songsee

Generate spectrograms and feature-panel visualizations from audio files via the songsee CLI.

1|Updated Jan 28, 2026

Search Tags:#cli #visualization #audio #generate #signal-processing #spectrogram

Ready to run

npx skills add https://github.com/Zentin-L/Masterbot --skill songsee-zentin-l

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: songsee
Source: https://github.com/Zentin-L/Masterbot/tree/main/skills/songsee
Command: npx skills add https://github.com/Zentin-L/Masterbot --skill songsee-zentin-l

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Generate spectrograms and feature-panel visualizations from audio data to simplify analysis and communication of acoustic content.

Core Features & Use Cases

Generate spectrograms from audio files to visualize spectral content over time.
Produce feature panels (mel, chroma, loudness, etc.) for quick analysis and comparison.
Use in research, education, and content creation to annotate and share insights from audio data.

Quick Start

Run songsee track.mp3 to generate a spectrogram and feature-panel visuals.

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?▼

To generate a spectrogram from an audio file, run the songsee CLI with your track, such as `songsee track.mp3`. This processes the audio data to render visual spectral content over time for acoustic analysis.

What audio formats can I use to generate spectrograms and feature panels?▼

You can use common audio formats to generate spectrograms and feature panels. The songsee CLI accepts standard audio files to visualize spectral content and features like mel, chroma, and loudness for analysis.

What features can I visualize from audio data for music analysis?▼

For music analysis, you can visualize feature panels including mel, chroma, and loudness from audio data. These multi-panel visualizations accelerate acoustic analysis by simplifying spectral content comparison.

Does the songsee CLI support multi-panel visualizations for acoustic analysis?▼

Yes, the songsee CLI supports multi-panel visualizations for acoustic analysis. You can render defined feature panels alongside spectrograms by using specific flags to accelerate audio research and teaching.

When do I need to generate spectrograms for audio research?▼

You need to generate spectrograms for audio research when you want to quickly visualize spectral content over time. This simplifies the analysis and communication of acoustic content in education and music analysis.