Project Rules

This rule provides comprehensive guidelines for developing robust, secure, and performant Tauri applications. It covers code organization, security best practices, performance optimization, testing strategies, and common pitfalls to avoid.

Comprehensive guide to TensorFlow best practices, covering code organization, performance, testing, and security for robust and maintainable machine learning projects.

This rule provides guidelines for Terraform best practices, coding standards, and security considerations to ensure maintainable, efficient, and secure infrastructure-as-code.

This rule provides guidelines and best practices for developing efficient, maintainable, and robust 3D web applications using Three.js. It covers aspects like code organization, performance optimization, security, testing, and common pitfalls to ensure a high-quality development experience.

This rule file provides comprehensive best practices for developing with tinygrad, covering code organization, performance, testing, and security. It aims to improve code quality, maintainability, and prevent common pitfalls when working with tinygrad.

This rule file outlines the best practices for developing GUI applications with tkinter in Python, including code organization, performance, security, testing, and tooling.

Comprehensive best practices and coding standards for the Tornado framework. This rule provides guidelines on code organization, performance, security, testing, and common pitfalls when developing Tornado applications.

This rule provides comprehensive best practices for using Tortoise ORM in Python projects, covering aspects like code organization, performance, security, and testing.

This rule file provides best practices and coding standards for using the `tqdm` library in Python. It focuses on performance, customization, and avoiding common pitfalls.

This rule set enforces best practices for developing with the transformers library, covering code organization, performance, security, and testing to promote maintainable and efficient NLP applications.

This rule provides comprehensive best practices for developing with the Trio asynchronous I/O library in Python, covering code organization, performance, testing, and common pitfalls.

This rule provides comprehensive guidance on tRPC best practices, covering code organization, performance, security, testing, and common pitfalls to ensure robust and maintainable tRPC applications.

This rule provides comprehensive best practices for developing with Turbopack, covering code organization, performance, security, testing, and tooling to ensure efficient and maintainable applications.

This rule provides best practices and coding standards for developing command-line interfaces (CLIs) using the Typer library in Python. It includes guidelines for code organization, performance, security, and testing, aiming to enhance usability and maintainability.

TypeScript coding standards and best practices

Enforces best practices for TypeScript development, including coding standards, performance considerations, and common pitfalls. This rule provides actionable guidance for developers to write clean, maintainable, and scalable TypeScript code.

This rule provides comprehensive best practices for writing effective, maintainable, and performant unit tests using Python's unittest library. It covers code organization, testing strategies, performance, security, and common pitfalls.

This rule provides best practices for Unity C# development, covering code style, organization, performance, and security to ensure maintainable and efficient projects.

Comprehensive best practices and coding standards for Unreal Engine projects. Covers code organization, performance, security, testing, and common pitfalls to ensure maintainable, efficient, and robust game development.

Enforces Vercel's recommended coding style, optimization strategies, and security best practices. This guide helps developers build performant, secure, and maintainable applications on the Vercel platform.

This rule file outlines best practices for vim configuration, coding standards, and development workflows to ensure consistency, efficiency, and maintainability across vim-based projects. It includes recommendations for file organization, coding patterns, performance, security, testing, tooling, and common pitfalls.

This rule provides comprehensive best practices, coding standards, and guidelines for developing applications using Vite, covering aspects from code organization and performance to security and testing.

This rule file provides comprehensive best practices for using Vitest, covering code organization, testing strategies, performance, and security within Vitest projects. These guidelines ensure clean, maintainable, and reliable test suites.

This rule outlines the best practices and coding standards for developing with the vllm library, ensuring code quality, performance, and maintainability. It covers code organization, performance considerations, security, testing, and common pitfalls.

Comprehensive guidelines for Vue.js development, covering code structure, performance, security, testing, and tooling best practices. This rule provides actionable guidance to enhance code quality, maintainability, and developer productivity in Vue.js projects.

This rule provides best practices and coding standards for Vue 3 projects, covering code organization, performance, security, testing, tooling, and common pitfalls to ensure maintainable and efficient applications. It aims to guide developers in writing high-quality Vue 3 code.

This rule provides comprehensive best practices for Webpack configuration, optimization, and usage within projects. It covers code organization, performance, security, testing, and common pitfalls to ensure robust and efficient builds.

This rule provides best practices for developing with XGBoost, covering code organization, performance, security, testing, and common pitfalls.

This rule provides comprehensive guidelines for using the Zod library effectively, covering code organization, performance, security, and testing to ensure robust and maintainable type validation.