Generate spectrograms and audio feature visualizations from audio files via CLI.
npx skills add https://github.com/igniteenow/robo --skill songsee-igniteenow
Please help me install this Agent Skill. Skill: songsee Source: https://github.com/igniteenow/robo/tree/main/skills/media/songsee Command: npx skills add https://github.com/igniteenow/robo --skill songsee-igniteenow
High-intent search queries and answers about installing and using this skill.
Run songsee with the audio file as argument, for example songsee track.mp3, and use -o to set the output image path. WAV and MP3 are decoded natively without extra tools.
songsee supports nine types via the --viz flag: spectrogram, mel, chroma, hpss, selfsim, loudness, tempogram, mfcc, and flux. Multiple comma-separated types render together as a grid in one image.
WAV and MP3 are decoded natively by songsee. For other formats such as FLAC or AAC, you need ffmpeg installed so the audio can be converted before visualization.
Use the --start and --duration flags to select a time slice, for example songsee track.mp3 --start 12.5 --duration 8 to render an 8-second segment beginning at 12.5 seconds.
Yes, pipe audio data with a dash as the input, such as cat track.mp3 | songsee - --format png -o out.png. This is useful when chaining with other command-line audio tools.
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