SongSee

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

577|62|Updated May 15, 2026
One-click install
npx skills add https://github.com/agentic-in/elephant-agent --skill songsee-agentic-in
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: SongSee
Source: https://github.com/agentic-in/elephant-agent/tree/main/packages/skills/builtin_packages/media/songsee
Command: npx skills add https://github.com/agentic-in/elephant-agent --skill songsee-agentic-in

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Audio analysis and documentation often require manually creating visualizations, which is time-consuming and error-prone. SongSee automates generating spectrograms and multi-panel audio feature visuals from audio files via the CLI, enabling quick inspection and sharing of results.

Core Features & Use Cases

  • Generate standard spectrograms and additional visualizations (mel, chroma, MFCC, tempogram, etc.) from audio files
  • Create multi-panel visualizations and save as image files for reports, debugging, or documentation
  • Use in music production workflows to compare features across tracks or iterations

Quick Start

Generate a spectrogram and multi-panel audio visualizations from an audio file and save the result as an image.

Frequently Asked Questions about SongSee

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

FAQPage Schema
How do I generate spectrograms from audio files using a CLI?

To generate spectrograms from audio files, you need a CLI tool that processes audio and outputs visualizations. SongSee automates spectrogram creation from audio files via the CLI, enabling quick inspection and saving results as image files.

What audio feature visualizations can I create besides standard spectrograms?

Beyond standard spectrograms, you can generate mel, chroma, MFCC, and tempogram visualizations. SongSee creates multi-panel audio feature visuals from audio files, useful for comparing features across tracks or iterations in music production workflows.

Can I save multi-panel audio visualizations as image files for documentation?

Yes, you can save multi-panel audio visualizations as image files. SongSee generates these visuals from audio files and saves the results, making it suitable for visual documentation of audio pipelines, reports, and debugging.

What is the best way to visualize MFCC and chroma features for music production debugging?

The best way to visualize MFCC and chroma features is using a CLI tool that supports multiple visualization types. SongSee automates generating these multi-panel audio feature visuals, enabling quick inspection and sharing of results for debugging.

Do I need any dependencies to create tempogram and mel spectrograms from audio?

No dependencies are required to create tempogram and mel spectrograms. SongSee operates as a standalone Skill, automating the generation of these audio feature visualizations from audio files without needing external components.