skills.rest
chebizarro
chebizarroCOMMUNITY
Explore all skills by this author →
WebsiteGitHub

songsee

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

Updated Mar 2, 2026
Search Tags:#visualization#signal processing#audio#feature extraction#spectrogram
One-click install
npx skills add https://github.com/chebizarro/swarmstr --skill songsee-chebizarro
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: songsee
Source: https://github.com/chebizarro/swarmstr/tree/main/skills/songsee
Command: npx skills add https://github.com/chebizarro/swarmstr --skill songsee-chebizarro

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps users visualize audio data by generating spectrograms and other feature-panel visualizations, making complex audio information more accessible.

Core Features & Use Cases

  • Spectrogram Generation: Create detailed spectrograms from audio files.
  • Multi-Panel Visualizations: Generate a grid of various audio features like mel, chroma, loudness, and MFCC.
  • Audio Slicing: Extract specific time segments from audio for focused analysis.
  • Use Case: A musician can use this Skill to analyze the frequency content of a track over time, or a sound designer can visualize different acoustic features to identify specific sonic characteristics.

Quick Start

Generate a spectrogram from the audio file 'track.mp3'.

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, you use this Skill to process audio inputs and create detailed visual representations of acoustic data. It extracts frequency features over time to visualize audio signal information.

What audio features can I visualize besides a standard spectrogram?▼

Besides a standard spectrogram, you can visualize multi-panel audio features like mel, chroma, loudness, and MFCC. These feature-panel visualizations generate a grid layout to help analyze specific sonic characteristics.

Can I extract and visualize a specific time segment from an audio track?▼

Yes, you can extract and visualize a specific time segment from an audio track using audio slicing. This feature extracts focused time segments from audio files to analyze specific frequency content.

Do I need to install any specific software to generate mel and MFCC visualizations?▼

Yes, generating mel and MFCC visualizations requires the songsee binary to be installed in your environment. The Skill relies on this command-line interface to execute audio feature extraction and format control.

What is the best way to analyze the frequency content of a track over time?▼

The best way to analyze the frequency content of a track over time is by generating a spectrogram. This process visualizes audio data by mapping frequency amplitudes across the duration of an audio signal.

Related Skills

Explore More Design & Creative Skills→
SafeAI-Lab-XSafeAI-Lab-X
1.0k

songsee

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

Community
Intermediate
quiznatquiznat

songsee

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

Community
Intermediate
yunseo-kimyunseo-kim
1

songsee

Generate spectrograms and feature-panel visualizations from audio files.

Community
Intermediate
okgoogle13okgoogle13
1

figma-to-component

Generate React component files from Figma Inspect panel details.

Community
Intermediate