Individual skill
wan-flf-video
Build WAN 2.2 First-Last-Frame video workflows. Native dual hi-lo (required), and WanVideoWrapper VACE approaches
plugin/skills/wan-flf-video/SKILL.md
Source commit 5bfe534ed114c3037137b3fabd209011238e9d10
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- No
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Not checked yet
- Last checked
- Nov 4, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 904
- Repository last updated
- Nov 4, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- agent-skills Repository topic
- ai-agent Repository topic
- claude-code Repository topic
- claude-plugin Repository topic
- comfyui Repository topic
- comfyui-extension Repository topic
- flux Repository topic
- image-generation Repository topic
- mcp Repository topic
- mcp-server Repository topic
- engineering Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
Read excerpt
# WAN 2.2 First-Last-Frame (FLF) Video Workflows
## Overview
First-Last-Frame (FLF) video generation takes a start image and an end image and generates a smooth video transition between them. The WAN 2.2 I2V (Image-to-Video) 14B model is good at this.
## CRITICAL: Dual Hi-Lo Architecture (REQUIRED)
**WAN 2.2 I2V uses a split-noise architecture.** Unlike WAN 2.1, the 2.2 model was trained with separate HighNoise and LowNoise components that handle different denoising ranges. **You MUST use both models in a two-pass KSamplerAdvanced setup.** Using a single model produces low-quality, broken output.
- HighNoise model (pass 1, steps 0→N/2) establishes structure, motion, and composition
- LowNoise model (pass 2, steps N/2→N) refines details and keeps fidelity to input frames
- Both passes share the same conditioning from `WanFirstLastFrameToVideo`
- Pass 1 returns noisy latent → Pass 2 continues from there