Generate multi-panel spectrograms and audio feature visualizations from audio files.
npx skills add https://github.com/unclehowell/unclehowell --skill songsee-unclehowell
Please help me install this Agent Skill. Skill: songsee Source: https://github.com/unclehowell/unclehowell/tree/main/skills/media/songsee Command: npx skills add https://github.com/unclehowell/unclehowell --skill songsee-unclehowell
Manually creating detailed spectrograms and audio feature visualizations is time‑consuming and requires specialized tools, hindering quick analysis and documentation of audio content.
Use the songsee skill to generate a multi‑panel spectrogram image for 'track.mp3'.
High-intent search queries and answers about installing and using this skill.
To generate a spectrogram from an mp3 file, you can create a multi-panel visualization image that combines spectrogram, mel, chroma, and MFCC features to provide visual insight into frequency, timbre, and rhythm.
Visualizing MFCC and chroma features is best achieved by combining them into a single multi-panel image, which allows audio engineers to instantly compare processing stages or debug synthesis issues within a track.
You need the songsee command-line tool installed via Go to create audio visualizations, and you optionally need ffmpeg installed to extend support for additional audio formats beyond the default.
You can customize the spectrogram output by adjusting the size, style, frequency range, and time slices via command-line flags, tailoring the visual report to specific audio analysis or documentation tasks.
Limitations include requiring the songsee tool installed via Go and optionally ffmpeg for extended format support, meaning manual command-line execution is necessary rather than using a graphical interface for visualizations.
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