wuyoscar/GPT-Image2-Skill

What it solves

This project provides a curated library of prompts and a set of tools to help users effectively generate and edit images using the gpt-image-2 model. It bridges the gap between raw API access and high-quality output by providing a gallery of proven prompts for various styles (e.g., research figures, UI mockups, photography) and a CLI for easy execution.

How it works

The project operates through three primary interfaces:

• CLI Tool: A command-line interface (gpt-image) that allows users to generate images from text or edit existing images using reference images and masks via the OpenAI API.
• Agent Skills: Pluggable skills for AI agent runtimes (like Claude Code, Codex, and OpenClaw) that enable agents to generate images or extract prompts from existing images using vision-capable models.
• Prompt Gallery: A curated collection of prompts and metadata (size and quality settings) that serve as templates for high-quality results.

Who it’s for

• AI Artists and Designers: Those looking for a library of high-quality prompt templates for diverse visual styles.
• Developers: Users who want a CLI to quickly iterate on image generation and editing without writing boilerplate code.
• Agent Users: People using skill-capable AI agents who want to give their agents the ability to create or reverse-engineer images.

Highlights

• Reverse Prompting: Includes a get-prompt-from-image skill that uses vision models to extract reusable prompts from reference images.
• Multi-Reference Editing: Supports passing multiple reference images to the edits endpoint for complex compositions.
• Agent Integration: Specifically designed to be installed as a plugin/skill for various AI agent runtimes.
• Detailed Parameter Control: Provides granular control over image size, quality (low/medium/high), and output formats.