songsee

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

6|Updated Apr 26, 2026

Search Tags:#cli #visualization #audio #spectrogram #music-analysis #audio-features

Ready to run

npx skills add https://github.com/Strategic-Automation/arachne --skill songsee-strategic-automation

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: songsee
Source: https://github.com/Strategic-Automation/arachne/tree/main/src/arachne/skills/default/media/songsee
Command: npx skills add https://github.com/Strategic-Automation/arachne --skill songsee-strategic-automation

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Transforms audio into visual representations to accelerate analysis, debugging, and documentation workflows.

Core Features & Use Cases

Visualization: generate spectrograms and multi-panel audio feature visualizations from audio files.
CLI workflow: operate via a single binary with flexible options (viz, start, duration, output).
Use Case: quickly analyze music collections or debug audio pipelines by visualizing features like mel, chroma, MFCC, and more.

Quick Start

Run songsee on an audio file to generate a multi-panel spectrogram visualization.

Frequently Asked Questions about songsee

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

FAQPage Schema

How do I generate multi-panel spectrograms from audio files for music analysis?▼

Multi-panel spectrograms visualize audio features like mel, chroma, and MFCC from audio files. This process transforms audio into visual representations to accelerate analysis, debugging, and documentation workflows in music production.

What audio features can I visualize for debugging audio pipelines?▼

You can visualize audio features including mel, chroma, MFCC, and spectrograms. These visual representations help debug audio pipelines and document workflows by exposing specific audio characteristics across multi-panel layouts.

Do I need ffmpeg to visualize audio files with spectrograms?▼

ffmpeg is optional but provides broader audio format support. The core spectrogram visualization requires the Go-based songsee CLI binary, while ffmpeg extends the range of input audio formats you can analyze.

Can I specify a start time and duration when generating audio spectrograms?▼

Yes, the CLI provides flexible options including start, duration, viz, and output parameters. This allows you to generate spectrograms and audio feature visualizations for specific segments of an audio file rather than the entire track.

What is the best way to visualize audio features for music production debugging?▼

Using a single CLI binary to generate multi-panel spectrograms is an efficient way to visualize audio features for music production debugging. It transforms audio into visual representations to accelerate analysis and documentation workflows.

Are there limitations when generating spectrograms from audio files without ffmpeg?▼

Without ffmpeg, spectrogram generation is limited to audio formats natively supported by the Go-based CLI. Installing ffmpeg removes this constraint and enables broader audio format support for visualization workflows.