Script To Reel — AI skill for Claude Code
Turn a written script into a finished 9:16 vertical reel.
How to install Script To Reel
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open HariNayan/Script-to-Reel and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What Script To Reel does
Turn a written script into a finished 9:16 vertical reel. An AI-powered Claude skill that generates an illustrated cartoon host, per-beat scene art, labelled props, and word-timed burst captions from a voiceover. Built as a HyperFrames composition and rendered to MP4. Supports Hindi, English, and code-switched speech.
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README
Script to Reel
Turn a written script into a finished 9:16 vertical reel — an illustrated cartoon host, per-beat scene art, labelled props, and word-timed burst captions — built as a HyperFrames composition and rendered to MP4.
This is a **Claude skill** that automates the pipeline from script to short-form video, designed for Reels, Shorts, TikTok, and vertical explainers.
What It Does
Takes a script and produces a vertical narrated explainer:
- A flat-vector cartoon host who gestures through the beats
- One illustrated scene per beat with a text label
- Burst captions (2-3 words) locked to the real voiceover timing
- Everything rendered from authored SVG — resolution-independent, no design drift
Pipeline Overview
Script → Audio → Word Onsets → Caption Chunks → SVG Art + Animation → MP4
| Step | Command | What Happens |
|---|---|---|
| 1. Timing | python scripts/word_timings.py |
Extract word-level onsets via Whisper |
| 2. Captions | python scripts/build_captions.py --cues cues.json --onsets onsets.json |
Chunk into 2-3 word burst frames |
| 3. Art | Author SVG symbols | Character rig + scene props |
| 4. Motion | GSAP timeline | Pose swaps, prop entrances, caption pops |
| 5. Verify | npm run check && npx hyperframes snapshot |
Validate and preview |
Scripts
`word_timings.py`
Extracts word-level onset timestamps from a voiceover file using OpenAI Whisper.
python scripts/word_timings.py assets/voiceover.mp3 --language hi --out onsets.json
- Supports Hindi, English, and code-switched speech
- Transcript text is deliberately discarded — only onset times are used (ASR garbles code-switched speech)
- Outputs
onsets.jsonwith word timestamps as a timing grid
`build_captions.py`
Chunks sentence-level caption cues into 2-3 word burst frames, snapping boundaries to real speech onsets.
python scripts/build_captions.py --cues cues.json --onsets onsets.json
`
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