Video-Making: a video skill pack for AI coding agents

One installable agent skill (video-making), scripts and a tested pipeline that let an AI agent (Codex, Claude Code, or any agent that reads SKILL.md files) make narrated, captioned, music-backed videos entirely from code, with free local tools: Kokoro text-to-speech, word-exact karaoke subtitles, canvas animation captured one frame at a time by headless Chrome, ffmpeg mixing at -14 LUFS, and automatic quality checks.

Quick start

git clone https://github.com/namra-030604/Video-Making && cd Video-Making && bash install.sh && bash install.sh verify
bash smoke-test/run.sh            # makes smoke-test/out/project/out/hello-world.mp4 (~7 s) and checks it
bash scripts/new_project.sh my-video && bash scripts/build.sh my-video

install.sh also links the one skill folder into ~/.codex/skills/video-making and/or ~/.claude/skills/video-making (auto-detected; options in bash install.sh --help). Agents: see AGENT_INSTALL.md.

One skill: router -> master video -> components

video-making/
  SKILL.md                     the ONLY skill entry point: a router (keywords -> component -> what to run)
  components/
    master-video/MASTER.md     full end-to-end orchestration (default route for "make a video")
    script-writing/  voice-and-audio/  subtitles-karaoke/  vertical-9-16-framing/  short-form-editing/
    qc-and-render/  lessons-from-failures/  video-production-standard/      (each a COMPONENT.md)
    motion-studio/   COMPONENT.md + templates/ scripts/ references/        (music-led motion pieces)
    motion-graphics/ COMPONENT.md + fx.js + guides/ (18 effect guides) + gallery/ + test/

The router reads the request and sends the agent to one component: script/text, voice/music/SFX/loudness, motion graphics (or the maps guide), music-led promos, captions/karaoke, 9:16 framing, short-form editing, rendering/QC/resume, lessons, the production standard, or (default, for a whole video) the master component. python3 scripts/router_test.py checks the routing table against tests/router_cases.json: it is a deterministic keyword check, not an LLM test.

What you get

Folder	Contents
video-making/	the single skill (router SKILL.md, master component, 10 sub-components, 18 motion guides)
scripts/	the pipeline: make_voice.py, align_words.py, make_audio.py, stills.mjs, render.mjs, subtitle_qc.mjs, qc_final.py, framediff.py, build.sh, new_project.sh; checks: router_test.py, check_links.py
tests/router_cases.json	sample prompts and the component each must route to
lib/browser.mjs	a small dependency-free Chrome DevTools driver (no npm packages needed)
examples/hello-world/	a complete 540x960 narrated scene to copy
smoke-test/run.sh	end-to-end test of the whole pipeline
install.sh	installs and verifies everything (project-local .venv, cache in ~/.cache/video-skill-pack)

Requirements

• Linux x86_64 (tested on Debian 13). macOS/Windows are not supported by install.sh (untested).
• System packages: python3 (3.10+, with venv; tested with 3.13), node (18+; tested with 20.19), ffmpeg with libx264, curl, unzip, sha256sum. install.sh prints the apt-get command if something is missing (it runs it only with --apt).
• About 4 GB free disk and 2 GB free RAM. No GPU, no API keys, no accounts.

Download sizes (first install, cached afterwards)

Item	Size
Python venv (CPU PyTorch, onnxruntime, kokoro-onnx...)	~1.1 GB on disk
Kokoro v1.0 int8 model + voices	~120 MB
MMS_FA alignment model (skip with --skip-aligner)	~1.26 GB
chrome-headless-shell 156.0.8078.47 (only if no usable Chrome)	~126 MB zip, ~270 MB unpacked
Inter + Caveat fonts	~1.3 MB

Important license notes

• The word-alignment model (MMS_FA) is CC-BY-NC 4.0: non-commercial use only. Captions in commercial videos need a different aligner (not included).
• Remotion (optional, --with-remotion) is free only for individuals and organisations of up to 3 people.
• Check the license of every music, SFX, image or footage file you add; the pack's own sounds are synthesized.

License and credits

The pack's own code and docs: MIT. Third-party tools and the projects that inspired parts of the pack are listed with their licenses in CREDITS.md and NOTICE. No third-party code is vendored except where CREDITS.md says so.