Pickawesome-gpt-image-2: Structuring GPT-Image2 Prompts with 532 Reverse-Engineering Cases

Image generation with GPT-Image2 has moved beyond mere 'possibility' into the stage of 'stable control'. This repository collects 532 successful cases scattered across the community and restructures prompts as assets that can be treated like code. Rather than a sporadic collection of examples, it provides structured protocols that are immediately reusable in agent and automation workflows.

The core concept is decomposing prose-style prompts into atomic schemas. Components such as subject, lighting, materials, layout, and visual details are separated into combinable units. This maintains consistency in layout and information hierarchy during batch generation and makes it easier to build template systems.

It provides cases categorized into 13 categories, including UI interfaces, infographics, posters, product photography, and brand logos. Each category is composed of prompt templates focused on the core competencies of that domain (e.g., page hierarchy for UI, data structure for infographics). It supports a workflow where you first choose a visual direction and then convert it into a reusable structure.

This is suitable for developers looking to build reproducible production pipelines rather than just simple image generation. The repository includes agent skills to assist with style selection, allowing direct integration into scripts or automation systems. Released under the MIT License, it can be freely used in commercial projects or internal tool development.