What problem does it solve? Turning raw audio 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 spectrograms from WAV or MP3 files with configurable FFT window, hop size, and frequency range. - Multi-Panel Feature Grids: Combine mel, chroma, HPSS, self-similarity, loudness, tempogram, MFCC, and flux visualizations into one grid image. - Time Slicing & Styling: Extract specific time ranges and apply color palettes (classic, magma, inferno, viridis, gray) at custom output sizes. - Use Case: A music researcher wants to compare the spectral structure of two recordings; they generate side-by-side mel and chroma panels for each track as PNG images for a paper. ## Quick Start Ask the assistant to generate a spectrogram from your audio file, for example: create a spectrogram of track.mp3 using songsee and save it as a PNG.
