Agent skill

Aliyun Wan Image

A skill your agent uses when generating or editing images with DashScope Wan 2.7 image models (wan2.7-image, wan2.7-image-pro).

MITAuto-check passedMedia & Creative

Install Aliyun Wan Image

skills CLI

$ npx skills add cinience/alicloud-skills --skill aliyun-wan-image -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install cinience/alicloud-skills aliyun-wan-image --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/cinience/alicloud-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ai/image/aliyun-wan-image .claude/skills/aliyun-wan-image && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "aliyun-wan-image" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/image/aliyun-wan-image into .claude/skills/aliyun-wan-image/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-wan-image", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/cinience/alicloud-skills/tree/main/skills/ai/image/aliyun-wan-image

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add cinience/alicloud-skills --skill aliyun-wan-image -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install cinience/alicloud-skills aliyun-wan-image --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/cinience/alicloud-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ai/image/aliyun-wan-image .agents/skills/aliyun-wan-image && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "aliyun-wan-image" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/image/aliyun-wan-image into .agents/skills/aliyun-wan-image/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-wan-image", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add cinience/alicloud-skills --skill aliyun-wan-image -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install cinience/alicloud-skills aliyun-wan-image --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/cinience/alicloud-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ai/image/aliyun-wan-image .cursor/skills/aliyun-wan-image && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "aliyun-wan-image" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/image/aliyun-wan-image into .cursor/skills/aliyun-wan-image/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-wan-image", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/cinience/alicloud-skills.git --path skills/ai/image/aliyun-wan-image

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add cinience/alicloud-skills --skill aliyun-wan-image -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install cinience/alicloud-skills aliyun-wan-image --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/cinience/alicloud-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ai/image/aliyun-wan-image .gemini/skills/aliyun-wan-image && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "aliyun-wan-image" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/image/aliyun-wan-image into .gemini/skills/aliyun-wan-image/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-wan-image", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install cinience/alicloud-skills aliyun-wan-image

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add cinience/alicloud-skills --skill aliyun-wan-image -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/cinience/alicloud-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ai/image/aliyun-wan-image .github/skills/aliyun-wan-image && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "aliyun-wan-image" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/image/aliyun-wan-image into .github/skills/aliyun-wan-image/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-wan-image", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add cinience/alicloud-skills --skill aliyun-wan-image -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install cinience/alicloud-skills aliyun-wan-image --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/cinience/alicloud-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ai/image/aliyun-wan-image .opencode/skills/aliyun-wan-image && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "aliyun-wan-image" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/image/aliyun-wan-image into .opencode/skills/aliyun-wan-image/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-wan-image", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: aliyun-wan-image
GitHub stars: 397
Token cost: ~1.5k tokens
SKILL.md length: 423 words
Files: 4 (incl. scripts, references)
Skills in repo: 96
Repo updated: Aug 11, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

A skill your agent uses when generating or editing images with DashScope Wan 2.7 image models (wan2.7-image, wan2.7-image-pro).

Works in 4 steps: Confirm user intent: text-to-image,… → Select appropriate model (pro for 4K or… → Execute with explicit parameters and… → …
Editing images with DashScope Wan 2.7 image models (wan2.7-image
SKILL.md covers Validation, Output And Evidence, Prerequisites and Critical model names, plus 10 more sections
Runs Python scripts from its folder; calls python and python3; reaches dashscope.aliyuncs.com; needs DASHSCOPE_API_KEY

What it does

Aliyun Wan Image is an agent skill from cinience/alicloud-skills. Use when generating or editing images with DashScope Wan 2.7 image models (wan2.7-image, wan2.7-image-pro). Use when implementing text-to-image, image editing, interactive editing with bounding boxes, sequential group image generation, or color palette control via the multimodal-generation API.

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/api_reference.md`, `references/sources.md` and `scripts/generate_image.py`).

It sits in Media & Creative, covering Image generation, Image editing and Theming and dark mode. It works with Alibaba Cloud. The repository describes itself as: alibaba cloud skills，qwen ，wan and all skills. The licence is MIT.

When your agent uses it

Editing images with DashScope Wan 2.7 image models (wan2.7-image
Wan2.7-image-pro)
Implementing text-to-image
Interactive editing with bounding boxes

Example prompts

“/aliyun-wan-image”

Requirements

Python 3
A credential in DASHSCOPE_API_KEY

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

Confirm user intent: text-to-image, image editing, group generation, or interactive editing.
Select appropriate model (pro for 4K or higher quality, standard for speed).
Execute with explicit parameters and bounded scope.
Download and save generated images before URL expiration.

What it can do on your machine

Read from SKILL.md and the folder at commit 1818263. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
- python
- python3
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
- dashscope.aliyuncs.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
- DASHSCOPE_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Aliyun Wan Image loads about 1.5k tokens when it runs, and up to ~2.2k if it reads all its reference files. Until then it costs about 78 tokens; SKILL.md has 423 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~78
When it runs · the whole SKILL.md, loaded when a task matches: ~1.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~2.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from cinience/alicloud-skills at commit 1818263, republished under its MIT licence (© cinience). 423 words, ~1,486 tokens.

Download SKILL.mdSave it as .claude/skills/aliyun-wan-image/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.

name: aliyun-wan-image
description: Use when generating or editing images with DashScope Wan 2.7 image models (wan2.7-image, wan2.7-image-pro). Use when implementing text-to-image, image editing, interactive editing with bounding boxes, sequential group image generation, or color palette control via the multimodal-generation API.

Wan 2.7 Image Generation & Editing

Validation

bash

mkdir -p output/aliyun-wan-image
python -m py_compile skills/ai/image/aliyun-wan-image/scripts/generate_image.py && echo "py_compile_ok" > output/aliyun-wan-image/validate.txt

Pass criteria: command exits 0 and output/aliyun-wan-image/validate.txt is generated.

Output And Evidence

Write generated image URLs, prompts, and metadata to output/aliyun-wan-image/.
Keep at least one sample JSON response per run.

Prerequisites

Install SDK (recommended in a venv):

bash

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.

Critical model names

wan2.7-image-pro — professional version, supports 4K output
wan2.7-image — faster generation, up to 2K

Capabilities

Capability	Description
Text-to-image	Generate images from text prompts
Image editing	Edit images with text instructions (1-9 input images)
Interactive editing	Edit specific regions via bounding boxes (`bbox_list`)
Group generation	Generate consistent multi-image sequences (`enable_sequential=true`, up to 12 images)
Color palette	Control color theme with custom hex+ratio palette (3-10 colors)
Thinking mode	Enhanced reasoning for better quality (text-to-image only)

API endpoint

Sync (recommended):

POST https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation

Async (for long tasks):

POST https://dashscope.aliyuncs.com/api/v1/services/aigc/image-generation/generation
Header: X-DashScope-Async: enable

Normalized interface (image.generate)

Request

prompt (string, required) — up to 5000 characters
size (string, optional) — 1K, 2K (default), 4K (pro only), or WxH pixel values
n (int, optional) — number of images, 1-4 (default 4), or 1-12 with enable_sequential
seed (int, optional) — range [0, 2147483647]
reference_image (string/array, optional) — URL or base64, up to 9 images
enable_sequential (bool, optional) — group image generation mode
thinking_mode (bool, optional, default true) — enhanced reasoning (text-to-image only)
bbox_list (array, optional) — bounding boxes for interactive editing
color_palette (array, optional) — custom color theme (3-10 colors with hex+ratio)
watermark (bool, optional, default false)

Response

image_url (string) — PNG, valid for 24 hours
image_count (int)
size (string) — actual output resolution
seed (int)

Quick start (Python + DashScope SDK)

python

import os
from dashscope.aigc.image_generation import ImageGeneration

def generate_image(req: dict) -> dict:
    messages = [
        {
            "role": "user",
            "content": [{"text": req["prompt"]}],
        }
    ]

    # Add reference images if provided
    ref_images = req.get("reference_images") or []
    if req.get("reference_image"):
        ref_images = [req["reference_image"]] + ref_images
    for img in ref_images:
        messages[0]["content"].append({"image": img})

    params = {
        "model": req.get("model", "wan2.7-image"),
        "messages": messages,
        "size": req.get("size", "2K"),
        "n": req.get("n", 1),
        "api_key": os.getenv("DASHSCOPE_API_KEY"),
        "seed": req.get("seed"),
        "watermark": req.get("watermark", False),
    }

    if req.get("enable_sequential"):
        params["enable_sequential"] = True
    if req.get("thinking_mode") is not None:
        params["thinking_mode"] = req["thinking_mode"]
    if req.get("bbox_list"):
        params["bbox_list"] = req["bbox_list"]
    if req.get("color_palette"):
        params["color_palette"] = req["color_palette"]

    response = ImageGeneration.call(**params)

    content = response.output["choices"][0]["message"]["content"]
    images = [item["image"] for item in content if isinstance(item, dict) and item.get("image")]

    return {
        "image_urls": images,
        "image_count": response.usage.get("image_count"),
        "size": response.usage.get("size"),
    }

Show full SKILL.md (174 more words)Show less

Size reference

Model	Supported sizes	Default
wan2.7-image-pro	1K, 2K, 4K (text-to-image only), or [768, 4096] px	2K
wan2.7-image	1K, 2K, or [768, 2048] px	2K

Error handling

Error	Likely cause	Action
401/403	Missing or invalid `DASHSCOPE_API_KEY`	Check env var or credentials file.
400 `InvalidParameter`	Unsupported size, bad n value, or missing required image	Validate parameters against model limits.
429	Rate limit or quota	Retry with backoff.

Output location

Default output: output/aliyun-wan-image/images/
Override base dir with OUTPUT_DIR.

Anti-patterns

Do not invent model names; use wan2.7-image or wan2.7-image-pro only.
Do not use 4K size with wan2.7-image (only pro supports 4K).
Do not use enable_sequential with bbox_list — they are separate modes.
Image URLs expire after 24 hours; download and persist immediately.

Workflow

Confirm user intent: text-to-image, image editing, group generation, or interactive editing.
Select appropriate model (pro for 4K or higher quality, standard for speed).
Execute with explicit parameters and bounded scope.
Download and save generated images before URL expiration.

References

See references/api_reference.md for full HTTP API details.
See references/sources.md for source links.

Files

SKILL.md and 3 other files (scripts, references) in skills/ai/image/aliyun-wan-image of cinience/alicloud-skills.

SKILL.md
references/api_reference.md
references/sources.md
scripts/generate_image.py

Open the folder on GitHubat commit 1818263

Compare with similar skills

Aliyun Wan Image next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Aliyun Wan Image compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Aliyun Wan Image this skillcinience/alicloud-skills	397	—	~1.5k	Automated safety check: Pass	MIT	2 mo ago
AI Image Generation and Editingzhayujie/CowAgent	47k	—	~1.3k	Automated safety check: Pass	MIT	today
Generate Imageynulihao/AgentSkillOS	618	10 repos	~1.7k	Automated safety check: Notes	None	7 mo ago
GPT Image Generation CLIwuyoscar/GPT-Image2-Skill	5.7k	—	~2.5k	Automated safety check: Notes	MIT	10 days ago
BlockRun Image GenerationBlockRunAI/ClawRouter	6.6k	—	~2.1k	Automated safety check: Pass	MIT	5 days ago
Native Transparent ImagegenZSeven-W/craft-skills	225	1 repos	~1.1k	Automated safety check: Pass	Apache-2.0	18 days ago

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Works with

Alibaba Cloud

Questions about Aliyun Wan Image

What does Aliyun Wan Image do?

A skill your agent uses when generating or editing images with DashScope Wan 2.7 image models (wan2.7-image, wan2.7-image-pro). Aliyun Wan Image is an agent skill from cinience/alicloud-skills.7-image-pro).

When should I use Aliyun Wan Image?

Aliyun Wan Image fits situations like: editing images with DashScope Wan 2.7 image models (wan2.7-image; wan2.7-image-pro); implementing text-to-image; interactive editing with bounding boxes.

How do I install Aliyun Wan Image in Claude Code?

Run `npx skills add cinience/alicloud-skills --skill aliyun-wan-image -a claude-code`. Or copy the skill folder (skills/ai/image/aliyun-wan-image in cinience/alicloud-skills) into .claude/skills/aliyun-wan-image in your project. Claude Code loads it when a task matches its description.

How do I install Aliyun Wan Image in Codex?

Run `npx skills add cinience/alicloud-skills --skill aliyun-wan-image -a codex`. Or copy the skill folder (skills/ai/image/aliyun-wan-image in cinience/alicloud-skills) into .agents/skills/aliyun-wan-image in your project. Codex loads it when a task matches its description.

Can I use Aliyun Wan Image in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add cinience/alicloud-skills --skill aliyun-wan-image -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/aliyun-wan-image, .gemini/skills/aliyun-wan-image, .github/skills/aliyun-wan-image and .opencode/skills/aliyun-wan-image in your project.

What does Aliyun Wan Image need to run?

Going by SKILL.md and its folder, Aliyun Wan Image needs Python for the scripts in its folder, the command-line tools its instructions call (python and python3) and credentials named DASHSCOPE_API_KEY. Our summary lists: Python 3; A credential in DASHSCOPE_API_KEY.

Does Aliyun Wan Image access the network?

SKILL.md names 1 domain. In commands or code: dashscope.aliyuncs.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Aliyun Wan Image safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Aliyun Wan Image use?

Aliyun Wan Image is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Aliyun Wan Image use?

About 1.5k tokens (SKILL.md is roughly 5.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 750 tokens, read only when the agent opens those files.

What are the alternatives to Aliyun Wan Image?

Skills that share tags, products or a category with Aliyun Wan Image: AI Image Generation and Editing (zhayujie/CowAgent, 47k stars), Generate Image (ynulihao/AgentSkillOS, 618 stars), GPT Image Generation CLI (wuyoscar/GPT-Image2-Skill, 5.7k stars) and BlockRun Image Generation (BlockRunAI/ClawRouter, 6.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Aliyun Wan Image?

cinience (a GitHub user) maintains it in cinience/alicloud-skills, which has 397 GitHub stars. The repository holds 96 skills in this directory. The repository was last updated on August 11, 2026.

Source: cinience/alicloud-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Aliyun Wan Image

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Wan 2.7 Image Generation & Editing

Validation

Output And Evidence

Prerequisites

Critical model names

Capabilities

API endpoint

Normalized interface (image.generate)

Request

Response

Quick start (Python + DashScope SDK)

Size reference

Error handling

Output location

Anti-patterns

Workflow

References

Files

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