Project Rules

This rule set provides comprehensive guidance on best practices for using Poetry in Python projects, including dependency management, project structure, and coding standards. It covers various aspects such as code organization, performance considerations, security, testing, and tooling.

Comprehensive guidelines for Pony ORM best practices, covering code organization, patterns, performance, security, testing, common pitfalls, and tooling.

Enforces PostgreSQL coding standards, best practices, and performance optimization techniques to ensure maintainable, efficient, and secure database interactions. This rule covers code formatting, data integrity, security, and performance considerations.

This rule provides best practices for effectively using Postman for API testing, covering code organization, common patterns, performance, security, testing, and tooling to ensure robust and maintainable API tests.

Enforces Prisma best practices for schema design, data access, and application security. Provides guidelines for writing efficient, secure, and maintainable Prisma applications.

This rule file outlines best practices for Puppeteer, covering code organization, performance, security, testing, and common pitfalls. It aims to guide developers in building robust and maintainable Puppeteer applications.

Comprehensive best practices and coding standards for utilizing Pydantic effectively in Python projects, covering code organization, performance, security, and testing.

This rule provides comprehensive guidelines for pygame development, covering code organization, performance, security, testing, and common pitfalls. It aims to establish best practices and coding standards for building maintainable, efficient, and secure pygame applications.

This rule file provides comprehensive best practices for using Pylint to ensure high-quality, maintainable, and secure Python code. It covers code organization, common patterns, performance, security, testing, and tooling.

This rule file provides comprehensive guidelines for PyQt development, covering code organization, common patterns, performance, security, testing, and tooling. It aims to help developers create maintainable, efficient, and secure PyQt applications.

This rule provides comprehensive best practices for developing secure, maintainable, and performant applications using the Pyramid web framework for Python. It covers code structure, security, testing, and deployment considerations.

This rule provides comprehensive best practices for using pyright and BasedPyright in Python projects, covering code organization, patterns, performance, security, testing, common pitfalls, and tooling.

This rule enforces best practices and coding standards for developing applications with the PySide library. It covers code organization, performance, security, testing, and common pitfalls to ensure maintainable and robust applications.

This rule file outlines comprehensive best practices for using pytest in Python projects, covering code organization, testing strategies, performance optimization, security measures, and common pitfalls to avoid.

Comprehensive guidelines for Python development, covering code organization, performance, security, testing, and more. These rules promote maintainable, efficient, and secure Python codebases.

This rule provides comprehensive guidelines for PyTorch development, covering code organization, performance optimization, security, testing, and common pitfalls. It aims to ensure readable, maintainable, and efficient PyTorch code.

This rule provides comprehensive best practices for developing Qwik applications, covering code organization, performance, security, testing, and common pitfalls. It aims to guide developers in writing maintainable, efficient, and secure Qwik code.

This rule outlines the best practices and coding standards for developing and deploying applications on the Railway platform, covering aspects from code organization to security and performance.

This rule provides comprehensive best practices for developing React applications with Mobx, covering code organization, performance, testing, and security considerations. It aims to guide developers in building robust and maintainable applications using React-Mobx.

This rule provides comprehensive best practices and coding standards for React Native development, covering code organization, performance, security, testing, and common pitfalls.

This rule enforces best practices for using react-query in React applications, covering code organization, performance, security, and testing.

Enforces best practices for structuring and maintaining React-Redux applications, focusing on code organization, performance, and maintainability. This rule provides guidelines for developers to write efficient, scalable, and testable React-Redux code.

Comprehensive guide to React best practices, covering code organization, performance, security, testing, and common pitfalls. Adhering to these guidelines helps developers build maintainable, scalable, and high-performing React applications.

This rule provides best practices for working with Redis, covering code organization, performance, security, testing, and common pitfalls to ensure efficient and reliable usage. It applies to any language file interacting with Redis.

This rule provides comprehensive guidance on Redux best practices, covering code structure, performance optimization, testing strategies, and common pitfalls to ensure robust and maintainable Redux applications.

This rule file provides comprehensive best practices for Remix development, covering code organization, performance, security, testing, and more. It aims to guide developers in building maintainable, scalable, and secure Remix applications.

This rule file outlines best practices for using the Python requests library, covering performance, security, code organization, and testing.

Comprehensive best practices and coding standards for the Rich library, focusing on code quality, performance, and maintainability within Python terminal applications.

Enforces Riverpod library best practices for Flutter applications. This rule provides guidance on code organization, performance, testing, and common pitfalls when using Riverpod.

Comprehensive guidelines for developing robust and maintainable web applications with the Rocket web framework, covering code organization, security, performance, testing, and more.