Cursor Rules Rule 🚀

⚠️ Important: If you're using Cursor without rules, you're doing it wrong!

⚠️ Important Part 2: Every major update seems to slightly change how the rules work and how they need to be applied. I'm currently working on a more generalizable solution to the problem and also exploring ways to port all ideas to GitHub Copilot and Windsurf.

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This repository contains a collection of custom rules for the Cursor AI coding assistant that significantly enhance its capabilities. These rules provide structure, automation, and consistency to your AI-assisted coding workflow.

The Future of Development is Here 🌟

AI is transforming software development, and Cursor represents a significant leap forward in this evolution. This repository showcases a fundamental paradigm shift in how we build software:

From: Developers manually writing every line of code
To: Developers creating rules and specifications that guide AI assistants to generate implementation

This approach fundamentally changes the developer's role from manual coding to:

1. Defining clear specifications for what should be built
2. Establishing technical rules for how code should be written
3. Supervising the AI as it implements solutions
4. Reviewing and refining the output

Cursor, with properly configured rules, is the first practical implementation of this new development model. The rules in this repository aren't just for code formatting or style, they establish a complete development workflow that manages everything from specifications to tasks, knowledge capture, and code commits.

By adopting this rules-based approach, developers can dramatically accelerate productivity while still maintaining control.

And the best part?

You can already begin this journey with Cursor today!

What are Cursor Rules? 🤔

Cursor rules (in .mdc format) are instructions that guide how the AI assistant behaves, processes information, and generates code. They act as a "stdlib" or framework for the AI, ensuring that it follows best practices, coding standards, and project-specific requirements.

Rules allow you to:

• Automate repetitive tasks 🔄
• Enforce coding standards 📏
• Implement workflows that boost productivity 🚀
• Create specifications that drive implementation 📜
• Maintain consistency across your codebase 🔍

Rules in this Repository 📚

On-Load Rule

on-load-rule.mdc: Establishes critical development principles that must be followed for all development activities.

• Enforces "specifications first" principle - no implementation without specs
• Ensures proper task tracking for all development activities
• Mandates quality assurance with tests for all implementations
• Requires knowledge capture of important learnings
• Acts as the foundation for all other rules in the system

Specification Management Rule

specification-management-rule.mdc: Comprehensive system for creating, validating, and tracking requirements.

• Automatically creates specifications when implementation is requested
• Provides structured format for requirements with clear acceptance criteria
• Includes validation mechanisms to ensure specification quality
• Tracks specification completion status throughout development
• Maintains a complete index of all project specifications

Development Workflow Rule

development-workflow-rule.mdc: Comprehensive development lifecycle system for task tracking, testing, and version control.

• Creates and manages tasks with unique IDs and structured metadata
• Maintains a central task index with status tracking
• Integrates testing frameworks appropriate to the project type
• Handles version control with conventional commit formatting
• Ensures quality assurance through automated testing
• Prevents completion of tasks that don't pass testing
• Automatically validates and updates README to keep documentation in sync with code

Knowledge Management Rule

knowledge-management-rule.mdc: System for capturing, organizing, and applying project knowledge.

• Documents important learnings during implementation
• Organizes and categorizes knowledge for easy retrieval
• Processes and indexes documentation provided by users
• Refines knowledge to extract patterns and insights
• Applies captured knowledge to new development tasks
• Creates cross-references between related information assets

Project Onboarding Rule

project-onboarding-rule.mdc: Automatically analyzes and onboards existing projects into the AI-driven workflow.

• Creates the required directory structure for AI-driven development
• Analyzes existing codebase structure and components
• Discovers and catalogs existing documentation
• Extracts specifications from existing code
• Sets up initial knowledge base and task tracking
• Provides integration options from full onboarding to basic setup

Command Rules

command-rules.mdc: Defines custom commands for AI-assisted development workflows.

• Provides specialized commands for specifications, code, tasks, and more
• Generates visual dashboards of specifications
• Performs code analysis and refactoring recommendations
• Creates project evaluation and progress reports
• Generates detailed code reviews and PR templates
• Produces comprehensive task summaries

Visualization Rule

visualization-rule.mdc: Creates visual representations of project elements.

• Generates specification dependency diagrams and progress visualizations
• Creates task timelines and status visualizations
• Produces knowledge maps and category charts
• Generates system architecture diagrams
• Automatically includes visualizations in reports

Location Rule

location-rule.mdc: Defines standards for organizing rule files in the repository.

• Establishes consistent locations for rule files
• Ensures proper organization of generated files
• Facilitates discovery and maintenance of rules

Critical Development Principles ⚙️

All development with these rules fol