image-generation

📁 qwenlm/qwen-code-examples 📅 Feb 1, 2026
8
总安装量
6
周安装量
#33757
全站排名
安装命令
npx skills add https://github.com/qwenlm/qwen-code-examples --skill image-generation

Agent 安装分布

cursor 6
opencode 6
gemini-cli 5
github-copilot 5
codex 5
kimi-cli 5

Skill 文档

Image Generation Skill

This skill allows agents to automatically generate high-quality images (defaulting to hand-drawn style) based on user intent.

Core Features

  • Smart Prompt Optimization: Transforms simple user intent into detailed hand-drawn style prompts.
  • Fast Generation: Uses non-streaming interfaces to significantly speed up image generation.
  • Auto-Save: Automatically downloads generated images locally and saves metadata and API responses simultaneously.

Prerequisites

Before using this skill, ensure that the DASHSCOPE_API_KEY environment variable is set:

export DASHSCOPE_API_KEY="Your API Key"

User Guide

1. Refine the Prompt

You need to refine the user’s original intent into a prompt suitable for image generation. For hand-drawn versions of architecture or flowcharts, it’s recommended to include keywords like “hand-drawn”, “sketch”, “architectural drawing”, etc.

2. Run the Script

Use the following command to call the generation script:

node skills/image-generate/scripts/generate_image.js "Your detailed prompt"

3. View Results

After the script completes, it will generate the following files in the current directory:

  • image_YYYY-MM-DDTHH-mm-ss.png: The generated image file.
  • metadata_YYYY-MM-DDTHH-mm-ss.json: Metadata including prompt, file size, and duration.
  • response_YYYY-MM-DDTHH-mm-ss.json: Raw API response data (for debugging).

Example

User Intent: “Help me draw an architecture diagram of an AI coding assistant.”

Recommended Prompt: “A detailed hand-drawn architectural diagram of an AI coding assistant, showing the interaction between the user, the IDE, and the LLM, technical sketch style, clean lines, white background.”

Execution Command:

node skills/image-generate/scripts/generate_image.js "A detailed hand-drawn architectural diagram of an AI coding assistant, showing the interaction between the user, the IDE, and the LLM, technical sketch style, clean lines, white background."