# Songsee

> Generates spectrograms and multi-panel audio feature visualizations from audio files via a command-line tool.

- Skill: `comeonoliver/songsee` (Agent Skill)
- Install (CLI): `npx skillmds add comeonoliver/songsee`
- Raw SKILL.md: https://api.skillmd.com/api/skills/comeonoliver/songsee/raw
- Safety review: PASS (external: skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics, AI & ML, Data Visualization, Speech & Audio
- Tags: Audio Analysis, Audio Visualization, Chroma, Ffmpeg, Mel Spectrogram, Mfcc, Spectrogram
- Author: ComeOnOliver (https://skillmd.com/u/comeonoliver)
- Updated: 2026-08-22
- Page: https://skillmd.com/skills/comeonoliver/songsee

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# 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.