Show HN: JSON Schema for Google Gemini Image Generation (github.com)

A new open-source project delivers a robust JSON schema tailored for Google’s Gemini image generation API, enabling engineers and prompt authors to create repeatable, high-fidelity image prompts with enhanced structure and precision. By transforming a proven slide framework into an opinionated, validated JSON schema alongside lightweight Python and optional Node.js validators, the repo streamlines prompt construction into reusable, lintable, and version-controlled objects. This brings greater consistency and control over visual dimensions such as style, composition, and materials, reducing ambiguity and unexpected results in image outputs. The project includes practical tools like a CLI validator, minimal example prompts, and a comprehensive cookbook demonstrating Gemini API calls mapped directly to the schema in both Python and JavaScript. It also offers automated testing scripts to validate schema compliance, run sample generation workflows, and simulate continuous integration pipelines. This fosters best practices in prompt engineering for Gemini’s image generation platform while encouraging community-driven enhancements under an MIT license. By providing structured, versioned prompt definitions aligned with Gemini’s official docs, the repo promises to improve reproducibility and collaboration in AI-driven creative workflows, marking a key step forward for developers working with Google’s latest generative AI tooling.