Generate spectrograms and multi-panel audio feature visualizations from audio files via CLI.
npx skills add https://github.com/ever-oli/io --skill songsee-ever-oli
Please help me install this Agent Skill. Skill: songsee Source: https://github.com/ever-oli/io/tree/main/skills/media/songsee Command: npx skills add https://github.com/ever-oli/io --skill songsee-ever-oli
This skill helps audio professionals and researchers quickly generate spectrograms and multi-panel visualizations from audio files, enabling faster analysis and clearer documentation.
Run songsee on an audio file to generate a multi-panel visualization image.
High-intent search queries and answers about installing and using this skill.
You generate spectrograms from audio files by running a visualization command that outputs multi-panel images, revealing spectral content, tempo, and timbre features for music analysis and quality checks.
Alongside a spectrogram, you can visualize Mel-scale features, chroma for pitch content, MFCC for timbre characteristics, and tempo panels to reveal the rhythmic structure of your audio files.
You need optional ffmpeg installed to process extended audio formats for visualization, while the core spectrogram generation requires the Go environment to install and run the visualization binary.
You can batch process multiple audio files to create comparative spectrograms, enabling comparative studies across different tracks by generating individual multi-panel visualization images for each file.
The best way to document audio analysis results visually is to generate multi-panel images containing spectrograms, chroma, MFCC, and tempo data, providing clear visual documentation for audio professionals.
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