songsee

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

Updated Mar 24, 2026

Search Tags:#cli #visualization #audio #chroma #spectrogram #mfcc #mel

Ready to run

npx skills add https://github.com/1thirteeng3/greenmoire --skill songsee-1thirteeng3

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: songsee
Source: https://github.com/1thirteeng3/greenmoire/tree/main/integrations/hermes-agent/skills/media/songsee
Command: npx skills add https://github.com/1thirteeng3/greenmoire --skill songsee-1thirteeng3

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Generate quick, interpretable visual representations of audio content by creating spectrograms and multiple audio feature visualizations from input audio files.

Core Features & Use Cases

Visualize frequency content with spectrograms (and multi-panel grids of mel, chroma, MFCC, tempogram, etc.) for debugging, music analysis, and documentation.
CLI-driven workflow: generate outputs directly from audio files or streams for rapid analysis and reporting.
Use Case: produce a visual report of a track's timbre and rhythm for music production notes or educational materials.

Quick Start

Install and run the tool via its CLI to generate a spectrogram from an audio file.

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 audio file using a CLI?▼

Audio feature visualization displays timbre and rhythm characteristics by plotting mel, chroma, MFCC, and tempogram data in multi-panel grids. It is needed for music production debugging, audio analysis, and creating visual documentation for educational materials.

Do I need ffmpeg to visualize MP3 and WAV audio files?▼

You do not need ffmpeg to visualize MP3 and WAV audio files, as the tool supports decoding these formats natively. FFmpeg is only required as an optional dependency for decoding other audio formats beyond MP3 and WAV.

Can I generate multi-panel audio feature grids showing mel, chroma, and MFCC?▼

Yes, you can generate multi-panel audio feature grids showing mel, chroma, MFCC, and tempogram visualizations. These grids provide a comprehensive visual report of a track's frequency content, timbre, and rhythm.

What's the best way to document audio analysis for music production notes?▼

The best way to document audio analysis is by generating multi-panel visual reports of spectrograms and audio features as image files. These visual representations provide interpretable documentation of a track's timbre and rhythm for production notes.

How do I install and run the songsee CLI for audio visualization?▼

Install the songsee CLI using go install github.com/steipete/songsee/cmd/songsee@latest. Once installed, run the tool from your command line to generate spectrograms and audio feature visualizations from your input audio files.