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:

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

4a. Background Music

cd ~/.openclaw/workspace/claude-code-video-toolkit
python3 tools/music_gen.py \
  --preset corporate-bg \
  --duration 90 \
  --output projects/PROJECT_NAME/public/audio/bg-music.mp3 \
  --cloud modal

Presets: corporate-bg, upbeat-tech, ambient, dramatic, tension, hopeful, cta, lofi.

4b. Voiceover (per-scene)

Generate ONE .mp3 file PER SCENE. Do NOT generate a single voiceover file.

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

# Scene 01
python3 tools/qwen3_tts.py \
  --text "The voiceover text for scene one." \
  --speaker Ryan --tone warm \
  --output projects/PROJECT_NAME/public/audio/scenes/01.mp3 \
  --cloud modal

# Scene 02
python3 tools/qwen3_tts.py \
  --text "The voiceover text for scene two." \
  --speaker Ryan --tone warm \
  --output projects/PROJECT_NAME/public/audio/scenes/02.mp3 \
  --cloud modal

# ... repeat for each scene

Speakers: Ryan, Aiden, Vivian, Serena, Uncle_Fu, Dylan, Eric, Ono_Anna, Sohee Tones: neutral, warm, professional, excited, calm, serious, storyteller, tutorial

For voice cloning (needs a reference recording):

cd ~/.openclaw/workspace/claude-code-video-toolkit
python3 tools/qwen3_tts.py \
  --text "Text to speak" \
  --ref-audio assets/voices/reference.m4a \
  --ref-text "Exact transcript of the reference audio" \
  --output projects/PROJECT_NAME/public/audio/scenes/01.mp3 \
  --cloud modal

4c. Scene Images

cd ~/.openclaw/workspace/claude-code-video-toolkit
python3 tools/flux2.py \
  --prompt "Dark tech background with blue geometric grid, cinematic lighting" \
  --width 1920 --height 1080 \
  --output projects/PROJECT_NAME/public/images/title-bg.png \
  --cloud modal

Image presets (use --preset instead of --prompt --width --height): title-bg, problem, solution, demo-bg, stats-bg, cta, thumbnail, portrait-bg

cd ~/.openclaw/workspace/claude-code-video-toolkit
python3 tools/flux2.py \
  --preset title-bg \
  --output projects/PROJECT_NAME/public/images/title-bg.png \
  --cloud modal

4d. Video Clips — B-Roll & Animated Backgrounds (optional)

Generate AI video clips for b-roll cutaways, animated slide backgrounds, or intro/outro sequences:

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

# B-roll clip from text
python3 tools/ltx2.py \
  --prompt "Aerial drone shot over a European city at golden hour, cinematic wide angle" \
  --output projects/PROJECT_NAME/public/videos/broll-europe.mp4 \
  --cloud modal

# Animate a slide/screenshot (image-to-video)
python3 tools/ltx2.py \
  --prompt "Gentle particle effects, soft ambient light shifts, very slight camera drift" \
  --input projects/PROJECT_NAME/public/images/title-bg.png \
  --output projects/PROJECT_NAME/public/videos/animated-title.mp4 \
  --cloud modal

# Abstract intro/outro background
python3 tools/ltx2.py \
  --prompt "Dark moody abstract background with flowing blue light streaks, bokeh particles, cinematic" \
  --output projects/PROJECT_NAME/public/videos/intro-bg.mp4 \
  --cloud modal

Use in Remotion compositions with <OffthreadVideo>:

<OffthreadVideo src={staticFile('videos/broll-europe.mp4')} />

LTX-2 rules:

• Max ~8 seconds per clip (193 frames at 24fps). Default is ~5s (121 frames).
• Width/height must be divisible by 64. Default: 768x512.
• ~$0.20-0.25 per clip, ~2.5 min generation time.
• Cold start ~60-90s. Subsequent clips on warm GPU are faster.
• Generated audio is ambient only — use voiceover/music tools for speech and music.
• ~30% of generations may have training data artifacts (logos/text). Re-run with --seed to vary.

4e. Talking Head Narrator (optional)

Generate a presenter portrait, then animate per-scene clips:

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

# 1. Generate portrait
python3 tools/flux2.py \
  --prompt "Professional presenter portrait, clean style, dark background, facing camera, upper body" \
  --width 1024 --height 576 \
  --output projects/PROJECT_NAME/public/images/presenter.png \
  --cloud modal

# 2. Generate per-scene narrator clips (one per scene, NOT one long video)
python3 tools/sadtalker.py \
  --image projects/PROJECT_NAME/public/images/presenter.png \
  --audio projects/PROJECT_NAME/public/audio/scenes/01.mp3 \
  --preprocess full --still --expression-scale 0.8 \
  --output projects/PROJECT_NAME/public/narrator-01.mp4 \
  --cloud modal

# Repeat for each scene that needs a narrator

SadTalker rules — follow these exactly:

• ALWAYS use --preprocess full (default crop outputs a square, wrong aspect ratio)
• ALWAYS use --still (reduces head movement, looks professional)
• ALWAYS generate per-scene clips (6-15s each), NEVER one long video
• Processing: ~3-4 min per 10s of audio on Modal A10G
• --expression-scale 0.8 keeps expressions subtle (range 0.0-1.5)

4e. Image Editing (optional)

Create scene variants from existing images:

cd ~/.openclaw/workspace/claude-code-video-toolkit
python3 tools/image_edit.py \
  --input projects/PROJECT_NAME/public/images/title-bg.png \
  --prompt "Make it darker with red tones, more ominous" \
  --output projects/PROJECT_NAME/public/images/problem-bg.png \
  --cloud modal

4f. Upscaling (optional)

cd ~/.openclaw/workspace/claude-code-video-toolkit
python3 tools/upscale.py \
  --input projects/PROJECT_NAME/public/images/some-image.png \
  --output projects/PROJECT_NAME/public/images/some-image-4x.png \
  --scale 4 --cloud modal

Step 5: Sync Timing

ALWAYS do this after generating voiceover. Audio duration differs from estimates.

cd ~/.openclaw/workspace/claude-code-video-toolkit
for f in projects/PROJECT_NAME/public/audio/scenes/*.mp3; do
  echo "$(basename $f): $(ffprobe -v error -show_entries format=duration -of csv=p=0 "$f")s"
done

Update each scene's durationSeconds in demo-config.ts to: ceil(actual_audio_duration + 2).

Example: if 01.mp3 is 6.8s, set scene 1 durationSeconds to 9 (ceil(6.8 + 2) = 9).

Step 6: Review Still Frames

cd ~/.openclaw/workspace/claude-code-video-toolkit/projects/PROJECT_NAME
npx remotion still src/index.ts ProductDemo --frame=100 --output=/tmp/review-scene1.png
npx remotion still src/index.ts ProductDemo --frame=400 --output=/tmp/review-scene2.png

Check: text truncation, animation timing, narrator PiP positioning, background contrast.

Step 7: Render

cd ~/.openclaw/workspace/claude-code-video-toolkit/projects/PROJECT_NAME
npm run render

Output: out/ProductDemo.mp4

---

Composition Patterns

Per-Scene Audio

Use per-scene audio with a 1-second delay (from={30} = 30 frames = 1s at 30fps):

<Sequence from={30}>
  <Audio src={staticFile('audio/scenes/01.mp3')} volume={1} />
</Sequence>

Per-Scene Narrator PiP

<Sequence from={30}>
  <OffthreadVideo
    src={staticFile('narrator-01.mp4')}
    style={{ width: 320, height: 180, objectFit: 'cover' }}
    muted
  />
</Sequence>

ALWAYS use <OffthreadVideo>, NEVER <video>. Remotion requires its own component for frame-accurate rendering.

Transitions

import { TransitionSeries, linearTiming } from '@remotion/transitions';
import { fade } from '@remotion/transitions/fade';
import { glitch } from '../../../lib/transitions/presentations/glitch';
import { lightLeak } from '../../../lib/transitions/presentations/light-leak';

NEVER import from lib/transitions barrel — import custom transitions from lib/transitions/presentations/ directly.

---

Error Recovery

Problem	Solution
Tool command fails with "No module named..."	Run pip3 install --break-system-packages -r tools/requirements.txt from toolkit root
"MODAL_*_ENDPOINT_URL not configured"	Check .env has the endpoint URL. Run python3 tools/verify_setup.py
SadTalker output is square/cropped	You forgot --preprocess full. Re-run with that flag
Audio too short/long for scene	Re-run Step 5 (sync timing) and update config
npm run render fails	Make sure you're in the project dir, not toolkit root. Run npm install first
"Cannot find module" in Remotion	Check import paths. Custom components use ../../../lib/ relative paths
Cold start timeout on Modal	First call after idle takes 30-120s. Retry once — second call uses warm GPU

---

Cost Estimates (Modal)

Tool	Typical Cost	Notes
Qwen3-TTS	~$0.01/scene	~20s per scene on warm GPU
FLUX.2	~$0.01/image	~3s warm, ~30s cold
ACE-Step	~$0.02-0.05	Depends on duration
SadTalker	~$0.05-0.20/scene	~3-4 min per 10s audio
Qwen-Edit	~$0.03-0.15	~8 min cold start (25GB model)
RealESRGAN	~$0.005/image	Very fast
LTX-2.3	~$0.20-0.25/clip	~2.5 min per 5s clip, A100-80GB

Total for a 60s video: ~$1-3 depending on scenes and narrator clips.

Modal Starter plan: $30/month free compute. Apps scale to zero when idle.