---
name: video-edit
description: Edit any video into a captioned showcase — transcribe (any language, defaults to large-v3), present a transcript_review.txt for the user to fix mishears BEFORE rendering, then build a HyperFrames composition with liquid-glass caption pills, liquid blob background, liquid morph wipes, optional behind-subject text via background removal, and render the final video. Use whenever the user provides a video file and asks to edit it, caption it, add subtitles, fix existing captions, make a reel/promo/captioned tutorial, or "do the same" pattern as a prior captioned video. Supports English, Hebrew, and any Whisper-supported language. **Renders both 16:9 (YouTube / horizontal) and 9:16 (TikTok / Instagram Reels / YouTube Shorts) from the SAME 16:9 source** — vertical mode uses a centered footage strip with a blurred backdrop + liquid blobs and a vertical-tuned caption pill, no need to re-shoot. THE PIPELINE PAUSES FOR USER APPROVAL on the transcript before final render — this is the support mechanism for getting captions perfect (especially Hebrew). Pairs with hyperframes, hyperframes-cli, hyperframes-registry, and yuv-design-system skills.
---

# Video Edit — Captioned Showcase Pipeline

End-to-end captioned video editor on top of HyperFrames. The user gives you a video; you orchestrate transcribe → review → render and ALWAYS pause for transcript approval before the long render.

## Where this skill sits in the YUV.AI pyramid

`video-edit` is in the **middle tier** of the YUV.AI skills pyramid alongside `yuv-design-system`, `yuv-decks`, `yuv-viral-video`, `parallax-landing-page`, and `video-to-landing-page`. The top-tier orchestrator `yuv-pilot` routes here whenever the user wants a captioned showcase, tutorial, or talking-head edit with subtitles.

This is the more general video sibling to `yuv-viral-video`. The split:
- `yuv-viral-video` — opinionated YUV.AI viral-short pipeline (MrBeast pacing, signature editorial style)
- `video-edit` — general captioned editor with transcript-review-before-render (Hebrew + English + any Whisper language)

For YUV.AI-branded captioned video, pair this skill with `yuv-design-system` (Neon mode for type/palette decisions). For generic / third-party captioned video, this skill works standalone.

## When to invoke

- A path to a video file (mp4/mov/mkv) + a request to "edit", "caption", "add subtitles", "make a reel/promo", "do the same"
- "Fix the captions / Hebrew misspells" — re-enter at the review step on an existing project
- Any captioned tutorial / talking-head / promo build

## Save location

**Default:** `~/Documents/yuv-projects/videos/<slug>/` — always save captioned video projects here so renders are findable. The `<slug>` is short, derived from the topic or source filename.

```bash
mkdir -p ~/Documents/yuv-projects/videos
cd ~/Documents/yuv-projects/videos
# Initialize the project here.
```

Final render lands at `~/Documents/yuv-projects/videos/<slug>/renders/<name>_FINAL.mp4`. Tell the user where the video lives at the end of the render.

---

## Workflow (12 steps)

1. **Probe the source** — `ffprobe` for dimensions, fps, duration, audio.
2. **Scaffold** — `cd ~/Documents/yuv-projects/videos && npx hyperframes init <slug> --video <path> --non-interactive`. Rename the copied video to `source.mp4`.
3. **Extract audio** — `ffmpeg -i source.mp4 -vn -ac 1 -ar 16000 audio.wav`.
4. **Transcribe** — copy `references/transcribe.py` into the project. Default model `large-v3` (best Hebrew). CUDA usually fails on Windows (missing cuDNN); the script falls back to CPU int8. Force `language="he"` for Hebrew, `language="en"` for English; otherwise auto-detect.
5. **Apply known corrections** — copy `references/corrections-hebrew.md` content into a `corrections.json` at the project root (keys = wrong token, values = correct token).
6. 🛑 **STOP — start the review server and let the user approve in a webapp.**
   First apply known corrections: copy `references/make_review.py` into the project and run
   `python make_review.py`. It applies `corrections.json` to `transcript.json`.

   Then spawn the review server **as a background task** (it blocks until the user clicks
   "Approve & Render" in the browser):
   ```bash
   python "$HOME/.claude/skills/video-edit/references/serve_review.py" .
   # On Windows: python "C:\Users\<you>\.claude\skills\video-edit\references\serve_review.py" .
   ```
   The server prints a line like `REVIEW_URL=http://localhost:PORT/`. Grab that URL from
   the background-task output (or read stdout) and send the user:

   > 👉 Review your transcript here: **http://localhost:PORT/**
   > When you click **Approve & Render**, I'll continue automatically.

   The agent **does not need a "continue" message** — when the user clicks the button, the
   server writes `transcript_review.txt` to the project dir AND exits with code 0. The
   agent's background-task notification fires, and the pipeline resumes from step 8.

   **Fallback if no browser / no server**: open the editor as a static file
   (`start "" "$HOME/.claude/skills/video-edit/transcript-editor/index.html"`),
   ask the user to pick the project folder, edit, save `transcript_review.txt` back into
   the project, and reply "continue". The editor supports both modes.

7. **(Optional) Background removal** — see step 7 below; can run in parallel with the user's
   review.

8. After approval, run `python references/apply_review.py`. It re-tokenises edited lines and
   redistributes word timings back into `transcript.json` so caption sync still works.
7. **(Optional) Background removal** — if any talking-head segment needs behind-subject text, extract the segment as `outro.mp4` (or `intro.mp4`) and run `npx hyperframes remove-background <clip>.mp4 -o <name>_subject.webm --quality best`. CPU only on most setups (~3–8 min for a ~15s 1440p clip).
8. **Re-encode source with dense keyframes** — multi-worker render seeks freeze on sparse keyframes. Always run:
   ```bash
   ffmpeg -y -i source.mp4 -c:v libx264 -preset medium -crf 18 -r 30 -g 30 -keyint_min 30 -sc_threshold 0 -pix_fmt yuv420p -movflags +faststart -c:a copy footage.mp4
   ```
9. **Re-load the (edited) transcript** and generate the body sub-composition via `references/gen_body.py`. The generator emits the full `compositions/components/caption-body.html` with editorial + matrix alternating in liquid-glass pills, anchored lower-left-of-centre (clears bottom-right webcam PiPs).
10. **Wire the host `index.html`** from `references/host-template.html`. Layer order (z-index, NOT track-index):
    - z0: footage `.cam-bg`
    - z1: liquid blob background (`compositions/liquid-blobs.html`, `mix-blend-mode: screen`, full duration)
    - z2: parallax behind-subject caption (intro and/or outro, when bg-removal used)
    - z3: subject cut-out `.cam-out` / `.cam-sub` (with matching `data-media-start`)
    - z6: body captions
    - z46: progress bar + flash + liquid morph wipe
11. **Lint** — `npx hyperframes lint`. Must be 0 errors. Common fixes: GSAP/CSS transform conflict on the wipe element (use `xPercent/yPercent` or remove the CSS transform); overlapping tweens on the same property (add `overwrite: "auto"`).
12. **Render** — `npx hyperframes render --quality standard --fps 30 --output renders/<name>_FINAL.mp4`. Standard is the right delivery target — `high` roughly doubles render time. Verify with 6–8 spot-check frames from across the timeline before reporting done.

### Vertical (9:16) output for TikTok / Reels / Shorts

When the user asks for vertical / portrait / TikTok / Reels / 9:16 output (from a 16:9 source):

1. Clone the project to a sibling folder: `cp -r project/ project-vertical/`.
2. Replace its `index.html` with `references/host-template-vertical.html` (1080×1920 canvas, blurred-bg backdrop with liquid blobs, the 16:9 footage as a centered horizontal strip, captions below).
3. Replace its `gen_body.py` with `references/gen_body_vertical.py` (centered pill, larger fonts, narrower max-width), then re-run it to emit `compositions/components/caption-body.html`.
4. Drop the behind-subject cut-out + parallax sub-compositions (the cutout is aligned for 16:9; not worth re-aligning for v1). The vertical comp uses the blurred-source backdrop + blobs for atmosphere instead.
5. Update `data-duration` to the actual video duration. Update the brand-chip text in `index.html` (`YUV.AI` by default).
6. Lint + render — same commands. Output is `1080×1920`. Drop straight onto TikTok / IG Reels / YT Shorts.

To deliver **both** 16:9 and 9:16 in one go, run two render commands (in parallel projects). The transcript_review.txt approval applies to both — same captions, two compositions.

## Critical rules

- **Never render the final without explicit transcript approval.** The review step is the whole point.
- For Hebrew: `large-v3` + `language="he"` + `direction: rtl` + Rubik (700 + 900 for editorial dual-weight emphasis).
- Caption pills always need an opaque dark backing — bare light text vanishes on white app UI.
- Centre caption pills horizontally but shift the centre x-coord left (e.g. `left: 720px`) when the footage has a bottom-right webcam PiP.
- The behind-subject cut-out clip MUST carry `data-media-start` matching its `data-start` (or matching the offset from the source if the clip was extracted), or the cut-out plays from frame 0 and desyncs.
- The `remove-background` webm keeps the original RGB and writes only the alpha mask — `ffprobe` reports `yuv420p`, which looks like "no alpha". Confirm via `TAG:ALPHA_MODE=1` or composite over a solid colour.
- Outro/end cards with burned-in text — do NOT caption over them; they collide.

## File references

| File | Purpose |
| --- | --- |
| `transcript-editor/index.html` | **Interactive browser editor** — video preview, RTL editing, dictionary apply, optional WebLLM AI suggestions, saves `transcript_review.txt` |
| `references/setup.md` | Prerequisites + install commands for Node / Python / FFmpeg / faster-whisper |
| `references/transcribe.py` | faster-whisper transcribe with CPU fallback + word timestamps |
| `references/serve_review.py` | **Local review server** — auto-loads editor, blocks until user clicks Approve & Render, then writes `transcript_review.txt` and exits (signals the agent) |
| `references/make_review.py` | Apply corrections + emit `transcript_review.txt` (file-mode fallback) |
| `references/apply_review.py` | Parse edited review file, redistribute word timings, update `transcript.json` |
| `references/gen_body.py` | Caption-body generator (editorial + matrix in liquid-glass pills) |
| `references/host-template.html` | **16:9** host composition with liquid effects + transition wipe |
| `references/host-template-vertical.html` | **9:16** host (1080×1920) — TikTok / Reels / Shorts layout: blurred bg, centered 16:9 footage strip, captions below, brand chip top-right |
| `references/gen_body_vertical.py` | Caption-body generator tuned for vertical (centered pill, larger fonts, narrower max-width) |
| `references/liquid-blobs.html` | Full-duration drifting blob layer |
| `references/caption-parallax-outro.html` | Behind-subject caption template (English; clone for other languages) |
| `references/corrections-hebrew.md` | Known Hebrew Whisper mishears |
| `references/transcript-review-workflow.md` | The pause/approve step in detail |