ai-video-generation
Installation
Summary
Route across 10+ video models (HappyHorse, Kling, Seedance, Veo, Wan, Hailuo, Dreamina) for text-to-video, image-to-video, and video extension.
- Supports text-to-video (t2v), image-to-video (i2v), and Veo's video-extend endpoint with model selection logic optimized for intent (quality tier, multi-shot identity, physics accuracy, audio sync, speed)
- Includes 10+ production models with documented prompting patterns: HappyHorse 1.0 (Arena #1, in-pass audio), Kling 3.0 (4K, multi-shot), Seedance v2 (multi-modal, cinematic), Veo 3-1 (physics-respecting), Wan 2-7 (audio-driven lip-sync), plus Hailuo, Dreamina, and legacy tiers
- Each model route ships its exact schema, invoke command, and prompting tips (e.g., "lead with subject and motion verb", "describe audio inline", "Veo respects physics")
- Invoked via
runcomfy run <vendor>/<model>/<endpoint>with JSON input; triggers on "generate video", "make a video
SKILL.md
AI Video Generation
Generate videos with the full RunComfy video-model catalog through one CLI — text-to-video, image-to-video, and Veo's video-extend. This skill picks the right model for the user's intent and ships the documented prompt patterns + the exact runcomfy run invoke for each.
runcomfy.com · Video models · CLI docs
Powered by the RunComfy CLI
# 1. Install (see runcomfy-cli skill for details)
npm i -g @runcomfy/cli # or: npx -y @runcomfy/cli --version
# 2. Sign in
runcomfy login # or in CI: export RUNCOMFY_TOKEN=<token>
Installs
174.1K
Repository
agentspace-so/runcomfy-agent-skillsGitHub Stars
19
First Seen
May 13, 2026
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