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video-add-captionslisted

Add word-timed captions to an Open Recut program. Use this skill to map the canonical transcript through timeline.json, review a maintained style on source-backed pixels, render a local transparent HyperFrames PNG sequence, and register it as an overlay contribution for the shared delivery render.
WhiteTowerAI/cut-as-code · ★ 7 · Code & Development · score 75
Install: claude install-skill WhiteTowerAI/cut-as-code
# Video Add Captions ## Dependencies `/video-understand` is a prerequisite. Run it first so captions use the validated word-level transcript and canonical timeline. Before starting, verify that it is installed. If it is not, warn the user that this prerequisite is missing and stop before processing media. Require `ffmpeg`/`ffprobe` on PATH, Python with `Pillow`, and Node.js >= 22 (for the `.mjs` scripts and `npx hyperframes`, fetched on demand). `hyperframes render`/`snapshot` drives a headless Chrome — it manages its own `chrome-headless-shell`, and falls back to a system Chrome (set `CHROME` to override) when the cached one is unusable. Check these before processing media. ## Scope This skill owns caption grouping, style selection, review, and the transparent caption track. It does not transcribe, cut, retime, grade, reframe, or choose the delivery audio policy. If a cut exists, caption the active program timeline; do not treat source transcript seconds as program seconds. ## Protocol Inputs Required: - `work/project.json` - `work/understand/transcript.json`, with word-level source timestamps - `work/understand/media.json` - `work/timeline.json` - the source video named by `work/project.json` The timeline is the only source-to-program mapping. All ranges are half-open `[start_s, end_s)`. `scripts/build_captions.py` uses the shared `projectlib.map_transcript_to_timeline`; words in dropped source ranges disappear, retained words move to program time, and cues always