wuyoscar/GPT-Image2-Skill

What it solves

This project provides a comprehensive toolkit for working with GPT Image 2 and 2.5, streamlining the process of generating, editing, and reverse-engineering images. It solves the difficulty of crafting precise prompts for high-quality AI image generation and the complexity of managing reference-image workflows through a curated gallery and dedicated tools.

How it works

The project consists of three main components:

• Prompt Gallery: A collection of 163 numbered entries across 31 categories providing proven prompts and reference images.
• Agent Skills: Two specific skills (gpt-image and get-prompt-from-image) that can be integrated into agent runtimes like Claude Code, Codex, and OpenClaw to handle image generation/editing and prompt extraction.
• CLI: A command-line interface that allows users to generate images from text, edit images using reference images or masks (inpainting), and specify model versions (e.g., gpt-image-2.5-flare or gpt-image-2.5-sunburst).

Who it’s for

It is designed for designers, industrial designers, and AI artists who need precise control over image generation, particularly those using reference images for layout or architectural cutaways, and those who want to integrate image generation capabilities directly into their AI agent workflows.

Highlights

• Reference-Based Generation: Supports multi-reference edits and mask-based inpainting to maintain layout anchors while changing styles or details.
• Prompt Extraction: Includes a vision-capable agent skill that can reverse-engineer a reusable English prompt from a reference image.
• Model Versatility: Supports multiple GPT Image models, including the 2.5 series for higher quality and precise edits.
• Extensive Gallery: Offers a large, curated library of prompts for various styles, including technical illustrations and isometric dioramas.