songsee

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

Updated Apr 24, 2026
One-click install
npx skills add https://github.com/Harries/hermes-agent --skill songsee-harries
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: songsee
Source: https://github.com/Harries/hermes-agent/tree/main/skills/media/songsee
Command: npx skills add https://github.com/Harries/hermes-agent --skill songsee-harries

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

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

Core Features & Use Cases

  • Visualization types include spectrogram, mel, chroma, hpss, selfsim, loudness, tempogram, mfcc, and flux.
  • CLI-based usage allows generation from single files or pipelines for audio analysis, music production debugging, and visual documentation.
  • Use cases include debugging mixes, documenting processing steps, and comparing audio pipelines.

Quick Start

Use songsee to generate visualizations from an audio file and save the result to an image 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?

Yes, songsee generates loudness, tempogram, and MFCC visualizations from audio files to help debug mixes and document processing steps. These multi-panel outputs provide detailed audio analysis for visual inspection.

How do I visualize audio features like mel, chroma, and MFCC?

You can visualize audio features like mel, chroma, and MFCC by running the songsee CLI tool against your audio files. It supports multiple visualization types including spectrogram, hpss, selfsim, and flux for comprehensive analysis.

Can I use songsee for music production debugging and visual documentation?

Yes, songsee is designed for music production debugging and visual documentation workflows. It generates spectrograms and multi-panel audio feature visualizations to help you debug mixes and compare audio pipelines.

What do I need to install to start visualizing audio with spectrograms?

To start visualizing audio, you need to install the songsee CLI using Go with the command go install github.com/steipete/songsee/cmd/songsee@latest. This sets up the environment to generate visualizations from single files or pipelines.

Are there limitations when generating tempogram or loudness visualizations from audio pipelines?

The metadata does not specify explicit limitations for generating tempogram or loudness visualizations. The tool supports CLI-based generation from single files or pipelines for audio analysis and visual documentation workflows.