songsee

Generate spectrograms and audio feature visualizations from audio files.

Updated Feb 18, 2026
One-click install
npx skills add https://github.com/ClaudioCeppi83/kora-os-kernel --skill songsee-claudioceppi83
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: songsee
Source: https://github.com/ClaudioCeppi83/kora-os-kernel/tree/main/engines/openclaw/skills/songsee
Command: npx skills add https://github.com/ClaudioCeppi83/kora-os-kernel --skill songsee-claudioceppi83

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires songsee, and includes scripts (resource) and assets (resource) components.

What problem does it solve?

songsee simplifies the process of generating spectrograms and feature-panel visualizations from audio files.

Core Features & Use Cases

  • Spectrogram Generation: Automatically creates spectrograms from audio files.
  • Feature Visualization: Visualizes various audio features like melody, rhythm, and frequency.
  • Custom Outputs: Allows users to specify different visualizations and format outputs.
  • Use Case: Ideal for audio analysts or musicologists needing to quickly visualize audio features for research or analysis.

Quick Start

Run the songsee command with an audio file to create a spectrogram. For example: songsee input.mp3

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?

To generate a spectrogram from an audio file, run the `songsee` command with your input file. This automatically creates visual representations of audio features like melody and rhythm for analysis.

Do I need ffmpeg to create audio visualizations?

You need ffmpeg to create audio visualizations only when processing additional audio formats. The core spectrogram generation requires the songsee binary, while ffmpeg extends support to broader file types.

What audio features can I visualize for music analysis?

You can visualize audio features such as melody, rhythm, and frequency for music analysis. The tool generates spectrograms and mel spectrograms to help musicologists quickly research audio characteristics.

Can I specify custom output formats for mel spectrograms?

Yes, you can specify custom outputs for mel spectrograms. The tool allows users to define different visualizations and format outputs to suit specific audio feature analysis requirements.

What is the best way to analyze audio features without manual processing?

The best way to analyze audio features without manual processing is using an automated visualization tool. Running `songsee input.mp3` instantly generates feature-panel visualizations for immediate research.