songsee – Coding skill for AI agents
Audio spectrograms/features (mel, chroma, MFCC) via CLI.
Install the songsee skill with one command
Pick the tool you use, copy the command and paste it in your terminal. The skill lands in that tool's skills folder and is ready in your next session.
Claude Code
mkdir -p ~/.claude/skills && curl -fsSL https://skill.dn1nguoi.com/z/songsee-04cf7.tgz | tar xz -C ~/.claude/skills
Call it in Claude Code: /songsee – then describe the task you want done.
Codex
mkdir -p ~/.codex/skills && curl -fsSL https://skill.dn1nguoi.com/z/songsee-04cf7.tgz | tar xz -C ~/.codex/skills
Call it in Codex: $songsee – then describe the task you want done.
Hermes Agent
mkdir -p ~/.hermes/skills && curl -fsSL https://skill.dn1nguoi.com/z/songsee-04cf7.tgz | tar xz -C ~/.hermes/skills
Call it in Hermes Agent: /songsee – then describe the task you want done.
DeepSeek
mkdir -p ~/.deepcode/skills && curl -fsSL https://skill.dn1nguoi.com/z/songsee-04cf7.tgz | tar xz -C ~/.deepcode/skills
Call it in DeepSeek: /songsee – then describe the task you want done.
SKILL.md content
songsee
Generate spectrograms and multi-panel audio feature visualizations from audio files.
Prerequisites
Requires [Go](https://go.dev/doc/install):
go install github.com/steipete/songsee/cmd/songsee@latestOptional: ffmpeg for formats beyond WAV/MP3.
Quick Start
# Basic spectrogram
songsee track.mp3
# Save to specific file
songsee track.mp3 -o spectrogram.png
# Multi-panel visualization grid
songsee track.mp3 --viz spectrogram,mel,chroma,hpss,selfsim,loudness,tempogram,mfcc,flux
# Time slice (start at 12.5s, 8s duration)
songsee track.mp3 --start 12.5 --duration 8 -o slice.jpg
# From stdin
cat track.mp3 | songsee - --format png -o out.pngVisualization Types
Use --viz with comma-separated values:
| Type | Description |
|------|-------------|
| spectrogram | Standard frequency spectrogram |
| mel | Mel-scaled spectrogram |
| chroma | Pitch class distribution |
| hpss | Harmonic/percussive separation |
| selfsim | Self-similarity matrix |
| loudness | Loudness over time |
| tempogram | Tempo estimation |
| mfcc | Mel-frequency cepstral coefficients |
| flux | Spectral flux (onset detection) |
Multiple --viz types render as a grid in a single image.
Common Flags
| Flag | Description |
|------|-------------|
| --viz | Visualization types (comma-separated) |
| --style | Color palette: classic, magma, inferno, viridis, gray |
| --width / --height | Output image dimensions |
| --window / --hop | FFT window and hop size |
| --min-freq / --max-freq | Frequency range filter |
| --start / --duration | Time slice of the audio |
| --format | Output format: jpg or png |
| -o | Output file path |
Notes
- WAV and MP3 are decoded natively; other formats require
ffmpeg - Output images can be inspected with
vision_analyzefor automated audio analysis - Useful for comparing audio outputs, debugging synthesis, or documenting audio processing pipelines
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