Boost Your Coding Efficiency: 3 Documentation Tricks for CursorAI

Are you wasting time with AI coding assistance? If you’re using CursorAI, Windsurf, or VS Code, you might be facing a common frustration: AI doesn’t understand your project’s specific requirements, best practices, or file structure. This leads to incorrect code suggestions and inconsistent coding styles.

Here’s the reality: 90% of developers aren’t getting the most out of their AI coding tools. But there’s a solution that can reduce errors and hallucinations by over 90% while saving you significant time on prompting.

I’ll show you three powerful documentation tricks that will transform how you work with CursorAI. These methods will help you provide perfect context to your AI assistant every time, resulting in cleaner code and faster development.

The first method is surprisingly simple but incredibly powerful: using the @ key in CursorAI. Here’s how it works:

Adding Public Documentation

• In Cursor, type @docs to search for public documentation
• You can attach documentation from popular libraries like OpenAI or Beautiful Soup
• If you can’t find specific documentation, add a public website link

Web Integration

• Type @web to use the web search tool
• For existing projects, use @codebase to include all your files as context

This method works great for quick documentation needs, but it’s just the beginning. The real power comes from creating project-specific documentation, which we’ll explore in the next section.

Pro Tip: When working with public documentation, make sure to pick the most relevant sections for your project. You don’t need to include everything – focus on the parts that align with your current development needs.

The key to maximizing AI coding assistance lies in creating your own project documentation. While you can add this documentation at any point, it’s ideal to set it up before starting your project. One powerful feature available in CursorAI (and also in WindSurf and VS Code) is the ability to specify rule files.

Here’s how to set up custom rules in CursorAI:

Creating a New Rule File

• Press Command + Shift + P
• Select “New Cursor Rule”
• Choose a name for your rule (e.g., “frontend-rules” or “backend-rules”)

Defining Rule Scope

{ "description": "Frontend TypeScript rules", "pattern": "frontend/**/*.{ts,tsx}" } This example applies rules to all TypeScript files within the frontend folder and its subfolders.

Finding Rule Examples

• Visit cursor.directory for inspiration
• Search for framework-specific examples (like Next.js)
• Copy and modify rules to match your project needs

Example rule structure for Next.js frontend:

The beauty of rule files is that they’re applied automatically every time you make changes to matching files. You can create multiple rule files – for example, separate ones for frontend and backend code.

Pro Tip: Keep your rules specific and well-documented. It’s better to have multiple focused rule files than one massive configuration that’s hard to maintain.

The most powerful way to improve AI code suggestions is creating a dedicated documentation structure. Here’s how to build it:

Setting Up the Documentation Folder

• Create a new folder called documentation
• Start with a README.md as your documentation index
• Create separate markdown files for different aspects of your project

Essential Documentation Files

• Software requirements document
• Technical stack overview
• System architecture
• Frontend guidelines
• Backend structure
• File structure
• App flow
• Development setup
• Deployment guide
• Testing strategy
• API documentation
• System prompts
• Data processing guidelines

Remember, you don’t need to create all these documents at once. Start with the most crucial ones for your current development phase and add more as your project grows.

Using LLMs to Generate Documentation

One of the most efficient ways to create documentation is by leveraging Large Language Models. Here’s a powerful workflow:

Choosing Your LLM

In Cursor, use O3 mini for its high output limit (100,000 tokens). To access different models:

• Go to Cursor settings
• Navigate to the Models tab
• Activate/deactivate desired models

Creating Documentation with AI

Here’s a proven prompt template: Act as a senior software architect specialized in technical writing. Your task: Craft documentation for a software project. Follow technical writing style. Present output as markdown. Documentation structure: - Overview - Purpose - Detailed content - Related documents - References - Change log - Visual elements (Mermaid diagrams) Project details: [Add your project specifics here]

Adding Visual Elements

• Use Mermaid diagrams for flowcharts
• Test diagrams at mermaid.live before adding them
• AI can understand and generate these diagrams for cleaner code

Example Mermaid diagram:

Integrating Documentation with Cursor

The magic happens when you connect your documentation with your coding environment:

Adding Documentation Context

@documentation This simple command adds your entire documentation folder as context.

Using Enhanced Context

• Now you can make simple requests like “help me build user authentication”
• The AI will reference your documentation automatically
• Results will align with your project’s architecture and requirements

The third method involves Cursor’s notepad feature, which offers unique advantages for managing context:

Creating and Using Notepads

• Click the notepad tab
• Create a new notepad
• Add content and reference existing files

Key Features

• Similar to markdown files but with file referencing capabilities
• Can reference specific sections of your codebase
• Easy to add as context in chat window

Limitations

• Not easily version-controlled with Git
• Less suitable for team collaboration compared to documentation folders

Pro Tip: Use notepads for personal notes and quick references, but prefer the documentation folder method for team projects.

By implementing these three documentation methods – @ key integration, custom rules, and comprehensive documentation folders – you’ll see dramatic improvements in your AI-assisted coding:

• 90%+ reduction in AI coding errors
• Significantly faster development time
• More consistent code quality
• Better alignment with project requirements

Remember these key takeaways:

1. Start with public documentation using the @ key for quick wins
2. Create custom rules to enforce coding standards automatically
3. Build comprehensive project documentation for the best results
4. Use notepads for personal reference when needed

The secret to efficient AI coding isn’t just about having the right tools – it’s about giving them the right context. Keep your documentation simple, easy to maintain, and well-organized. The time you invest in documentation will pay off many times over through cleaner code and faster development cycles.

Download a free summary with the prompts here: Google Doc