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songsee

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

Updated Mar 22, 2026
Search Tags:#visualization#audio-analysis#spectrogram#mfcc#mel#tempogram
One-click install
npx skills add https://github.com/ChimeraFoundationa/Agentx --skill songsee-chimerafoundationa
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: songsee
Source: https://github.com/ChimeraFoundationa/Agentx/tree/main/skills/media/songsee
Command: npx skills add https://github.com/ChimeraFoundationa/Agentx --skill songsee-chimerafoundationa

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill makes it easy to produce visualizations for audio data, saving time in audio analysis, production debugging, and documentation by generating consistent spectrograms and feature plots from audio files.

Core Features & Use Cases

  • Generate spectrograms (standard, mel) and a suite of audio feature visualizations (MFCC, chroma, tempogram, etc.)
  • Create multi-panel visualization grids for easy comparison, reporting, and debugging of audio processing pipelines
  • CLI-driven workflow suitable for music analysis, sound design, and research documentation

Quick Start

Analyze track.mp3 to produce a full-feature spectrogram visualization and export as PNG.

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 MP3 file?▼

Generating spectrograms from MP3 files requires parsing the audio signal and mapping its frequencies over time. This Skill processes common audio formats like WAV and MP3 to export multi-panel feature visualizations as PNG images.

Can I visualize MFCC and mel spectrograms together in a single image?▼

Visualizing MFCC and mel spectrograms together requires arranging multiple audio feature plots into a single layout. This Skill generates multi-panel visualization grids combining MFCC, chroma, and tempogram plots into one exportable image.

Does audio visualization work with WAV files or do I need additional dependencies?▼

Audio visualization works with WAV files directly, but processing additional formats requires optional ffmpeg integration. A Go toolchain is needed to install the CLI that generates the spectrograms and feature plots.

What is the best way to create visual documentation for audio analysis pipelines?▼

Creating visual documentation for audio analysis pipelines is best achieved by exporting standardized, multi-panel feature plots. This Skill generates consistent spectrograms and visualizations suitable for embedding in research reports and debugging pipelines.

Why do I need a Go toolchain to generate audio spectrograms and feature plots?▼

A Go toolchain is needed to install the underlying CLI that performs the audio processing and visualization. This CLI-driven workflow supports music analysis and research documentation by generating exportable spectrogram and feature plot images.

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