What problem does it solve? Turning raw audio files into visual representations like spectrograms and feature panels normally requires writing custom signal-processing code. This Skill wraps the songsee CLI so you can produce publication-ready audio visualizations with a single command. ## Core Features & Use Cases - Spectrogram Generation: Render a spectrogram from any audio file with one command, with control over palette, size, FFT window, and frequency range. - Multi-Panel Feature Grids: Combine visualizations such as mel, chroma, HPSS, self-similarity, loudness, tempogram, MFCC, and flux into a single grid image. - Time Slicing and Streaming: Visualize a specific time range with --start and --duration, or pipe audio via stdin for scripted pipelines. - Use Case: A music researcher wants to compare the spectral structure of several tracks. They run songsee on each MP3 with the mel and chroma panels enabled and collect the resulting JPG grids for their analysis report. ## Quick Start Ask the assistant to generate a spectrogram of your audio file, for example: create a spectrogram of track.mp3 using songsee and save it as a PNG.
