Introduction
If you’re a developer using Cursor, you already know it’s more than just a code editor—it’s an AI-powered IDE that integrates autocomplete, chat, and command modes directly into your workflow. But even the best tool is only as good as the instructions you give it. That’s where prompts come in: the right prompt can turn a generic AI suggestion into a precise, context-aware solution that saves you hours of debugging or refactoring.
This guide collects 10 ready-to-use prompts for Cursor, categorized by the three main interaction modes: autocomplete, chat, and command. Each prompt is copy-paste ready, includes a real-world example, and shows the expected output. Whether you’re a solo developer or part of a team, these prompts will help you extract maximum value from Cursor’s AI capabilities.
1. Autocomplete: Generate a Complete Function from Comments
Use case: You have a clear idea of what a function should do, but you want Cursor to write the implementation, including edge cases and error handling.
Prompt (as a comment before the function):
// Function to validate an email address.
// Returns an object { isValid: boolean, reason: string }.
// Checks format, domain existence (via DNS lookup stub), and length.
Example: Place the comment above an empty function body in a JavaScript file:
function validateEmail(email) {
// Cursor autocomplete will fill this in
}
Expected output from Cursor autocomplete:
function validateEmail(email) {
if (typeof email !== 'string') {
return { isValid: false, reason: 'Email must be a string' };
}
if (email.length > 254) {
return { isValid: false, reason: 'Email too long' };
}
const emailRegex = /^[^\s@]+@[^\s@]+\.[^\s@]+$/;
if (!emailRegex.test(email)) {
return { isValid: false, reason: 'Invalid email format' };
}
// Stub for DNS check
return { isValid: true, reason: '' };
}
Why it works: Cursor’s autocomplete uses the surrounding context (comments, function name, parameters) to infer the desired logic. Adding explicit requirements in comments reduces guesswork.
2. Autocomplete: Refine an Existing Loop for Performance
Use case: You have a working but slow loop, and you want Cursor to suggest optimizations without rewriting the entire file.
Prompt (as a comment near the loop):
// Optimize this loop: reduce time complexity, avoid duplicate lookups.
Example: Given a loop that filters an array of users:
const activeUsers = [];
for (let i = 0; i < users.length; i++) {
if (users[i].status === 'active' && users[i].lastLogin > Date.now() - 86400000) {
activeUsers.push(users[i]);
}
}
Place the comment right before the loop. Cursor will suggest:
const now = Date.now();
const activeUsers = users.filter(u => u.status === 'active' && u.lastLogin > now - 86400000);
Why it works: Cursor identifies patterns and suggests idiomatic, performant alternatives. The comment signals the intent to optimize.
3. Chat: Explain a Code Snippet in Detail
Use case: You inherited a complex piece of code and need a line-by-line explanation, including why certain patterns are used.
Prompt in Chat:
Explain the following code snippet in detail, focusing on the design pattern and potential pitfalls:
<paste code here>
Example: Paste a snippet using a builder pattern for HTTP requests. Cursor’s chat response will break down each method, explain the builder pattern, and highlight thread-safety concerns.
Why it works: Chat mode has a larger context window and can provide structured explanations. The explicit request for “design pattern” and “pitfalls” forces deeper analysis.
4. Chat: Generate Unit Tests for a Function
Use case: You need comprehensive unit tests covering normal cases, edge cases, and error conditions.
Prompt in Chat:
Generate unit tests for the following function using Jest. Include tests for:
- Normal input
- Empty input
- Invalid input (null, undefined, non-string)
- Performance (timeout if function takes > 100ms)
Function:
<function code>
Example: For a parseCSV function, Cursor will output a test file with describe blocks and it statements, including mock data and assertions.
Why it works: The prompt specifies the testing framework (Jest) and the categories of tests, which reduces ambiguity.
5. Chat: Refactor Code with Specific Requirements
Use case: You want to refactor a monolithic function into smaller, testable functions, but you have constraints (e.g., no external dependencies, keep the same public API).
Prompt in Chat:
Refactor this function into smaller, pure functions. Keep the same public API (same parameters and return type). Do not use any external libraries. Explain each new function’s purpose.
<function code>
Example: A 100-line function that processes orders gets broken into validateOrder, applyDiscount, and calculateShipping. Cursor will show the refactored code and a short explanation for each function.
Why it works: By specifying constraints (no libraries, same API), you avoid hallucinations and get a solution that fits your project.
6. Chat: Debug an Error Message
Use case: You have an unhandled error and need help understanding its root cause and fix.
Prompt in Chat:
I’m getting this error: "TypeError: Cannot read properties of undefined (reading 'id')"
Here is the relevant code:
<code snippet>
What is the most likely cause and how do I fix it? Suggest 2-3 solutions, ordered by simplicity.
Example: The error occurs in a React component when trying to access props.user.id before user is loaded. Cursor will suggest: 1) optional chaining (props.user?.id), 2) conditional rendering, 3) default state.
Why it works: Providing the exact error message and code snippet lets Cursor match the error pattern to known solutions.
7. Command: Batch Rename Variables in a File
Use case: You need to rename a variable across multiple files without using find-and-replace, to avoid renaming similar words.
Command in Command Mode:
Rename all occurrences of 'oldVarName' to 'newVarName' in the current file, but only when it is used as a variable (not inside string literals or comments).
Example: In a 500-line file, Cursor will apply the rename with semantic awareness, leaving strings like "oldVarName is deprecated" untouched.
Why it works: Command mode supports natural language instructions and can perform semantic operations that simple regex cannot.
8. Command: Extract a Method from a Block of Code
Use case: You have a block of code inside a large function that you want to move to its own method for readability.
Command:
Extract lines 45-70 into a new private method called 'calculateTotal'. Replace the original block with a call to this method. Keep the same logic.
Example: In a Java file, Cursor will create:
private double calculateTotal(List<Item> items) {
// extracted logic
}
and replace the original block with double total = calculateTotal(items);
Why it works: Command mode can operate on specific line ranges and understands programming constructs like method signatures.
9. Autocomplete: Generate JSDoc Comments
Use case: You want to document a function with JSDoc, including parameter types, return type, and a description.
Prompt (as a comment above function):
// Generate JSDoc for this function
Example: Place the comment above:
function fetchData(url, options = {}) {
// implementation
}
Cursor will add:
/**
* Fetches data from the given URL.
* @param {string} url - The endpoint to fetch from.
* @param {Object} [options] - Optional fetch options.
* @param {string} [options.method='GET'] - HTTP method.
* @returns {Promise<Object>} Parsed JSON response.
*/
Why it works: Autocomplete reads the function signature and body to infer documentation. The comment signals the desired output format.
10. Chat: Generate a Regex Pattern from Description
Use case: You need a regex to parse or validate a specific format, but you don’t want to write it manually.
Prompt in Chat:
Create a regex pattern that matches:
- A date in format YYYY-MM-DD
- Must be a valid calendar date (leap years considered)
- Must not match dates before 1900
- Return the pattern and a short explanation of each part.
Example: Cursor will output:
^(19[0-9]{2}
|2[0-9]{3})-(0[1-9]|1[0-2])-(0[1-9]|[12][0-9]|3[01])$
with an explanation that the first group handles years 1900–2999, the second group months 01–12, and the third group days 01–31.
Why it works: The prompt explicitly states constraints (valid date, leap years, minimum year), which Cursor uses to craft a more accurate pattern.
Conclusion
Cursor’s AI modes—autocomplete, chat, and command—each excel at different tasks. Autocomplete is best for inline code generation and small refactorings; chat is ideal for explanations, debugging, and complex questions; command mode shines for file-wide operations and refactoring. By using specific prompts like the ones above, you can turn Cursor from a simple autocomplete tool into a full-fledged pair programmer.
Start by trying one prompt from each category today. For example, use the autocomplete prompt to generate a function, then chat to explain a legacy code snippet, then command to rename a variable. Over time, you’ll develop your own library of prompts that match your personal workflow.
What’s your favorite Cursor trick? Share it in the comments below—we’d love to hear how you’re using AI-assisted development in your IDE.
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