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songsee

Generate spectrograms and multi-panel audio feature visualizations from audio files via CLI.

2|Updated Jan 2, 2026
Search Tags:#cli#chroma#spectrogram#mfcc#audio visualization#music analysis#mel
One-click install
npx skills add https://github.com/ShineBreaker/Guix-configs --skill songsee-shinebreaker
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: songsee
Source: https://github.com/ShineBreaker/Guix-configs/tree/main/dotfiles/mutable/agents/hermes/.local/share/hermes/skills/.archive/songsee
Command: npx skills add https://github.com/ShineBreaker/Guix-configs --skill songsee-shinebreaker

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Analyzing audio content visually requires specialized tooling; this Skill turns audio files into spectrograms and feature visualizations (mel, chroma, MFCC, and more) with a single CLI command, making audio characteristics inspectable as images. ## Core Features & Use Cases - Spectrogram Generation: Render standard, mel-scaled, and styled spectrograms from WAV or MP3 files with configurable FFT window, hop size, and frequency range. - Multi-Panel Feature Grids: Combine up to nine visualization types (chroma, HPSS, self-similarity, loudness, tempogram, MFCC, flux) into a single image grid. - Time Slicing & Piping: Visualize specific audio segments with --start/--duration, or stream audio via stdin for pipeline integration. - Use Case: Compare two synthesized audio outputs by generating side-by-side mel spectrograms, then inspect the images with a vision model to verify frequency content. ## Quick Start Ask the assistant to generate a mel spectrogram of your audio file, for example: "Create a spectrogram of track.mp3 and save it as spectrogram.png."

Frequently Asked Questions about songsee

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate a spectrogram from an MP3 file?▼

Run songsee with the audio file as argument, for example: songsee track.mp3 -o spectrogram.png. WAV and MP3 are decoded natively, and you can control output size, color palette, and frequency range with flags.

What audio visualization types does songsee support?▼

songsee supports nine visualization types: spectrogram, mel, chroma, hpss, self-similarity, loudness, tempogram, MFCC, and spectral flux. Pass them comma-separated via --viz to render multiple panels as a grid in one image.

Does songsee support audio formats other than WAV and MP3?▼

WAV and MP3 are decoded natively by songsee. For other formats such as FLAC, AAC, or OGG, you need ffmpeg installed so the audio can be decoded before visualization.

How do I visualize only part of an audio file?▼

Use the --start and --duration flags to select a time slice, for example: songsee track.mp3 --start 12.5 --duration 8 -o slice.jpg. This renders only the specified 8-second segment beginning at 12.5 seconds.

Can I pipe audio into songsee from stdin?▼

Yes, songsee accepts stdin input using a dash as the file argument, for example: cat track.mp3 | songsee - --format png -o out.png. This makes it suitable for shell pipelines and scripted audio processing workflows.

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