mckruz/comfyui-expert/comfyui-video-pipeline
Claude Code and agent skill by mckruz/comfyui-expert
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Checking that the SKILL.md file is still in the repository.
Generate videos using ComfyUI with Wan 2.2, FramePack, or AnimateDiff. Handles image-to-video, text-to-video, talking heads, and motion-controlled animation. Use when creating any video content from character images or text descriptions.
Install
npx vskill@latest install mckruz/comfyui-expert/comfyui-video-pipelineSKILL.md
ComfyUI Video Pipeline
Orchestrates video generation across three engines, selecting the best one based on requirements and available resources.
Engine Selection
Pipeline 1: Wan 2.2 MoE (Highest Quality)
Image-to-Video
Prerequisites:
wan2.1_i2v_720p_14b_bf16.safetensorsinmodels/diffusion_models/umt5_xxl_fp8_e4m3fn_scaled.safetensorsinmodels/clip/open_clip_vit_h_14.safetensorsinmodels/clip_vision/wan_2.1_vae.safetensorsinmodels/vae/
Settings:
| Parameter | Value | Notes | |
|---|---|---|---|
| Resolution | 1280x720 (landscape) or 720x1280 (portrait) | Native training resolution | |
| Frames | 81 (~5 seconds at 16fps) | Multiples of 4 + 1 | |
| Steps | 30-50 | Higher = better quality | |
| CFG | 5-7 | ||
| Sampler | uni_pc | Recommended for Wan | |
| Scheduler | normal |
Frame count guide:
| Duration | Frames (16fps) | |
|---|---|---|
| 1 second | 17 | |
| 3 seconds | 49 | |
| 5 seconds | 81 | |
| 10 seconds | 161 |
VRAM optimization:
- FP8 quantization: halves VRAM with minimal quality loss
- SageAttention: faster attention computation
- Reduce frames if OOM
Text-to-Video
Same as I2V but uses wan2.1_t2v_14b_bf16.safetensors and EmptySD3LatentImage instead of image conditioning.
First+Last Frame Control (Wan 2.2 Exclusive)
Wan 2.2 MoE allows specifying both the first and last frame, enabling precise video planning:
- Generate two hero images with consistent character
- Use first as start frame, second as end frame
- Wan interpolates the motion between them
Pipeline 2: FramePack (Long Videos, Low VRAM)
Key Innovation
VRAM usage is invariant to video length - generates 60-second videos at 30fps on just 6GB VRAM.
How it works:
- Dynamic context compression: 1536 markers for key frames, 192 for transitions
- Bidirectional memory with reverse generation prevents drift
- Frame-by-frame generation with context window
Settings
| Parameter | Value | Notes | |
|---|---|---|---|
| Resolution | 640x384 to 1280x720 | Depends on VRAM | |
| Duration | Up to 60 seconds | VRAM-invariant | |
| Quality | High (comparable to Wan) | Uses same base models |
When to Use
- Videos longer than 10 seconds
- Limited VRAM systems (but RTX 5090 doesn't need this)
- When VRAM is needed for parallel operations
- Batch video generation
Pipeline 3: AnimateDiff V3 (Fast, Controllable)
Strengths
- Motion LoRAs for camera control (pan, zoom, tilt, roll)
- Effect LoRAs (shatter, smoke, explosion, liquid)
- Sliding context window for infinite length
- Very fast with Lightning model (4-8 steps)
Settings
| Parameter | Value (Standard) | Value (Lightning) | |
|---|---|---|---|
| Motion Module | v3_sd15_mm.ckpt | animatediff_lightning_4step.safetensors | |
| Steps | 20-25 | 4-8 | |
| CFG | 7-8 | 1.5-2.0 | |
| Sampler | euler_ancestral | lcm | |
| Resolution | 512x512 | 512x512 | |
| Context Length | 16 | 16 | |
| Context Overlap | 4 | 4 |
Camera Motion LoRAs
| LoRA | Motion | |
|---|---|---|
| v2_lora_ZoomIn | Camera zooms in | |
| v2_lora_ZoomOut | Camera zooms out | |
| v2_lora_PanLeft | Camera pans left | |
| v2_lora_PanRight | Camera pans right | |
| v2_lora_TiltUp | Camera tilts up | |
| v2_lora_TiltDown | Camera tilts down | |
| v2_lora_RollingClockwise | Camera rolls clockwise |
Post-Processing Pipeline
After any video generation:
1. Frame Interpolation (RIFE)
Doubles or quadruples frame count for smoother motion:
Use rife47 or rife49 model.
2. Face Enhancement (if character video)
Apply FaceDetailer to each frame:
- denoise: 0.3-0.4 (lower than image - preserves temporal consistency)
- guide_size: 384 (speed optimization for video)
- detection_model: face_yolov8m.pt
3. Deflicker (if needed)
Reduces temporal inconsistencies between frames.
4. Color Correction
Maintain consistent color grading across frames.
5. Video Combine
Final output via VHS Video Combine:
Talking Head Pipeline
Complete pipeline for character dialogue:
Quality Checklist
Before marking video as complete:
- [ ] Character identity consistent across frames
- [ ] No flickering or temporal artifacts
- [ ] Motion looks natural (not jerky or frozen)
- [ ] Face enhancement applied if character video
- [ ] Frame rate is smooth (24+ fps for delivery)
- [ ] Audio synced (if talking head)
- [ ] Resolution matches delivery target
Reference
references/workflows.md- Workflow templates for Wan and AnimateDiffreferences/models.md- Video model download linksreferences/research-log.md- Latest video generation advancesstate/inventory.json- Available video models
Security
- Security scanPassed, 95 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/comfyui-video-pipeline/SKILL.md
Popularity
- Repository stars
- 27
- Repository forks
- 6
- 7-day trend score
- 17
Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 16 Mar 2026, 7 months ago.
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