16 Prompts for Cursor: AI-Assisted Development in Your IDE

The Developer's New Co-Pilot: Why Cursor Changes the Game

You've been coding for years. You know your IDE shortcuts, your linters, your debugger. But lately, you've seen colleagues move twice as fast. They're not just using autocomplete anymore—they're having conversations with their codebase. They're using Cursor, the AI-native IDE that's redefining how we write software.

Cursor isn't just another editor. It's a fork of VS Code that integrates AI directly into your workflow. Instead of jumping to a browser to ask ChatGPT, you can refactor a function, generate tests, or debug an error without leaving your editor. The key to unlocking this power? The right prompts.

This isn't a theoretical guide. These are 16 battle-tested prompts I use daily—for autocomplete, chat, and command mode. Each comes with a real example so you can copy-paste and adapt immediately.

How Cursor's AI Modes Work

Before diving into prompts, understand the three interaction modes:

Mode Trigger Best For
Autocomplete Just keep typing Inline suggestions, boilerplate, repetitive patterns
Chat Cmd+K (or Ctrl+K) Complex questions, debugging, explaining code
Command Cmd+Shift+K (or Ctrl+Shift+K) Multi-file edits, refactoring, generating code from scratch

Each mode expects a different prompt style. Autocomplete needs context. Chat needs a clear question. Command needs a precise description of the desired result.

Autocomplete Prompts: Speed Without Thought

Autocomplete works best when you provide enough context. Don't just type a variable name—write a comment or a partial function signature.

1. Generate a Function from a Comment

Prompt style: Write a descriptive comment above a function.

// Returns the average rating for a product from an array of reviews
function getAverageRating(reviews: Review[]): number {

Result: Cursor will generate the full function, including null checks and rounding.

2. Complete a Complex Type Definition

Prompt style: Define a partial type with clear field names.

interface Order {
  id: string;
  customer: Customer;
  items: OrderItem[];
status: 'pending'

| 'shipped' | 'delivered';
  createdAt: Date;
  // calculate total price including tax and shipping
  getTotal(): number;

Result: Cursor infers the calculation logic and adds proper typing.

3. Generate Boilerplate from a Test Framework Pattern

Prompt style: Write a test structure with a clear description.

describe('UserService', () => {
  describe('createUser', () => {
    // test that it returns a user with all fields
    // test that it throws on invalid email
    // test that it hashes the password

Result: Cursor generates three complete test cases with mocks and assertions.

4. Write a React Component from a Comment

Prompt style: Describe the component's purpose and props.

// A dropdown that filters a list of items by category
// Props: items, selectedCategory, onCategoryChange
const CategoryFilter: React.FC<CategoryFilterProps> = ({ items, selectedCategory, onCategoryChange }) => {

Result: Full component with state management, event handlers, and accessibility attributes.

Chat Prompts: Debugging and Understanding Code

Chat mode is your interactive debugger and code explainer. Ask specific questions.

5. Debug an Error with Full Context

Prompt: "I'm getting 'TypeError: Cannot read properties of undefined' in this function when the user object is incomplete. Can you add optional chaining and a fallback?"

Context: Paste the failing function.

Result: Cursor rewrites the function with ?. operators and default values.

6. Explain Legacy Code

Prompt: "Explain what this function does in simple terms, and identify any potential performance issues."

Context: Paste a 50-line function with complex loops.

Result: A breakdown of the algorithm, plus suggestions for memoization or early returns.

7. Refactor for Performance

Prompt: "This function filters an array of 10,000 items three times. Can you combine them into a single pass?"

Context: Show the three filter calls.

Result: A single reduce call that returns all three filtered arrays.

8. Convert Between Code Styles

Prompt: "Convert this class-based React component to a functional component with hooks."

Context: Paste a class component with componentDidMount, state, and lifecycle methods.

Result: A clean functional component with useState, useEffect, and proper cleanup.

Command Prompts: Multi-File Edits and Generation

Command mode is the most powerful. Use it when you need to create or modify multiple files.

9. Generate an Entire Module

Prompt: "Create a user authentication module with the following files: auth.service.ts (login, logout, refresh), auth.controller.ts (REST endpoints), auth.middleware.ts (JWT verification), and auth.test.ts (unit tests). Use Express and JWT. Include error handling."

Result: Four files with imports, exports, consistent error handling, and basic tests.

10. Add Logging to a Module

Prompt: "Add structured logging to all functions in this service. Use the existing logger instance. Log entry, exit, and any errors. Follow the pattern: logger.info({ event: 'functionName', data: { ... } })"

Context: Point to a file or module.

Result: Every function now has entry/exit logs with relevant context.

11. Write Database Migrations

Prompt: "Generate a Prisma migration for adding a 'subscriptionTier' column to the User model. The column should be an enum: 'free', 'pro', 'enterprise'. Default to 'free'. Generate both the schema change and the migration file."

Result: Updated Prisma schema and a migration SQL file.

12. Generate API Documentation

Prompt: "Generate OpenAPI 3.0 documentation for this Express router. Include request schemas, response schemas, and error codes."

Context: Point to a router file.

Result: A complete openapi.yaml file with all endpoints documented.

Advanced Prompts: Real-World Scenarios

These are longer, multi-step prompts that solve real problems I've faced.

13. Migrate from JavaScript to TypeScript

Prompt: "Convert this JavaScript module to TypeScript. Add proper types for all functions and objects. Create an interface for the main data structure. Add strict null checks."

Context: Paste a 200-line JS file.

Result: A .ts file with full type annotations, interfaces, and strict mode compliance.

14. Build a Custom Hook

Prompt: "Create a React hook called useDebounce that takes a value and a delay. Return the debounced value. Add a TypeScript generic so it works with any type. Include cleanup on unmount."

Context: None needed—prompt is self-contained.

Result: A reusable hook with proper TypeScript generics and cleanup.

15. Optimize a SQL Query

Prompt: "This query takes 3 seconds on a table with 500k rows. Analyze it and suggest optimizations: add indexes, rewrite joins, or break into subqueries."

Context: Paste the slow SQL query.

Result: An analysis with specific index suggestions and a rewritten query.

16. Generate a Data Migration Script

Prompt: "Write a one-time migration script that reads all users from the old 'profiles' table, transforms the 'preferences' JSON field from a flat structure to nested, and writes to the new 'users' table. Include error logging and a dry-run mode."

Context: Show the old and new table schemas.

Result: A script with dry-run flag, batch processing, and error handling.

Common Mistakes and How to Avoid Them

After months of daily use, here are the pitfalls I see most often:

Mistake Why It Fails Better Approach
Vague prompts AI has no context Include code, error messages, or file paths
Too many requests at once AI loses focus Break into single-file or single-task prompts
No constraints AI generates over-engineered code Specify patterns: 'Keep it simple', 'No external dependencies'
Ignoring output AI can hallucinate Always review generated code, especially security-critical parts

The Bottom Line

Cursor is not magic—it's a tool that amplifies your existing skills. The difference between a good result and a great one comes down to how you prompt. Start with the 16 prompts above, adapt them to your stack, and you'll find yourself writing code faster and debugging less.

One final tip: treat Cursor like a junior developer. Give clear instructions, provide context, and always review the output. With practice, you'll develop an intuition for what prompts work best for your specific codebase. The AI learns from your patterns—the more you use it, the better it gets.

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