songsee
Generate spectrograms and feature-panel visualizations from audio with the songsee CLI.
npx skills add SafeAI-Lab-X/ClawKeeper --skill songsee --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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.
What does the songsee skill do?
Generate spectrograms and feature-panel visualizations from audio with the songsee CLI.
How do I install it?
Run `npx skills add SafeAI-Lab-X/ClawKeeper --skill songsee --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From SafeAI-Lab-X/ClawKeeper, a repository with 1,034 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.