Set up a comprehensive Cursor AI project with rules, context files, and coding conventions that maximize AI-assisted development productivity.
By The Prompt Black Magic Team
How to Use
Copy and customize this prompt for your project. Paste the output into your .cursorrules file or use it to configure Cursor AI for your codebase.
The Prompt
You are an expert developer who creates optimized Cursor AI project configurations.
Project: [PROJECT_NAME]
Stack: [e.g., React + TypeScript + Node.js + PostgreSQL]
Project stage: [NEW / EXISTING - describe current state]
Team size: [SOLO / SMALL TEAM / LARGE TEAM]
Create a complete Cursor AI configuration:
1. **.cursorrules file:** Project-specific rules including:
- Tech stack and version constraints
- Code style conventions (naming, formatting, patterns)
- Architecture rules (file organization, import patterns, state management)
- Testing requirements (what to test, which framework, coverage expectations)
- Common patterns to follow and anti-patterns to avoid
- Documentation standards
2. **Context files strategy:** Which files Cursor should always have access to:
- Key configuration files
- Type definitions and interfaces
- Database schema
- API route definitions
- Environment variable list
3. **Prompt templates** for common development tasks:
- New feature implementation
- Bug fix workflow
- Refactoring request
- Code review checklist
- Test writing
- Database migration
4. **Workflow tips:**
- How to use Cursor Composer for multi-file changes
- When to use inline edits vs. chat vs. composer
- How to provide good context for accurate completions
- Common pitfalls to avoid
Make the output copy-paste ready for a .cursorrules file.
Pro Tips for Coding
Ask the AI to include error handling and edge cases in generated code. Production code needs to handle failures gracefully.
Request code comments that explain the "why" not the "what" - future developers need reasoning, not obvious statement descriptions.
Include your existing code patterns and conventions in the prompt so generated code integrates seamlessly with your codebase.
When to Use This Prompt
Your pull request needs comprehensive unit tests and you want to generate test cases that cover edge conditions.
You are integrating a third-party API and need boilerplate code with proper error handling and retry logic.
You want to optimize a slow database query and need to understand the execution plan and indexing strategy.
Expected Results
Architecture diagrams described in text that map components, data flow, and integration points.
Refactoring plans that break monolithic code into modular, testable functions with clear interfaces.
Performance optimization recommendations backed by profiling strategies and complexity analysis.
How to Customize This Prompt
Include your database type and ORM so generated data layer code integrates with your existing persistence layer.
Modify the testing framework references to match what your project already uses: Jest, Pytest, RSpec, or others.
Swap the sample API endpoint with your real endpoint URL, authentication method, and expected payload format.