Agent skill · nousresearch
songsee
Audio spectrograms/features (mel, chroma, MFCC) via CLI.
What it needs
About 1k tokens when loaded.
What this skill does
songsee Generate spectrograms and multi-panel audio feature visualizations from audio files. Prerequisites Requires Go: Optional: ffmpeg for formats beyond WAV/MP3. Quick Start Visualization Types Use --viz with comma-separated values: Type Description ------ ------------- spectrogram Standard frequency spectrogram mel Mel-scaled spectrogram chroma Pitch class distribution hpss Harmonic/percussive separation selfsim Self-similarity matrix loudness Loudness over time tempogram Tempo estimation mfcc Mel-frequency cepstral coefficients flux Spectral flux (onset detection) Multiple --viz types render as a grid in a single image. Common Flags Flag Description ------ ------------- --viz Visualization types (comma-separated) --style Color palette: classic, magma, inferno, viridis, gray --width / --height Output image dimensions --window / --hop FFT window and hop size --min-freq / --max-freq Frequency range filter --start / --duration Time slice of the audio --format Output format: jpg or png -o Output file path Notes WAV and MP3 are decoded natively; other formats require ffmpeg Output images can be inspected with visionanalyze for automated audio analysis Useful for comparing audio outputs, debugging synthesis, or documenting audio processing pipelines
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nousresearch/songsee--67ab65