songsee

Convert audio files into spectrograms and mel-spectrograms using songsee CLI.

4|Updated Apr 19, 2026
One-click install
npx skills add https://github.com/ragnarokhaa/hermes --skill songsee-ragnarokhaa
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: songsee
Source: https://github.com/ragnarokhaa/hermes/tree/main/hermes-cerul-tech-news-package/hermes-cerul-tech-news-package/hermes-agent/skills/media/songsee
Command: npx skills add https://github.com/ragnarokhaa/hermes --skill songsee-ragnarokhaa

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill provides a comprehensive toolset for visualizing audio data, helping users analyze and document audio files efficiently.

Core Features & Use Cases

  • Audio Visualization: Generate a variety of visualizations such as spectrograms, mel-spectrograms, and pitch class distributions.
  • Analysis Tools: Useful for audio analysis, music production debugging, and documentation.
  • Use Case: Visualize the frequency content of an audio track to identify specific frequencies or to analyze the timbre of a piece of music.

Quick Start

Generate a spectrogram for 'track.mp3' using songsee.

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 frequency analysis?

You can generate a spectrogram by running visualization commands through the songsee CLI tool. It converts audio files into visual representations to help you identify specific frequencies and analyze the timbre of music tracks.

What is a mel-spectrogram and when is it needed for music production debugging?

A mel-spectrogram is a visual representation of audio data scaled to human auditory perception. It is needed when debugging music production to analyze frequency content and timbre characteristics that standard spectrograms might not highlight effectively.

Can I visualize pitch class distributions for an audio track using command-line tools?

Yes, you can visualize pitch class distributions alongside spectrograms using the songsee command-line tool. It provides comprehensive audio visualization features to document and analyze audio files efficiently directly from the terminal.

Do I need to install the songsee CLI tool to visualize audio data?

Yes, the songsee CLI tool is a required dependency for executing audio visualization commands. The Skill relies on this command-line interface to convert audio files into spectrograms and mel-spectrograms.

What is the best way to analyze the timbre of a piece of music via CLI?

The best way to analyze music timbre via CLI is by generating visual representations like spectrograms and mel-spectrograms. This allows you to visually inspect the frequency content and identify specific acoustic characteristics of the track.