FlowCutPro

AI-powered cinematic video production using Google Veo 3 as the renderer and OpenClaw's configured LLM as the creative brain. Use when asked to create videos, animate concepts, generate Reels/TikToks, produce commercials, or turn any text concept into a stitched cinematic video. The LLM plans shots, writes optimized Veo 3 prompts, maintains style consistency, and runs a quality loop. Veo 3 renders. ffmpeg stitches. Triggers on: "make a video", "create a clip", "generate a reel", "produce a commercial", "animate this", "video generation", "FlowCutPro", "flowcutpro".

FlowCutPro — AI Cinematic Video Production

Two-layer architecture:

• Brain: OpenClaw's configured LLM — shot planning, prompt engineering, style consistency, quality evaluation
• Renderer: Google Veo 3 (veo-3.1-generate-preview) — photorealistic, physics-accurate, cinematic camera moves, 9:16/16:9/1:1

The LLM does the creative work. Veo 3 renders. ffmpeg stitches. You get professional video from a casual prompt.

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Pipeline

text

User concept
    ↓
LLM: Shot Planner — breaks concept into N shots with timing + camera moves
    ↓
LLM: Prompt Engineer — expands each shot into optimized Veo 3 cinematic prompt
    ↓
Veo 3: Render shots in batches of 5 (API concurrent limit)
    ↓
LLM: Quality Evaluator — reviews output thumbnails vs brief, flags misses
    ↓
Veo 3: Regenerate any failing shots (up to 2 retries)
    ↓
ffmpeg: Stitch clips with crossfades → final video
    ↓
Deliver

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Setup

Veo 3 API Key

Get a Gemini API key from https://aistudio.google.com/apikeys

bash

export VEO_API_KEY="your-key-here"

Or store in 1Password: op://flow/gemini-api-key/key

Dependencies

bash

pip install Pillow requests  # optional for thumbnails
brew install ffmpeg

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Usage

bash

# Single concept → full stitched video
python3 ~/clawd/skills/flowcutpro/scripts/flowcutpro.py \
  --concept "A luxury hotel guest arriving at sunset in Puerto Rico" \
  --shots 6 \
  --aspect-ratio 9:16 \
  --output-dir ~/clawd/output/flowcutpro/

# Reel / TikTok
python3 ~/clawd/skills/flowcutpro/scripts/flowcutpro.py \
  --concept "Morning coffee ritual in a minimalist Tokyo apartment" \
  --shots 4 \
  --aspect-ratio 9:16 \
  --duration 5 \
  --output-dir ~/clawd/output/flowcutpro/

# Cinematic widescreen
python3 ~/clawd/skills/flowcutpro/scripts/flowcutpro.py \
  --concept "A founder's journey from garage to IPO day" \
  --shots 8 \
  --aspect-ratio 16:9 \
  --output-dir ~/clawd/output/flowcutpro/

# Dry run (inspect shot plan without rendering)
python3 ~/clawd/skills/flowcutpro/scripts/flowcutpro.py \
  --concept "Product launch event at a Silicon Valley rooftop" \
  --shots 5 \
  --dry-run

# Render specific shots only (re-render misses)
python3 ~/clawd/skills/flowcutpro/scripts/flowcutpro.py \
  --concept "..." \
  --shots 6 \
  --only-shots 3 5

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Output

text

~/clawd/output/flowcutpro/
  20260329-120000-shot01-arrival.mp4
  20260329-120000-shot02-lobby.mp4
  ...
  20260329-120000-FINAL-9x16.mp4   ← stitched master

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Prompt Engineering — Veo 3 Best Practices

FlowCutPro automatically applies these rules when generating prompts:

1. Always specify aspect ratio at the start: "Cinematic vertical 9:16 portrait..."
2. Describe camera movement explicitly: slow push-in, dolly, crane, static wide, tracking shot
3. Specify lighting: golden hour, overcast, blue hour, candlelit, harsh noon
4. Include motion direction: "camera slowly pushes forward", "slow pan left to right"
5. Name the aesthetic: cinematic, film grain, photorealistic, documentary, editorial
6. Negative elements: "no text overlays, no logos, no CGI artifacts"
7. Duration awareness: 5–8s per shot is optimal; 5s for fast cuts, 8s for slow moody shots
8. Style consistency prefix: Start every shot prompt with the same style fingerprint for visual coherence across cuts

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Examples

See examples/ folder:

• hotel-commercial.py — 8-shot luxury hotel commercial (9:16)
• product-launch.py — 6-shot product launch reel (9:16)
• brand-story.py — 10-shot founder story (16:9)

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Technical Details

• Model: veo-3.1-generate-preview (Google Generative AI)
• Endpoint: https://generativelanguage.googleapis.com/v1beta/models/veo-3.1-generate-preview:predictLongRunning
• Aspect ratios: 9:16, 16:9, 1:1
• Duration: 5–8 seconds per shot
• Concurrent limit: 5 shots per batch (enforced automatically)
• Stitch: ffmpeg xfade crossfade (0.5s transitions)
• Output codec: H.264, CRF 18 (high quality)
• Polling: 15s intervals, 10-minute timeout per shot

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Limits & Notes

• Veo 3 API is currently in preview — requires allowlist access via Google AI Studio
• Each shot takes ~2–4 minutes to render
• 10-shot video ≈ 20–40 minutes total (parallel batches of 5)
• API key needs Gemini API enabled in Google Cloud Console
• Free tier: limited daily quota; paid tier recommended for production use