AI Video Generation

Setup

On first use, read setup.md.

When to Use

User needs to generate, edit, or scale AI videos with current models and APIs. Use this skill to choose the right current model stack, write stronger motion prompts, and run reliable async video pipelines.

Architecture

User preferences persist in ~/video-generation/. See memory-template.md for setup.

~/video-generation/
├── memory.md      # Preferred providers, model routing, reusable shot recipes
└── history.md     # Optional run log for jobs, costs, and outputs

Quick Reference

Topic	File
Initial setup	setup.md
Memory template	memory-template.md
Migration guide	migration.md
Model snapshot	benchmarks.md
Async API patterns	api-patterns.md
OpenAI Sora 2	openai-sora.md
Google Veo 3.x	google-veo.md
Runway Gen-4	runway.md
Luma Ray	luma.md
ByteDance Seedance	seedance.md
Kling	kling.md
Vidu	vidu.md
Pika via Fal	pika.md
MiniMax Hailuo	minimax-hailuo.md
Replicate routing	replicate.md
Open-source local models	open-source-video.md
Distribution playbook	promotion.md

Core Rules

1. Resolve model aliases before API calls

Map community names to real API model IDs first. Examples: sora-2, sora-2-pro, veo-3.0-generate-001, gen4_turbo, gen4_aleph.

2. Route by task, not brand preference

Task	First choice	Backup
Premium prompt-only generation	sora-2-pro	veo-3.1-generate-001
Fast drafts at lower cost	veo-3.1-fast-generate-001	gen4_turbo
Long-form cinematic shots	gen4_aleph	ray-2
Strong image-to-video control	veo-3.0-generate-001	gen4_turbo
Multi-shot narrative consistency	Seedance family	hailuo-2.3
Local privacy-first workflows	Wan2.2 / HunyuanVideo	CogVideoX

3. Draft cheap, finish expensive

Start with low duration and lower tier, validate motion and composition, then rerender winners with premium models or longer durations.

4. Design prompts as shot instructions

Always include subject, action, camera motion, lens style, lighting, and scene timing. For references and start/end frames, keep continuity constraints explicit.

5. Assume async and failure by default

Every provider pipeline must support queued jobs, polling/backoff, retries, cancellation, and signed-URL download before expiry.

6. Keep a fallback chain

If the preferred model is blocked or overloaded:

1. same provider lower tier, 2) equivalent cross-provider model, 3) open model/local run.

Common Traps

• Using nickname-only model labels in code -> avoidable API failures
• Pushing 8-10 second generations before validating a 3-5 second draft -> wasted credits
• Cropping after generation instead of generating native ratio -> lower composition quality
• Ignoring prompt enhancement toggles -> tone drift across providers
• Reusing expired output URLs -> broken export workflows
• Treating all providers as synchronous -> stalled jobs and bad timeout handling

External Endpoints

Provider	Endpoint	Data Sent	Purpose
OpenAI	api.openai.com	Prompt text, optional input images/video refs	Sora 2 video generation
Google Vertex AI	aiplatform.googleapis.com	Prompt text, optional image input, generation params	Veo 3.x generation
Runway	api.dev.runwayml.com	Prompt text, optional input media	Gen-4 generation and image-to-video
Luma	api.lumalabs.ai	Prompt text, optional keyframes/start-end images	Ray generation
Fal	queue.fal.run	Prompt text, optional input media	Pika and Hailuo hosted APIs
Replicate	api.replicate.com	Prompt text, optional input media	Multi-model routing and experimentation
Vidu	api.vidu.com	Prompt text, optional start/end/reference images	Vidu text/image/reference video APIs
Tencent MPS	mps.tencentcloudapi.com	Prompt text and generation parameters	Unified AIGC video task APIs

No other data is sent externally.

Security & Privacy

Data that leaves your machine:

• Prompt text
• Optional reference images or clips
• Requested rendering parameters (duration, resolution, aspect ratio)

Data that stays local:

• Provider preferences in ~/video-generation/memory.md
• Optional local job history in ~/video-generation/history.md

This skill does NOT:

• Store API keys in project files
• Upload media outside requested provider calls
• Delete local assets unless the user asks

Trust

This skill can send prompts and media references to third-party AI providers. Only install if you trust those providers with your content.

Related Skills

Install with clawhub install <slug> if user confirms:

• image-generation - Build still concepts and keyframes before video generation
• image-edit - Prepare clean references, masks, and style frames
• video-edit - Post-process generated clips and final exports
• video-captions - Add subtitle and text overlay workflows
• ffmpeg - Compose, transcode, and package production outputs

Feedback

• If useful: clawhub star video-generation
• Stay updated: clawhub sync