alicloud-ai-video-wan-video

cinience/alicloud-skills · updated Apr 8, 2026

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$npx skills add https://github.com/cinience/alicloud-skills --skill alicloud-ai-video-wan-video
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summary

Category: provider

skill.md

Category: provider

Model Studio Wan Video

Validation

mkdir -p output/alicloud-ai-video-wan-video
python -m py_compile skills/ai/video/alicloud-ai-video-wan-video/scripts/generate_video.py && echo "py_compile_ok" > output/alicloud-ai-video-wan-video/validate.txt

Pass criteria: command exits 0 and output/alicloud-ai-video-wan-video/validate.txt is generated.

Output And Evidence

  • Save task IDs, polling responses, and final video URLs to output/alicloud-ai-video-wan-video/.
  • Keep one end-to-end run log for troubleshooting.

Provide consistent video generation behavior for the video-agent pipeline by standardizing video.generate inputs/outputs and using DashScope SDK (Python) with the exact model name.

Critical model names

Use one of these exact model strings:

  • wan2.6-t2v
  • wan2.6-t2v-us
  • wan2.2-t2v-plus
  • wan2.2-t2v-flash
  • wan2.6-i2v-flash
  • wan2.6-i2v
  • wan2.6-i2v-us
  • wanx2.1-t2v-turbo

Prerequisites

  • Install SDK (recommended in a venv to avoid PEP 668 limits):
python3 -m venv .venv
. .venv/bin/activate
python -m pip install dashscope
  • Set DASHSCOPE_API_KEY in your environment, or add dashscope_api_key to ~/.alibabacloud/credentials (env takes precedence).

Normalized interface (video.generate)

Request

  • prompt (string, required)
  • negative_prompt (string, optional)
  • duration (number, required) seconds
  • fps (number, required)
  • size (string, required) e.g. 1280*720
  • seed (int, optional)
  • reference_image (string | bytes, optional for t2v, required for i2v family models)
  • motion_strength (number, optional)

Response

  • video_url (string)
  • duration (number)
  • fps (number)
  • seed (int)

Quick start (Python + DashScope SDK)

Video generation is usually asynchronous. Expect a task ID and poll until completion. Note: Wan i2v models require an input image; pure t2v models such as wan2.6-t2v can omit reference_image.

import os
from dashscope import VideoSynthesis

# Prefer env var for auth: export DASHSCOPE_API_KEY=...
# Or use ~/.alibabacloud/credentials with dashscope_api_key under [default].

def generate_video(req: dict) -> dict:
    payload = {
        "model": req.get("model", "wan2.6-i2v-flash"),
        "prompt": req["prompt"],
        "negative_prompt": req.get("negative_prompt"),
        "duration": req.get("duration", 4),
        "fps": req.get("fps", 24),
        "size": req.get("size", "1280*720"),
        "seed": req.get("seed"),
        "motion_strength": req.get("motion_strength"),
        "api_key": os.getenv("DASHSCOPE_API_KEY"),
    }

    if req.get("reference_image"):
        # DashScope expects img_url for i2v models; local files are auto-uploaded.
        payload["img_url"] = req["reference_image"]

    response = VideoSynthesis.call(**payload)

    # Some SDK versions require polling for the final result.
    # If a task_id is returned, poll until status is SUCCEEDED.
    result = response.output.get("results", [None])[0]

    return {
        "video_url": None if not result else result.get("url"),
        "duration": response.output.get("duration"),
        "fps": response.output.get("fps"),
        "seed": response.output.get("seed"),
    }

Async handling (polling)

import os
from dashscope import VideoSynthesis

task = VideoSynthesis.async_call(
    model=req.get("model", "wan2.6-i2v-flash"),
    prompt=req["prompt"],
    img_url=req["reference_image"],
    duration=req.get("duration", 4),
    fps=req.get("fps", 24),
    size=req.get("size", "1280*720"),
    api_key=os.getenv("DASHSCOPE_API_KEY"),
)

final = VideoSynthesis.wait(task)
video_url = final.output.get("video_url")

Operational guidance

  • Video generation can take minutes; expose progress and allow cancel/retry.
  • Cache by (prompt, negative_prompt, duration, fps, size, seed, reference_image hash, motion_strength).
  • Store video assets in object storage and persist only URLs in metadata.
  • reference_image can be a URL or local path; the SDK auto-uploads local files.
  • If you get Field required: input.img_url, the reference image is missing or not mapped.
  • wan2.6-t2v and wan2.6-t2v-us add multi-shot narrative support and optional audio input according to the official docs.

Size notes

  • Use WxH format (e.g. 1280*720).
  • Prefer common sizes; unsupported sizes can return 400.

Output location

  • Default output: output/alicloud-ai-video-wan-video/videos/
  • Override base dir with OUTPUT_DIR.

Anti-patterns

  • Do not invent model names or aliases; use official Wan i2v model IDs only.
  • Do not block the UI without progress updates.
  • Do not retry blindly on 4xx; handle validation failures explicitly.

Workflow

  1. Confirm user intent, region, identifiers, and whether the operation is read-only or mutating.
  2. Run one minimal read-only query first to verify connectivity and permissions.
  3. Execute the target operation with explicit parameters and bounded scope.
  4. Verify results and save output/evidence files.

References

  • See references/api_reference.md for DashScope SDK mapping and async handling notes.

  • Source list: references/sources.md

how to use alicloud-ai-video-wan-video

How to use alicloud-ai-video-wan-video on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add alicloud-ai-video-wan-video
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/cinience/alicloud-skills --skill alicloud-ai-video-wan-video

The skills CLI fetches alicloud-ai-video-wan-video from GitHub repository cinience/alicloud-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/alicloud-ai-video-wan-video

Reload or restart Cursor to activate alicloud-ai-video-wan-video. Access the skill through slash commands (e.g., /alicloud-ai-video-wan-video) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.537 reviews
  • Chaitanya Patil· Dec 24, 2024

    alicloud-ai-video-wan-video is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Noor Torres· Dec 20, 2024

    Useful defaults in alicloud-ai-video-wan-video — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Aarav Dixit· Dec 20, 2024

    Solid pick for teams standardizing on skills: alicloud-ai-video-wan-video is focused, and the summary matches what you get after install.

  • Piyush G· Nov 15, 2024

    Useful defaults in alicloud-ai-video-wan-video — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Advait Rahman· Nov 11, 2024

    alicloud-ai-video-wan-video is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Amelia Patel· Nov 11, 2024

    alicloud-ai-video-wan-video has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Shikha Mishra· Oct 6, 2024

    Registry listing for alicloud-ai-video-wan-video matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Neel Mehta· Oct 2, 2024

    alicloud-ai-video-wan-video reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Omar Thompson· Oct 2, 2024

    alicloud-ai-video-wan-video fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Yash Thakker· Sep 13, 2024

    Solid pick for teams standardizing on skills: alicloud-ai-video-wan-video is focused, and the summary matches what you get after install.

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