Generates AI videos via AceDataCloud's Wan API. Supports text-to-video, image-to-video, reference video transfer, multi-resolution, and optional audio.
How this skill is triggered — by the user, by Claude, or both
Slash command
/acedatacloud-ai-media:wan-videoThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Generate AI videos through AceDataCloud's Wan (Alibaba) API.
Generate AI videos through AceDataCloud's Wan (Alibaba) API.
Setup: See authentication for token setup.
curl -X POST https://api.acedata.cloud/wan/videos \
-H "Authorization: Bearer $ACEDATACLOUD_API_TOKEN" \
-H "Content-Type: application/json" \
-d '{"action": "text2video", "prompt": "a dolphin jumping through ocean waves at golden hour", "model": "wan2.6-t2v"}'
Async: See async task polling. Poll via
POST /wan/taskswith{"id": "..."}.
| Model | Type | Best For |
|---|---|---|
wan2.6-t2v | Text-to-Video | Creating video from text description |
wan2.6-i2v | Image-to-Video | Animating a still image into video |
wan2.6-r2v | Reference Video-to-Video | Character extraction and transfer from reference video |
wan2.6-i2v-flash | Image-to-Video (Fast) | Quick image-to-video generation |
POST /wan/videos
{
"action": "text2video",
"prompt": "a time-lapse of flowers blooming in a meadow",
"model": "wan2.6-t2v",
"resolution": "720P",
"duration": 5
}
Animate a still image into a video clip.
POST /wan/videos
{
"action": "image2video",
"prompt": "gentle wind blows through the scene",
"model": "wan2.6-i2v",
"image_url": "https://example.com/landscape.jpg",
"resolution": "720P",
"duration": 5
}
Faster image-to-video generation with reduced latency.
POST /wan/videos
{
"action": "image2video",
"prompt": "camera slowly pans across the landscape",
"model": "wan2.6-i2v-flash",
"image_url": "https://example.com/scene.jpg"
}
Extract characters or timbres from a reference video and transfer them into a new generation.
POST /wan/videos
{
"action": "text2video",
"prompt": "the character walks through a futuristic city at night",
"model": "wan2.6-r2v",
"reference_video_urls": ["https://example.com/reference.mp4"]
}
Generate a video with multiple shots rather than a single continuous take.
POST /wan/videos
{
"action": "text2video",
"prompt": "a chef preparing a meal in a busy kitchen",
"model": "wan2.6-t2v",
"shot_type": "multi",
"duration": 10
}
Enable audio generation alongside the video.
POST /wan/videos
{
"action": "text2video",
"prompt": "ocean waves crashing on a rocky shore",
"model": "wan2.6-t2v",
"audio": true
}
| Parameter | Required | Values | Description |
|---|---|---|---|
action | Yes | "text2video", "image2video" | Action type |
prompt | Yes | string | Scene description |
model | Yes | "wan2.6-t2v", "wan2.6-i2v", "wan2.6-r2v", "wan2.6-i2v-flash" | Model |
image_url | For image2video | string | Source image URL (required for image-to-video) |
negative_prompt | No | string (max 500 chars) | Content to exclude from generation |
reference_video_urls | For r2v | array of strings | Reference videos for character/timbre extraction |
shot_type | No | "single", "multi" | Continuous shot or multi-cut editing |
audio | No | boolean | Enable audio in the generated video |
audio_url | No | string | Reference audio URL |
resolution | No | "480P", "720P", "1080P" | Output resolution (default: 720P) |
size | No | string | The size of the generated video |
duration | No | 5, 10, 15 | Video duration in seconds |
prompt_extend | No | boolean | Enable LLM-based prompt rewriting |
callback_url | No | string | Async webhook notification URL |
image_url is required for wan2.6-i2v and wan2.6-i2v-flash modelsreference_video_urls is used only with wan2.6-r2v for character/timbre transfernegative_prompt has a maximum length of 500 charactersshot_type: "multi" produces multi-cut edits rather than a single continuous shotMCP:
pip install mcp-wan| Hosted:https://wan.mcp.acedata.cloud/mcp| See all MCP servers
npx claudepluginhub acedatacloud/skills --plugin acedatacloud-ai-toolsCreates, edits, and optimizes skills for Claude Code, including drafting, evaluating with test prompts, iterating on performance, and improving skill descriptions for better triggering accuracy.