Songsee
- 14 installs
- 869 repo stars
- Updated June 8, 2026
- beita6969/scienceclaw
This is a copy of songsee by steipete - installs and ranking accrue to the original listing.
songsee is a Claude skill for the songsee CLI, which generates spectrograms and feature-panel visualizations from audio files.
About
This skill drives the songsee command-line tool to generate spectrograms and feature-panel visualizations from audio files. A developer uses it to render a spectrogram, produce a multi-panel grid of audio features like mel, chroma, MFCC, and tempogram, or extract a time slice of a track. It documents the CLI flags for visualization types, palettes, output size, FFT settings, frequency range, and format.
- Generates spectrograms and multi-panel feature visualizations from audio via the songsee CLI
- Supports mel, chroma, HPSS, self-similarity, loudness, tempogram, MFCC, and flux panels
- Time-slice, stdin piping, palette, and FFT window/hop flags
Songsee by the numbers
- 14 all-time installs (skills.sh)
- Data as of Aug 2, 2026 (Skillselion catalog sync)
songsee capabilities & compatibility
Free; requires installing the songsee CLI via brew (steipete/tap/songsee) and optionally ffmpeg for non-WAV/MP3 formats.
- Capabilities
- data analysis
- Use cases
- data analysis
- Platforms
- macOS
- Pricing
- Free
What songsee says it does
Generate spectrograms and feature-panel visualizations from audio with the songsee CLI.
Multi-panel: `songsee track.mp3 --viz spectrogram,mel,chroma,hpss,selfsim,loudness,tempogram,mfcc,flux`
WAV/MP3 decode native; other formats use ffmpeg if available.
npx skills add https://github.com/beita6969/scienceclaw --skill songseeAdd your badge
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| Installs | 14 |
|---|---|
| repo stars | ★ 869 |
| Last updated | June 8, 2026 |
| Repository | beita6969/scienceclaw ↗ |
What it does
Render a spectrogram or multi-panel audio-feature visualization from an audio file using the songsee CLI.
Who is it for?
Rendering spectrograms and multi-panel audio-feature visualizations from audio tracks.
Skip if: Editing or synthesizing audio; it only visualizes it.
When should I use this skill?
You need to visualize an audio file as a spectrogram or feature-panel grid.
What you get
Spectrogram and feature-panel images (mel, chroma, MFCC, tempogram, and more) rendered from an audio file.
- spectrogram image
- audio feature panel grid
By the numbers
- 9 visualization panel types
- 5 palette styles (classic, magma, inferno, viridis, gray)
- 2 native decode formats (WAV, MP3)
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
--vizlist (repeatable or comma-separated)--stylepalette (classic, magma, inferno, viridis, gray)--width/--heightoutput size--window/--hopFFT settings--min-freq/--max-freqfrequency range--start/--durationtime slice--formatjpg|png
Notes
- WAV/MP3 decode native; other formats use ffmpeg if available.
- Multiple
--vizrenders a grid.
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What visualizations can it produce?
Spectrogram, mel, chroma, HPSS, self-similarity, loudness, tempogram, MFCC, and flux panels, rendered as a grid when multiple are requested.
What audio formats work?
WAV and MP3 decode natively; other formats use ffmpeg if available.