What problem does it solve? Creating a video that stays synchronized with a music track requires manual beat detection, timeline editing, and frame-by-frame alignment. This Skill automates the entire pipeline: it analyzes a music track once, cuts it into frames at real musical changes, plans per-frame visual treatments, and renders a finished MP4 where every cut lands on the beat grid. ## Core Features & Use Cases - Deterministic audio analysis: A Python script (librosa-based) produces a canonical audiomap.json with tempo, beat grid, drum classification, energy phases, rolls, silences, and key moments — the single timing source for the whole video. - Structured multi-step workflow: Six gated steps (setup, analyze, skeleton, plan, build, assemble, render) with validation scripts, a storyboard format, and per-frame sub-agent dispatch for parallel composition building. - Template and motion-primitive catalogs: Typography-first templates and motion primitives cover lyric videos, slideshows, and kinetic promos; user-supplied images/videos are cut onto the same beat grid, and a complete video needs zero assets. - Use Case: Give the Skill a music file and ask for a 30-second kinetic promo; it analyzes the track, plans frames at drops and surges, builds HTML compositions, and renders a beat-synced MP4. ## Quick Start Turn my music track into a beat-synced lyric video and render the final MP4.
