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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/nousresearch/hermes-agent --skill songsee- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads songsee automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
songsee
Generate spectrograms and multi-panel audio feature visualizations from audio files.
Prerequisites
Requires Go:
go install github.com/steipete/songsee/cmd/songsee@latest
Optional: 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.png
Visualization 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
FAQ
What does the songsee skill do?
Audio spectrograms/features (mel, chroma, MFCC) via CLI.
How do I install songsee?
Run npx skills add https://github.com/nousresearch/hermes-agent --skill songsee in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/songsee/ (personal) or .claude/skills/songsee/ (project).
Which AI agents can use songsee?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is songsee safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains songsee?
It is published by nousresearch in nousresearch/hermes-agent. It has 370 recorded installs.
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