songsee

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

1|Updated Apr 18, 2026
One-click install
npx skills add https://github.com/rnben/hermes-skills --skill songsee-rnben
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: songsee
Source: https://github.com/rnben/hermes-skills/tree/main/plugins/media-skills/skills/songsee
Command: npx skills add https://github.com/rnben/hermes-skills --skill songsee-rnben

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Visualize audio data by generating spectrograms and multi-panel feature visualizations to aid analysis, debugging, and documentation of audio workflows.

Core Features & Use Cases

  • Generate spectrograms, mel, chroma, MFCC, and other audio feature visualizations from audio files.
  • Support multi-panel layouts to compare different analyses side-by-side.
  • Useful for music production debugging, academic research, and media documentation.

Quick Start

Run songsee on an audio file to generate a multi-panel visual analysis.

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 for visual analysis?▼

To generate a spectrogram from an audio file, run the songsee CLI on the file to automatically extract and plot audio features into a multi-panel visual layout for analysis.

Can I visualize MFCC and chroma audio features in a multi-panel layout?▼

Yes, you can visualize MFCC, chroma, and mel features side-by-side by generating multi-panel layouts that compare different audio analyses simultaneously for comprehensive documentation.

Do I need to install the songsee CLI before visualizing audio features?▼

Yes, the songsee CLI must be installed and accessible in your execution environment to process audio files and generate multi-panel audio feature visualizations.

What is the best way to analyze audio features for music production debugging?▼

Analyzing audio features for music production debugging is best achieved by generating spectrograms and multi-panel visualizations, providing visual insight that accelerates understanding of audio workflows.

Can I use audio feature visualization for podcast analysis and sound design workflows?▼

Yes, audio feature visualization is highly effective for podcast analysis and sound design workflows, applying visual insight to accelerate understanding of audio data and streamline documentation.