Agent skill

qwen-image-2-pro

Generate images with Alibaba Qwen-Image-2.0-Pro via inference.sh CLI. Professional text rendering, fine-grained realism, enhanced semantic adherence. Ideal for posters, banners, and text-heavy designs. Triggers: qwen image pro, qwen-image-pro, qwen 2 pro, alibaba image pro, dashscope pro, professional text rendering

majiayu000534★ · 1 repos on radarProfile →
claude-coderead-onlyMIT
Install
npx skills add majiayu000/claude-skill-registry --skill qwen-image-2-pro --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 6 KB
Bundled scripts: none
Allowed tools: Bash(infsh*)
Path: skills/ai-llm/qwen-image-2-pro/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Qwen-Image Pro - Professional Image Generation Generate images with Alibaba Qwen-Image-2.0-Pro via [inference.sh](https://inference.sh) CLI. Best for professional text rendering and complex designs. ![Qwen-Image-2.0-Pro](https://cloud.inference.sh/app/files/u/4mg21r6ta37mpaz6ktzwtt8krr/01kjtkdzbxw3ma6wx4j1e42yry.jpeg) ## Quick Start > Requires inference.sh CLI (`infsh`). Get installation instructions: `npx skills add inference-sh/skills@agent-tools` ```bash infsh login infsh app run alibaba/qwen-image-2-pro --input '{"prompt": "Poster with title \"Welcome!\" in bold blue text"}' ``` ## Pro Model Capabilities - **Professional Text Rendering**: Multi-line and paragraph-level text with fine-grained detail - **Fine-grained Realism**: Better textures and photorealistic scenes - **Stronger Semantic Adherence**: More accurately follows complex prompts - **Complex Designs**: Ideal for text + image combinations ## Examples ### Basic Text-to-Image ```bash infsh app run alibaba/qwen-image-2-pro --input '{ "prompt": "A futuristic cityscape at sunset with flying cars" }' ``` ### Text-Heavy Poster ```bash infsh app run alibaba/qwen-image-2-pro --input '{ "prompt": "Healing-style hand-drawn pos

What's inside
Steps it walks through
  1. Quick Start
  2. Pro Model Capabilities
  3. Examples
  4. Basic Text-to-Image
  5. Text-Heavy Poster
  6. Marketing Banner
  7. Multiple Variations
  8. Image Editing (Style Transfer)
  9. Reproducible Generation
  10. Input Options
  11. Output
  12. Text Rendering Tips
  13. Recommended Negative Prompt
  14. Sample Workflow
Ships with 1 file
  • metadata.json
Commands it runs
infsh login
infsh app run alibaba/qwen-image-2-pro --input '{"prompt": "Poster with title \"Welcome!\" in bold blue text"}'
infsh app run alibaba/qwen-image-2-pro --input '{
infsh app sample alibaba/qwen-image-2-pro --save input.json
infsh app run alibaba/qwen-image-2-pro --input input.json
Standard Qwen-Image (faster, general use)
npx skills add inference-sh/skills@qwen-image
Full platform skill (all 150+ apps)
npx skills add inference-sh/skills@agent-tools
All image generation models
More from claude-skill-registry
All skills →
About this skill
What does the qwen-image-2-pro skill do?

Generate images with Alibaba Qwen-Image-2.0-Pro via inference.sh CLI. Professional text rendering, fine-grained realism, enhanced semantic adherence. Ideal for posters, banners, and text-heavy designs. Triggers: qwen image pro, qwen-image-pro, qwen 2 pro, alibaba image pro, dashscope pro, professional text rendering

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill qwen-image-2-pro --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going