imagenCN
agent
Gecti
Health Gecti
- License — License: MIT
- Description — Repository has a description
- Active repo — Last push 0 days ago
- Community trust — 10 GitHub stars
Code Gecti
- Code scan — Scanned 1 files during light audit, no dangerous patterns found
Permissions Gecti
- Permissions — No dangerous permissions requested
Purpose
This is a Python-based agent skill designed for Claude Code and similar AI CLIs that enables natural language image generation. It uses the Alibaba Cloud Bailian API (Qwen/Wan models) to create images, with a specific focus on Chinese text rendering and photorealistic outputs.
Security Assessment
The overall risk is rated as Low. The automated code scan checked the core files and found no dangerous patterns, hardcoded secrets, or malicious code. The tool requires a third-party API key (`DASHSCOPE_API_KEY`) that you must provide and store as an environment variable. It makes external network requests to Alibaba Cloud to generate the images, which is expected behavior for this type of service. It does not request dangerous system permissions and does not appear to execute arbitrary shell commands beyond its intended Python script usage.
Quality Assessment
The project is very new and currently has low community visibility with only 8 GitHub stars, meaning it has not been widely battle-tested by a large user base. However, the repository is actively maintained (last updated today), has a clear description, and is fully licensed under the permissive and standard MIT license. The documentation is highly detailed, providing transparent instructions for installation, usage, and multi-region setup.
Verdict
Safe to use, though developers should be aware of the project's low community adoption and ensure they follow data handling best practices when configuring their Alibaba Cloud API keys.
This is a Python-based agent skill designed for Claude Code and similar AI CLIs that enables natural language image generation. It uses the Alibaba Cloud Bailian API (Qwen/Wan models) to create images, with a specific focus on Chinese text rendering and photorealistic outputs.
Security Assessment
The overall risk is rated as Low. The automated code scan checked the core files and found no dangerous patterns, hardcoded secrets, or malicious code. The tool requires a third-party API key (`DASHSCOPE_API_KEY`) that you must provide and store as an environment variable. It makes external network requests to Alibaba Cloud to generate the images, which is expected behavior for this type of service. It does not request dangerous system permissions and does not appear to execute arbitrary shell commands beyond its intended Python script usage.
Quality Assessment
The project is very new and currently has low community visibility with only 8 GitHub stars, meaning it has not been widely battle-tested by a large user base. However, the repository is actively maintained (last updated today), has a clear description, and is fully licensed under the permissive and standard MIT license. The documentation is highly detailed, providing transparent instructions for installation, usage, and multi-region setup.
Verdict
Safe to use, though developers should be aware of the project's low community adoption and ensure they follow data handling best practices when configuring their Alibaba Cloud API keys.
Claude Code skill for AI image generation using Alibaba Cloud Bailian API (通义千问/通义万相)
README.md
ImagenCN — AI Image Generation with Chinese Text Excellence
A Claude Code / OpenClaw skill for AI image generation using Alibaba Cloud Bailian API.
Why This Skill?
| Feature | This Skill | Native Claude Code | Other Image Skills |
|---|---|---|---|
| Chinese text rendering | ✓ Qwen-Image optimized | ✗ No image generation | Partial |
| Photorealistic images | ✓ Wan series multi-model | ✗ No image generation | Partial |
| Multi-model selection | ✓ 15+ models to choose from | ✗ N/A | Usually single model |
| Size presets | ✓ 7+ aspect ratios | ✗ N/A | Partial |
| Negative prompts | ✓ Fine-grained control | ✗ N/A | Partial |
| CLI direct invocation | ✓ Script ready to use | ✗ N/A | Requires custom code |
| Multi-region API | ✓ China/Singapore/Virginia | ✗ N/A | Usually single region |
Key advantages:
- Best Chinese text — Qwen-Image is one of the best models for rendering Chinese text on images
- Realism + art — Wan series covers everything from quick drafts to professional-grade output
- Ready to use —
pip installtwo packages + one API key to get started
Features
- Qwen-Image 2.0: Latest flagship, native 2K, professional typography rendering
- Qwen-Image Edit: Instruction-based image editing (
--imageinput) - Qwen-Image legacy: Lighter Chinese/English text rendering models
- Wan Series: Photorealistic images and photography-grade visuals, Wan2.7 supports 4K
- Z-Image: Lightweight, fast and low-cost; high-fidelity portraits and product shots
- Multiple size presets: 1:1, 16:9, 9:16, 4:3, 3:4, plus 1K/2K/4K
- Cross-platform: Windows, macOS, Linux support
- Multiple API regions: China (default), Singapore, Virginia
Install the Skill
Claude Code (global):
git clone https://github.com/Agents365-ai/imagenCN.git ~/.claude/skills/imagenCN
Claude Code (project-specific):
git clone https://github.com/Agents365-ai/imagenCN.git .claude/skills/imagenCN
OpenClaw:
git clone https://github.com/Agents365-ai/imagenCN.git skills/imagenCN
SkillsMP: Search imagenCN on skillsmp.com for one-click install.
Requirements
System Requirements
- Python 3.8+
- pip
Install Dependencies
pip install dashscope requests
API Key
Get your API key from Alibaba Cloud Bailian Console
export DASHSCOPE_API_KEY="your_api_key"
Optional Environment Variables
# Set default model (default: qwen-image-2.0-pro)
export DASHSCOPE_MODEL="wan2.7-image-pro"
# Set API endpoint (default: cn)
export DASHSCOPE_API_BASE="cn" # or "sg", "us", or full URL
Quick Start
Natural Language (Claude Code)
Just tell Claude what you want:
Generate an image of a cute orange cat
Create a poster with text "Happy New Year" in Chinese
Make a photorealistic 4K mountain sunset photo using wan2.7-image-pro
Generate a 16:9 landscape wallpaper
Command Line
# Basic usage (default model: qwen-image-2.0-pro, native 2K)
python ~/.claude/skills/imagenCN/scripts/generate_image.py "A cute cat" output.png
# Photorealistic 4K with Wan2.7
python ~/.claude/skills/imagenCN/scripts/generate_image.py --model wan2.7-image-pro --size 4K "Mountain sunset" photo.png
# Custom size
python ~/.claude/skills/imagenCN/scripts/generate_image.py --size 16:9 "Wide landscape" landscape.png
# Edit an existing image (requires --image)
python ~/.claude/skills/imagenCN/scripts/generate_image.py --model qwen-image-edit-max --image input.png "Change the background to a beach" edited.png
# With negative prompt
python ~/.claude/skills/imagenCN/scripts/generate_image.py --negative "blurry" "High quality portrait" portrait.png
# List available models
python ~/.claude/skills/imagenCN/scripts/generate_image.py --list-models
Models
| Model | Best For |
|---|---|
qwen-image-2.0-pro |
Default, latest flagship, native 2K, strongest typography and detail |
qwen-image-2.0-pro-2026-06-22 |
Latest snapshot (Jun 2026), generation + editing fusion |
qwen-image-2.0 |
Standard 2.0 tier, native 2K |
qwen-image-max |
Previous-gen flagship |
qwen-image-max-2025-12-30 |
qwen-image-max snapshot, improved realism |
qwen-image-plus |
Distilled accelerated version |
qwen-image-plus-2026-01-09 |
qwen-image-plus snapshot (Jan 2026) |
qwen-image-edit-max |
Flagship image editing (requires --image) |
qwen-image-edit-max-2026-01-16 |
Latest editing snapshot (Jan 2026) |
qwen-image-edit-plus |
Fast, lower-cost image editing |
qwen-image |
Base model |
wan2.7-image-pro |
Latest photorealistic, up to 4K output |
wan2.7-image |
Wan 2.7 standard, up to 2K |
wan2.6-t2i |
Wan 2.6, flexible sizing |
wan2.5-t2i-preview |
High quality art |
wan2.2-t2i-flash |
Fast generation |
wan2.2-t2i-plus |
Professional tier |
wanx2.1-t2i-turbo |
Fast execution |
wanx2.1-t2i-plus |
Professional tier |
wanx2.0-t2i-turbo |
Earlier generation |
z-image-turbo |
Lightweight, fast & low-cost; portraits and product images |
Size Presets
Qwen-Image 2.0 (native 2K):
1:1→ 2048×2048 (default)16:9→ 2688×15369:16→ 1536×26884:3→ 2304×17283:4→ 1728×23041K→ 1024×10242K→ 2048×2048
Qwen-Image legacy:
1:1→ 1328×132816:9→ 1664×9289:16→ 928×16644:3→ 1472×11043:4→ 1104×1472
Z-Image (pixel area 512×512 to 2048×2048):
1:1→ 1024×1024 (default)16:9→ 1280×7209:16→ 720×12802:3→ 1024×15363:2→ 1536×1024
Wan Series (Wan2.7 also accepts 1K/2K/4K):
1:1→ 1024×10241:1-large→ 1280×128016:9→ 1280×7209:16→ 720×12804:3→ 1200×9003:4→ 900×12002:1→ 1440×720
API Endpoints
| Region | Alias | URL |
|---|---|---|
| China (default) | cn |
https://dashscope.aliyuncs.com/api/v1 |
| Singapore | sg |
https://dashscope-intl.aliyuncs.com/api/v1 |
| Virginia | us |
https://dashscope-us.aliyuncs.com/api/v1 |
License
MIT License
Support
If this project helps you, consider supporting the author:
WeChat Pay |
Alipay |
Buy Me a Coffee |
Give a Reward |
Author
Agents365-ai
- Bilibili: https://space.bilibili.com/441831884
- GitHub: https://github.com/Agents365-ai
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