first line stating purpose, a supporting sentence, and a parameter breakdown. It is reasonably concise, though the parameter descriptions could be integrated into the main text. No superfluous content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (audio transcription with external dependency) and lack of output schema in the provided data, the description covers input parameters, output summary, and a required installation. It lacks error handling or edge cases, but for a tool that returns a path, it is fairly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description fully compensates by explaining both parameters: 'path' specifies allowed audio/video formats, 'output_path' gives default behavior and extension. This adds crucial meaning beyond the schema's type and title.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: transcribe audio to MIDI using basic-pitch ML audio transcription. It specifies the action (transcribe), the input (audio), and the output (MIDI). This distinguishes it from sibling tools like media_detect_beats or media_extract_audio.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains what the tool does but does not provide explicit guidance on when to use it versus alternatives. It implies use for audio-to-MIDI conversion, but lacks direct comparisons or when-not-to-use cases. Sibling tools include other audio processing, so implicit differentiation exists but not explicit.

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

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