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steipete avatar

Songsee

steipete/clawdis

songsee turns audio files into visual representations: spectrograms, mel frequency plots, chroma features, and several other analysis panels that audio engineers and music researchers actually use. You can render a single visualization or combine up to nine panels in a grid, slice specific time ranges, and pipe from stdin. The CLI feels thoughtfully designed with sensible defaults but plenty of control over FFT windows, frequency ranges, and color palettes. It's the kind of tool that's genuinely useful when debugging audio processing pipelines or just trying to see what's happening in a track beyond waveforms. Native WAV and MP3 support, falls back to ffmpeg for everything else.

installs
2.6K
GitHub stars
382.8K
last updated
Jul 14, 2026
View on GitHubSave

Install

$ npx -y skills add steipete/clawdis --skill songsee --agent claude-code

Installs into .claude/skills of the current project.

Files

songsee

Generate spectrograms + feature panels from audio.

Quick start

  • Spectrogram: songsee track.mp3
  • Multi-panel: songsee track.mp3 --viz spectrogram,mel,chroma,hpss,selfsim,loudness,tempogram,mfcc,flux
  • Time slice: songsee track.mp3 --start 12.5 --duration 8 -o slice.jpg
  • Stdin: cat track.mp3 | songsee - --format png -o out.png

Common flags

  • --viz list (repeatable or comma-separated)
  • --style palette (classic, magma, inferno, viridis, gray)
  • --width / --height output size
  • --window / --hop FFT settings
  • --min-freq / --max-freq frequency range
  • --start / --duration time slice
  • --format jpg|png

Notes

  • WAV/MP3 decode native; other formats use ffmpeg if available.
  • Multiple --viz renders a grid.
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Details

Repository
github.com/steipete/clawdis
First seen
Apr 16, 2026

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