Skill detail

music-analyze

Analyzes local audio files to extract rhythm, emotion, timbre, tonality, lyrics, and color palette as structured JSON.

MatchPossibleReviewed for Music Generation

Sourcebenzema216/music-analyzerExternal source

Reported installs4Popularity signal only

Inspect before use

Automated review checks relevance, not safety or endorsement. Read the source instructions before using this skill.

View on skills.sh (opens external page)Read SKILL.md on GitHub (opens external page)

Saved source preview

SKILL.md

The saved excerpt is a snapshot from review. The external source remains the complete and most current version.

---
name: music-analyze
description: Full music analysis — extracts rhythm, emotion, timbre, tonality, lyrics and outputs structured JSON
user_invocable: true
---

# /music-analyze — Full Music Analysis

Analyze a local audio file and output a comprehensive structured JSON containing rhythm, emotion, timbre, tonality, lyrics, onset, and color palette data.

## Usage

```
/music-analyze <audio_file_path>
```

## Accepted Formats
MP3, WAV, FLAC, OGG, M4A, AAC, WMA

## Steps

1. Validate the audio file path exists and is a supported format
2. Run the full analysis pipeline:

```bash
python3 -m music_analyzer analyze "<audio_file_path>"
```

3. Parse the JSON output and present a structured summary to the user:
   - **Rhythm**: BPM, time signature, song structure sections
   - **Emotion**: Primary mood, energy level, valence, genre
   - **Timbre**: Brightness, warmth, dynamic range, MFCC summary
   - **Tonality**: Key, mode, chord progression highlights
   - **Lyrics**: Whether vocals detected, language, transcription preview
   - **Onsets**: Onset rate (for visual sync reference)
   - **Color Palette**: Suggested colors based on mood

4. If the user wants to generate Dreamina prompts or storyboards, suggest:
   - `/music-to-dreamina` for Dreamina image/video generation prompts
   - `/music-to-storyboard` for shot-by-shot storyboard
   - `/music-color-palette` for detailed color scheme

## Options

- Add `--no-cache` to force re-analysis (skip cached results)
- Add `--no-separation` to skip Demucs source separation (faster)
- Add `--output <path>` to save JSON to a specific file

## Output

The analysis JSON follows the `MusicAnalysisResult` schema and can be saved and reused as input for the formatter commands (dreamina, storyboard, color-palette).

## Error Handling

- If librosa is not installed, instruct user: `pip install -e ~/.claude/plugins/music-analyzer/src/`
- If optional features are missing, the tool will degrade gracefully and note which tier is active (lite/standard/full)

Read the full source on GitHub

Context