/video_toolkit

name: video-toolkit
description: Create professional videos autonomously using claude-code-video-toolkit — AI voiceovers, image generation, music, talking heads, and Remotion rendering.
metadata:
  openclaw:
    emoji: "🎬"
    skillKey: "video-toolkit"
    os: ["darwin", "linux"]
    requires:
      bins: ["node", "python3", "ffmpeg", "npm"]

Video Toolkit

Create professional explainer videos from a text brief. The toolkit uses open-source AI models on cloud GPUs (Modal or RunPod) for voiceover, image generation, music, and talking head animation. Remotion (React) handles composition and rendering.

CRITICAL: Toolkit Path

The toolkit lives at a fixed path. **ALWAYS `cd` here before running any tool command.**

TOOLKIT=~/.openclaw/workspace/claude-code-video-toolkit
cd $TOOLKIT

**NEVER run tool commands from inside a project directory.** Tools resolve paths relative to the toolkit root.

Setup

Step 1: Check Current State

cd ~/.openclaw/workspace/claude-code-video-toolkit
python3 tools/verify_setup.py

If everything shows `[x]`, skip to "Quick Test" below. Otherwise continue setup.

Step 2: Install Python Dependencies

cd ~/.openclaw/workspace/claude-code-video-toolkit
pip3 install --break-system-packages -r tools/requirements.txt

Note: `--break-system-packages` is needed on Debian/Ubuntu with managed Python (PEP 668). Safe inside containers.

Step 3: Configure Cloud GPU Endpoints

The toolkit needs cloud GPU endpoint URLs in `.env`. Check if `.env` exists and has Modal endpoints:

cat ~/.openclaw/workspace/claude-code-video-toolkit/.env | grep MODAL

If Modal endpoints are configured, you're ready. If not, **ask the user to provide Modal endpoint URLs** or set up Modal:

pip3 install --break-system-packages modal
python3 -m modal setup   # Opens browser for authentication

# Deploy each tool — capture the endpoint URL from output
cd ~/.openclaw/workspace/claude-code-video-toolkit
modal deploy docker/modal-qwen3-tts/app.py
modal deploy docker/modal-flux2/app.py
modal deploy docker/modal-music-gen/app.py
modal deploy docker/modal-sadtalker/app.py
modal deploy docker/modal-image-edit/app.py
modal deploy docker/modal-upscale/app.py
modal deploy docker/modal-propainter/app.py
modal deploy docker/modal-ltx2/app.py      # Requires: modal secret create huggingface-token HF_TOKEN=hf_...

**LTX-2 prerequisite:** Before deploying LTX-2, create a HuggingFace secret and accept the [Gemma 3 license](https://huggingface.co/google/gemma-3-12b-it-qat-q4_0-unquantized):

modal secret create huggingface-token HF_TOKEN=hf_your_read_access_token

Add each URL to `.env`:

MODAL_QWEN3_TTS_ENDPOINT_URL=https://...modal.run
MODAL_FLUX2_ENDPOINT_URL=https://...modal.run
MODAL_MUSIC_GEN_ENDPOINT_URL=https://...modal.run
MODAL_SADTALKER_ENDPOINT_URL=https://...modal.run
MODAL_IMAGE_EDIT_ENDPOINT_URL=https://...modal.run
MODAL_UPSCALE_ENDPOINT_URL=https://...modal.run
MODAL_DEWATERMARK_ENDPOINT_URL=https://...modal.run
MODAL_LTX2_ENDPOINT_URL=https://...modal.run

Optional but recommended — Cloudflare R2 for reliable file transfer:

R2_ACCOUNT_ID=...
R2_ACCESS_KEY_ID=...
R2_SECRET_ACCESS_KEY=...
R2_BUCKET_NAME=video-toolkit

Step 4: Verify and Quick Test

cd ~/.openclaw/workspace/claude-code-video-toolkit
python3 tools/verify_setup.py

All tools should show `[x]`. Then run a quick test to confirm the GPU pipeline works:

cd ~/.openclaw/workspace/claude-code-video-toolkit
python3 tools/qwen3_tts.py --text "Hello, this is a test." --speaker Ryan --tone warm --output /tmp/video-toolkit-test.mp3 --cloud modal

If you get a valid .mp3 file, setup is complete. If it fails, check:

• `.env` has the correct `MODAL_QWEN3_TTS_ENDPOINT_URL`
• Run `python3 tools/verify_setup.py --json` and check `modal_tools` for which endpoints are missing

**Cost:** Modal includes $30/month free compute. A typical 60s video costs $1-3.

---

Creating a Video

Step 1: Create Project

cd ~/.openclaw/workspace/claude-code-video-toolkit
cp -r templates/product-demo projects/PROJECT_NAME
cd projects/PROJECT_NAME
npm install

Templates: `product-demo` (marketing/explainer), `sprint-review`, `sprint-review-v2` (composable scenes).

Step 2: Write Config

Edit `projects/PROJECT_NAME/src/config/demo-config.ts`:

export const demoConfig: ProductDemoConfig = {
  product: {
    name: 'My Product',
    tagline: 'What it does in one line',
    website: 'example.com',
  },
  scenes: [
    { type: 'title', durationSeconds: 9, content: { headline: '...', subheadline: '...' } },
    { type: 'problem', durationSeconds: 14, content: { headline: '...', problems: ['...', '...'] } },
    { type: 'solution', durationSeconds: 13, content: { headline: '...', highlights: ['...', '...'] } },
    { type: 'stats', durationSeconds: 12, content: { stats: [{value: '99%', label: '...'}, ...] } },
    { type: 'cta', durationSeconds: 10, content: { headline: '...', links: ['...'] } },
  ],
  audio: {
    backgroundMusicFile: 'audio/bg-music.mp3',
    backgroundMusicVolume: 0.12,
  },
};

Scene types: `title`, `problem`, `solution`, `demo`, `feature`, `stats`, `cta`.

**Duration rule:** Estimate `durationSeconds` as `ceil(word_count / 2.5) + 2`. You will adjust this after generating audio in Step 4.

Step 3: Write Voiceover Script

Create `projects/PROJECT_NAME/VOICEOVER-SCRIPT.md`:

## Scene 1: Title (9s, ~17 words)
Build videos with AI. The product name toolkit makes it easy.

## Scene 2: Problem (14s, ~30 words)
The problem statement goes here. Keep it punchy and relatable.

**Word budget per scene:** `(durationSeconds - 2) * 2.5` words. The -2 accounts for 1s audio delay + 1s padding.

Step 4: Generate Assets

**CRITICAL: All commands below MUST be run from the toolkit root, not the project directory.**

cd ~/.openclaw/workspace/claude-code-video-toolkit

#