How do I install the Workflow Wan I2v Lora Squish Effect skill?

Run npx skillmds@latest add steliosot/workflow-wan-i2v-lora-squish-effect in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the Workflow Wan I2v Lora Squish Effect skill do?

Workflow wrapper imported from `Wan i2v + Lora Squish Effect.json`. It is listed under Productivity on SkillMD.

Is Workflow Wan I2v Lora Squish Effect safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Workflow Wan I2v Lora Squish Effect?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Workflow Wan I2v Lora Squish Effect free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Workflow Wan I2v Lora Squish Effect?

steliosot (@steliosot) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Workflow Wan I2v Lora Squish Effect by steliosot

Name: Workflow Wan I2v Lora Squish Effect
Author: steliosot

File contents

workflow_wan_i2v_lora_squish_effect

Imported workflow skill generated from Wan i2v + Lora Squish Effect.json.

Family

video_t2v_i2v_avatar

Inputs

Optional runtime overrides supported by run(...):
- prompt
- negative_prompt
- width, height
- seed, steps, cfg
- sampler_name, scheduler, denoise
- server, headers, api_prefix

Outputs

Returns JSON with:
- status
- prompt_id
- output_images

Model Requirements

diffusion_model: wan2.1_i2v_480p_14B_fp8_scaled.safetensors -> models/diffusion_models
lora: squish_18.safetensors -> models/loras
clip: umt5_xxl_fp8_e4m3fn_scaled.safetensors -> models/clip
vae: wan_2.1_vae.safetensors -> models/vae

Custom Node Requirements

comfyui-videohelpersuite

Routing Metadata

Family: video_t2v_i2v_avatar
Input modalities: image, text_prompt
Output modalities: video/mp4
Model families: wan
Node count: 17
Complexity score: 8
Resource profile: high
Estimated runtime: slow (often 2-6 min depending on model/server load)
Max latent resolution hint: NonexNone
Max sampler steps hint: 30

Detected Models

diffusion_model: wan2.1_i2v_480p_14B_fp8_scaled.safetensors -> models/diffusion_models
lora: squish_18.safetensors -> models/loras
clip: umt5_xxl_fp8_e4m3fn_scaled.safetensors -> models/clip
vae: wan_2.1_vae.safetensors -> models/vae

Detected Custom Nodes

comfyui-videohelpersuite

Runtime Warnings

Large model(s) detected; ensure enough VRAM and disk space.
Uses custom nodes; missing nodes can cause validation/runtime failures.
Video workflow: usually slower and VRAM-intensive than still-image workflows.

---name: workflow-wan-i2v-lora-squish-effectdescription: Workflow wrapper imported from `Wan i2v + Lora Squish Effect.json`.---# workflow_wan_i2v_lora_squish_effectImported workflow skill generated from `Wan i2v + Lora Squish Effect.json`.## Family- `video_t2v_i2v_avatar`## Inputs- Optional runtime overrides supported by `run(...)`: - `prompt` - `negative_prompt` - `width`, `height` - `seed`, `steps`, `cfg` - `sampler_name`, `scheduler`, `denoise` - `server`, `headers`, `api_prefix`## Outputs- Returns JSON with: - `status` - `prompt_id` - `output_images`## Model Requirements- `diffusion_model`: `wan2.1_i2v_480p_14B_fp8_scaled.safetensors` -> `models/diffusion_models`- `lora`: `squish_18.safetensors` -> `models/loras`- `clip`: `umt5_xxl_fp8_e4m3fn_scaled.safetensors` -> `models/clip`- `vae`: `wan_2.1_vae.safetensors` -> `models/vae`## Custom Node Requirements- `comfyui-videohelpersuite`## Links- https://discord.com/invite/gggpkVgBf3- https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/clip_vision/clip_vision_h.safetensors?download=true- https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/wan2.1_i2v_480p_14B_fp8_scaled.safetensors?download=true- https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors?download=true- https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors?download=true- https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/tree/main/split_files/diffusion_models- https://huggingface.co/Remade-AI/Squish/resolve/main/squish_18.safetensors?download=true- https://huggingface.co/collections/Remade-AI/wan21-14b-480p-i2v-loras-67d0e26f08092436b585919b- https://www.youtube.com/@pixaroma## Routing Metadata- Family: `video_t2v_i2v_avatar`- Input modalities: `image, text_prompt`- Output modalities: `video/mp4`- Model families: `wan`- Node count: `17`- Complexity score: `8`- Resource profile: `high`- Estimated runtime: `slow (often 2-6 min depending on model/server load)`- Max latent resolution hint: `None`x`None`- Max sampler steps hint: `30`## Detected Models- `diffusion_model`: `wan2.1_i2v_480p_14B_fp8_scaled.safetensors` -> `models/diffusion_models`- `lora`: `squish_18.safetensors` -> `models/loras`- `clip`: `umt5_xxl_fp8_e4m3fn_scaled.safetensors` -> `models/clip`- `vae`: `wan_2.1_vae.safetensors` -> `models/vae`## Detected Custom Nodes- `comfyui-videohelpersuite`## Runtime Warnings- Large model(s) detected; ensure enough VRAM and disk space.- Uses custom nodes; missing nodes can cause validation/runtime failures.- Video workflow: usually slower and VRAM-intensive than still-image workflows.

Frequently asked questions

Workflow Wan I2v Lora Squish Effect