
Aliyun Wan Edit
- 57 installs
- 396 repo stars
- Updated July 18, 2026
- cinience/alicloud-skills
Edits existing video with Alibaba Cloud Model Studio Wan models for style transfer, keyframe-controlled editing, and animation remix.
About
This skill prepares requests for Model Studio Wan video-editing models to transform video style, guide edits by keyframes, or remix animation. A developer uses it when modifying existing video material rather than generating new clips.
- Models include wanx2.1-vace-plus, wanx2.1-kf2v-plus, wan2.2-animate-mix
- Points to sibling skills for Wan generation and dedicated lip-sync
Aliyun Wan Edit by the numbers
- 57 all-time installs (skills.sh)
- Ranked #871 of 1,335 Generative Media skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 57 |
|---|---|
| repo stars | ★ 396 |
| Last updated | July 18, 2026 |
| Repository | cinience/alicloud-skills ↗ |
What it does
Edits existing video with Alibaba Cloud Model Studio Wan models for style transfer, keyframe-controlled editing, and animation remix.
Files
Category: provider
Model Studio Wan Video Edit
Validation
mkdir -p output/aliyun-wan-edit
python -m py_compile skills/ai/video/aliyun-wan-edit/scripts/prepare_video_edit_request.py && echo "py_compile_ok" > output/aliyun-wan-edit/validate.txtPass criteria: command exits 0 and output/aliyun-wan-edit/validate.txt is generated.
Critical model names
Use one of these exact model strings as needed:
wanx2.1-vace-pluswanx2.1-kf2v-pluswan2.2-animate-mixVideoRetalk
Typical use
- Video style transformation
- Keyframe-to-video guided editing
- Animation remix
Quick start
python skills/ai/video/aliyun-wan-edit/scripts/prepare_video_edit_request.py \
--output output/aliyun-wan-edit/request.jsonNotes
- Use
skills/ai/video/aliyun-wan-video/for Wan generation. - Use
skills/ai/video/aliyun-videoretalk/for dedicated lip-sync replacement. - Use this skill only when the user wants to modify existing video material.
References
references/sources.md
interface:
display_name: "Alibaba Cloud AI Video Wan Edit"
short_description: "Video editing with Wan edit models"
default_prompt: "Use $aliyun-wan-edit to complete this ai/video editing task on Alibaba Cloud."
Sources
- https://help.aliyun.com/zh/model-studio/video-generation
- https://help.aliyun.com/zh/model-studio/newly-released-models
#!/usr/bin/env python3
"""Prepare a minimal request payload for Wan video editing models."""
from __future__ import annotations
import argparse
import json
from pathlib import Path
DEFAULT_PAYLOAD = {
"model": "wanx2.1-vace-plus",
"prompt": "Apply a cinematic cool-tone grade and keep the subject identity stable.",
"video_url": "https://example.com/input.mp4",
}
def main() -> None:
parser = argparse.ArgumentParser()
parser.add_argument(
"--output",
default="output/aliyun-wan-edit/request.json",
)
args = parser.parse_args()
output = Path(args.output)
output.parent.mkdir(parents=True, exist_ok=True)
output.write_text(json.dumps(DEFAULT_PAYLOAD, ensure_ascii=False, indent=2), encoding="utf-8")
print(output)
if __name__ == "__main__":
main()