What problem does it solve? Analyzing audio files for music-information-retrieval attributes like tempo, musical key, and song structure normally requires specialized tools and signal-processing knowledge. This Skill turns any WAV, MP3, FLAC, or OGG file into a structured analysis with BPM, detected key, section boundaries, and spectrogram-style visualizations. ## Core Features & Use Cases - Tempo Detection: Computes BPM from an onset-strength envelope via autocorrelation, reporting one-decimal precision with a confidence ratio. - Key Estimation: Builds a 12-bin chroma vector and cross-correlates it against Krumhansl-Schmuckler major and minor profiles to report the most likely key. - Section Segmentation: Detects structural boundaries from RMS energy and self-similarity, labeling sections as intro, verse, chorus, bridge, or outro. - Structured Output: Produces a human-readable Markdown analysis plus a machine-readable sections.json companion. - Use Case: Given a demo track, generate an analysis.md with BPM, key, and a section table, plus a sections.json file for downstream processing. ## Quick Start Analyze the attached song.wav file and report its BPM, musical key, and section structure in a Markdown summary and a sections.json file.
