gpt-image-2-style-library
Choose GPT-Image2 / gpt-image-2 visual styles and industrial prompt templates from the awesome-gpt-image-2 style library. Use when an agent needs to create, rewrite, classify, or improve image-generation prompts with repository-backed templates, categories, style tags, scene tags, pitfalls, and example cases.
Works with
--- name: gpt-image-2-style-library description: Choose GPT-Image2 / gpt-image-2 visual styles and industrial prompt templates from the awesome-gpt-image-2 style library. Use when an agent needs to create, rewrite, classify, or improve image-generation prompts with repository-backed templates, categories, style tags, scene tags, pitfalls, and example cases. license: MIT --- # GPT-Image2 Style Library Use this skill to turn a user's image-generation intent into a production-ready GPT-Image2 prompt using the awesome-gpt-image-2 style library. ## Example Output  Example request: `用 gpt-image-2-style-library 技能生成城市生命系统图谱` ## Reference - Read `references/style-library.md` before choosing a template or style. - The reference is generated from `data/style-library.json` in the repository. - Prefer the reference over memory when template names, categories, covers, or style tags matter. ## Workflow 1. Detect the user's language and answer in that language. 2. Identify the user's target output: product, poster, UI, infographic, brand, photo, illustration, character, scene, history, document, or special task. 3. Match the request in this order: template category, visual style tag, scene tag, then nearest example cases. 4. If one template is clearly strongest, use it directly. If several are plausible, present 2-3 options with short reasons and ask the user to choose. 5. Build the final prompt with these blocks: - subject and task - composition and layout - visual style and materials - text and label requirements - aspect ratio and output format - constraints and negative details 6. Include the selected template name and any useful example case IDs. ## Output Defaults - Provide a copyable prompt first. - Keep constraints concrete: exact text, aspect ratio, readable labels, layout hierarchy, and avoided artifacts. - For Chinese requests, write the final prompt in Chinese unless the user asks for English. - For English requests, write the final prompt in English unless the user asks for Chinese. - When the user asks for multiple concepts, reuse one template and vary subject, composition, palette, and scene. ## Maintenance When the source repository changes, run: ```bash npm run generate:style-skill ``` To install the skill into the local Codex skill folder, run: ```bash npm run install:skill ```
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