<2-3 sentences summarising what the project addresses and solves, the target audience, and the benefit.> This project addresses the challenge of translating abstract creative ideas into precise, high-quality prompts for AI image generation models like gpt-image-2. It provides a Claude Code skill and a verification script to compile vague requests into detailed, production-ready prompts, benefiting users who need to generate specific visual assets efficiently and accurately.

How It Works

The core mechanism involves a Claude Code skill that takes a simple natural language request and transforms it into a structured prompt. This prompt meticulously defines scene composition, camera angles, lighting, color grading (using HEX codes), texture, and text placement. A companion Node.js script (check_prompt.mjs) acts as a validator, ensuring the generated prompts adhere to strict rules, such as avoiding negative phrasing and correctly formatting text elements, before they are passed to an image generation model.

Quick Start & Requirements

• Installation involves cloning the repository and creating a symbolic link to the image-prompt skill in the Claude environment (~/.claude/skills/image-prompt).
• Requires Node.js for the prompt validation script. Actual image generation necessitates Codex CLI login and a ChatGPT Plus/Pro subscription.
• An interactive demo is available at kimsh-1.github.io/gongnyang-prompt-kit.

Highlighted Details

• Automates the creation of detailed prompts for diverse visual assets, including posters, key art, infographics, product mockups, and comics.
• Supports complex outputs like infographics with high-density Korean text (up to 700-800 characters) and intricate diagrams (e.g., sequence diagrams, network graphs).
• Employs a structured prompt format with distinct sections for Scene, Camera, Lighting, Color Grading, Texture, and Text-in-image.
• Offers curated "look presets" and "concept axes" to guide aesthetic choices and explore variations systematically.
• Includes a robust validation system that enforces specific prompt engineering rules and prevents common pitfalls.

Maintenance & Community

The repository does not explicitly list maintainers, community channels (like Discord or Slack), or a public roadmap.

Licensing & Compatibility

The project is released under the MIT License, which permits broad use, including commercial applications, with minimal restrictions.

Limitations & Caveats

The kit functions solely as a prompt generator; it does not perform image synthesis itself. The prompt validation rules are strict and tailored for specific AI models, potentially limiting flexibility for users accustomed to more permissive prompt structures. Achieving high-density text accuracy in generated images is dependent on selecting appropriate aspect ratios (e.g., 16:9 or 2:3 are preferred over 21:9).