About .cursorrules prompt file
What you can build
Recipe Collaboration Platform: Create a platform where multiple users can collaboratively create and edit recipes, with real-time updates and AI suggestions for improvements or alternative ingredients.
Dynamic Meal Planner: Develop an app that uses AI to generate personalized meal plans based on user dietary preferences, restrictions, and available ingredients, integrating seamlessly with Dishify for recipe suggestions.
Smart Kitchen Assistant: Design a comprehensive smart kitchen assistant that integrates with IoT devices to manage cooking timers, suggest recipes based on fridge inventory, and provide cooking instructions via voice commands.
Grocery Optimizer: Build an AI-driven tool that optimizes grocery shopping lists by analyzing store promotions, availability, and user preferences for cost-effective and time-efficient shopping trips.
Sustainable Cooking Guide: Create a service that offers eco-friendly recipe alternatives, highlighting sustainable ingredients and cooking methods to reduce carbon footprints, with integration into Dishify's recipe database.
Culinary Education Platform: Launch an educational platform offering interactive cooking classes and tutorials, utilizing AI to tailor lessons to users' skill levels and preferred cuisines, with integration into Dishify's ecosystem.
Recipe Monetization Marketplace: Develop a marketplace where chefs and home cooks can share or sell their unique recipes, with Dishify providing AI validation of recipe quality and potential allergen alerts.
Dietary Tracking Companion: Implement a nutrition tracking component that links with fitness and health apps, offering personalized dietary feedback based on Dishify's AI-generated recipes and consumption patterns.
AI-Powered Flavor Pairing Tool: Create a tool that suggests unexpected ingredient pairings based on flavor profiles and culinary trends, enhancing Dishify's recipe database with innovative flavor combinations.
Localized Ingredient Finder: Design an app feature that helps users find local substitutes for ingredients not available in their region, leveraging community-sourced data and AI recommendations for similar taste profiles.
Benefits
- Cross-Platform Support: The project utilizes Next.js for web, Expo for mobile, and React Native for cross-platform development, ensuring broad accessibility across devices.
- Type-Safe API Communication: Utilizes tRPC for robust, type-safe API interactions, complementing TypeScript's strong typing for comprehensive type safety.
- CI/CD and Deployment: Integrates GitHub Actions for continuous integration and Cloudflare for seamless deployment of web and backend services.
Synopsis
Developers building cross-platform AI-based culinary apps with a focus on consistency, accessibility, and performance will benefit, enabling optimized recipe generation and shopping features.
Overview of .cursorrules prompt
The .cursorrules file outlines the project guidelines for Dishify, an AI-powered culinary companion application. It details the tech stack utilized, which includes technologies like Next.js, Expo, and Cloudflare Workers, and describes the project structure and conventions around code style, file naming, styling with Tailwind CSS, and state management. It also covers performance optimization techniques, error handling, testing with Jest, CI/CD practices via GitHub Actions, and deployment strategies. The file highlights the use of environment variables, code quality tools like Biome, and accessibility standards. Additionally, it provides guidelines for commenting style and maintaining consistency in code documentation.
