AI-Assisted Frontend Reviews Using Gemma 4

PR Sentinel is an AI-assisted tool that uses Gemma 4 to analyze React and TypeScript code snippets, generating structured engineering feedback focused on maintainability, accessibility, performance, and UI quality. Inspired by common enterprise frontend review pain points like stale closures and infinite re-renders, the tool organizes feedback into categorized review cards resembling senior-level comments. The project includes a live demo and built-in diagnostic sandbox scenarios to simulate real React engineering issues.

This is a submission for the Gemma 4 Challenge: Build with Gemma 4 PR Sentinel analyzes React and TypeScript snippets and generates structured engineering feedback focused on maintainability, accessibility, performance, and UI quality. PR Sentinel is an AI-assisted frontend PR reviewer focused on React and TypeScript engineering quality. Developers can paste frontend code snippets and receive structured engineering feedback across: The project was inspired by real frontend review pain points commonly seen in enterprise applications, especially issues related to stale closures, infinite re-renders, semantic accessibility structure, and reusable component design. Instead of producing generic AI summaries, PR Sentinel organizes feedback into categorized engineering review cards that resemble actual senior-level frontend review comments. Live demo uses a limited development API configuration and may occasionally be unavailable during evaluation periods. https://github.com/naomirasamalla/Frontend-PR-Review-Assistant The application allows developers to paste frontend snippets and receive categorized AI-generated engineering review feedback in real time. Key Features: AI-powered React/TypeScript review analysis Structured frontend engineering feedback Accessibility-focused review insights UI/UX and maintainability recommendations Real-time review rendering PR Sentinel uses Gemma 4 to analyze React and TypeScript frontend code snippets and generate structured PR-style engineering feedback. The project focuses on identifying practical frontend issues such as: Gemma 4 was selected because the project required fast reasoning over frontend engineering patterns while generating concise, developer-focused review output. The model is used to evaluate pasted code snippets and return structured recommendations similar to a lightweight frontend pull request review workflow. The application includes built-in diagnostic sandbox scenarios that simulate real frontend engineering issues commonly encountered in React applications.