Generate multi-panel spectrogram visualizations from audio files.
npx skills add https://github.com/huidge/hermes-skills --skill songsee-huidge
Please help me install this Agent Skill. Skill: songsee Source: https://github.com/huidge/hermes-skills/tree/main/media/songsee Command: npx skills add https://github.com/huidge/hermes-skills --skill songsee-huidge
Generate multi-panel spectrogram visualizations from audio files to aid analysis, debugging, and visual documentation.
Run songsee track.mp3 to generate a multi-panel visualization image.
High-intent search queries and answers about installing and using this skill.
To generate multi-panel spectrogram visualizations, you can run the songsee command on an audio file like an MP3 to produce a single image comparing multiple audio features for analysis and debugging.
You can visualize spectrogram, mel, chroma, MFCC, tempogram, hpss, selfsim, loudness, and flux features together in a single panel to compare tempo and timbre across track sections.
You need FFmpeg as an optional dependency to decode unsupported audio formats into a compatible state before generating spectrogram visualizations, alongside the required Go binary installation.
Spectrogram visualizations are highly useful for visual documentation of audio processing pipelines, allowing you to capture and compare multi-panel representations of various audio features.
The best way to compare tempo and timbre is by generating a multi-panel visualization that renders chroma and tempogram data side-by-side, providing a comprehensive view of track characteristics.
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