songsee

Generate spectrograms and audio feature visualizations from audio files.

Updated Jun 28, 2026
One-click install
npx skills add https://github.com/jleechanorg/hermes-agent --skill songsee-jleechanorg
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: songsee
Source: https://github.com/jleechanorg/hermes-agent/tree/main/skills/media/songsee
Command: npx skills add https://github.com/jleechanorg/hermes-agent --skill songsee-jleechanorg

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

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

Core Features & Use Cases

  • Automated Visualization: Produce spectrograms, mel spectrograms, chroma, MFCCs, and more to analyze audio content.
  • Batch and Single-file Processing: Process individual tracks or multiple files in a grid layout for comparative analysis.
  • Use Case: Ideal for music analysis, audio research, and speech processing pipelines needing quick visual summaries.

Quick Start

Generate a spectrogram image from the input file track.mp3 using the songsee CLI.

Frequently Asked Questions about songsee

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate spectrograms and audio feature visualizations from an audio file?▼

You generate spectrograms and audio feature visualizations by running the songsee CLI on individual tracks or multiple files in a batch workflow, producing multi-panel visual summaries for audio analysis.

What audio features can I visualize for music analysis and speech processing?▼

For music analysis and speech processing, you can visualize spectrograms, mel spectrograms, chroma, and MFCCs to analyze audio content and generate quick visual summaries.

Do I need to install Go to run spectrogram generation locally?▼

Yes, you need to install Go to run spectrogram generation locally, specifically by using the command go install github.com/steipete/songsee/cmd/songsee@latest to set up the required songsee CLI environment.

Can I process multiple audio files in a batch workflow for comparative spectrogram analysis?▼

Yes, you can process multiple audio files in a batch workflow for comparative spectrogram analysis, which arranges the output visualizations in a grid layout to compare audio features across tracks.

What is the best way to extract MFCCs and chroma features for visual audio analysis?▼

The best way to extract MFCCs and chroma features for visual audio analysis is using a CLI tool that automates the generation of multi-panel visualizations directly from your source audio files.