Individual skill
wan-t2v-video
Build WAN 2.2 Text-to-Video workflows. Dual hi-lo models, lightning LoRAs, VACE modules, and KSamplerAdvanced two-pass
plugin/skills/wan-t2v-video/SKILL.md
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- agent-skills Repository topic
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- claude-plugin Repository topic
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- comfyui-extension Repository topic
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# WAN 2.2 Text-to-Video (T2V) Workflows
## Overview
WAN 2.2 T2V generates videos from text prompts using a 14B parameter MoE (Mixture of Experts) architecture split across two specialized models:
- HighNoise model handles early denoising. It establishes structure, motion, composition
- LowNoise model handles late denoising. It refines details, sharpens output
This dual-model technique is the same as FLF/I2V (see wan-flf-video skill) but without image conditioning nodes.
Key difference from I2V/FLF: T2V does NOT use `CLIPVisionEncode`, `WanFirstLastFrameToVideo`, or any image input. It uses `EmptyHunyuanLatentVideo` for latent initialization and text-only conditioning.
## Models