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How to review Cursor-generated code

Cursor generates code fast but reviewing it thoroughly is essential before committing. This tutorial shows a structured PR review workflow using Cursor's built-in diff view, git integration, and @git context to review AI-generated changes efficiently. You will learn what to check, how to spot common AI mistakes, and how to use Cursor itself to review its own output.

What you'll learn

  • How to use Cursor's diff view to review AI-generated changes
  • What to check in AI-generated code before committing
  • How to use @git context to review changes
  • How to create a pre-commit review checklist
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Beginner6 min read10-15 minCursor Free+, Git-based projectsMarch 2026RapidDev Engineering Team
TL;DR

Cursor generates code fast but reviewing it thoroughly is essential before committing. This tutorial shows a structured PR review workflow using Cursor's built-in diff view, git integration, and @git context to review AI-generated changes efficiently. You will learn what to check, how to spot common AI mistakes, and how to use Cursor itself to review its own output.

Reviewing Cursor-generated code before committing

AI-generated code passes casual review easily but often contains subtle issues: hallucinated imports, incomplete error handling, security vulnerabilities, and logic bugs. This tutorial establishes a review workflow that catches these issues before they reach your codebase.

Prerequisites

  • Cursor installed with Git initialized
  • Code generated by Cursor that needs review
  • Familiarity with git diff and Cursor's diff view

Step-by-step guide

1

Review the diff before accepting

After Cursor generates code in Composer or Cmd+K, always review the diff before clicking Accept. Look for red lines (deletions) that should not have been removed and green lines (additions) that introduce unexpected patterns.

Cursor diff review
1// In Cursor's diff view, check for:
2// 1. RED LINES: Code that was deleted but should not have been
3// - Existing error handling removed
4// - Comments or documentation stripped
5// - Working code replaced entirely
6// 2. GREEN LINES: New code that looks suspicious
7// - Hardcoded values (URLs, credentials, magic numbers)
8// - Missing error handling (no try/catch on async)
9// - Imports from packages not in your package.json
10// - console.log statements left in production code

Expected result: A mental checklist for quickly scanning AI-generated diffs.

2

Use @git to review all changes at once

After accepting multiple Cursor changes, use @git in Chat to get a summary of everything that changed. This catches issues across multiple files that single-file diffs might miss.

Cursor Chat prompt
1// Cursor Chat prompt (Cmd+L, Ask mode):
2// @git Review all uncommitted changes. For each modified
3// file, check for:
4// 1. Missing error handling
5// 2. Hardcoded values that should use config
6// 3. Imports that reference non-existent modules
7// 4. Security issues (SQL injection, XSS, exposed secrets)
8// 5. Functions without return types
9// 6. Dead code or unused imports
10// Report issues by file with severity (High/Medium/Low).

Expected result: A structured review of all AI-generated changes with categorized issues.

3

Create a pre-commit review checklist

Store a review checklist as a Cursor Notepad or custom command that you run before every commit. This standardizes the review process.

.cursor/rules/review-checklist.mdc
1---
2description: Pre-commit review checklist
3globs: ""
4alwaysApply: false
5---
6
7## Pre-Commit Review Checklist for AI Code
8Before committing, verify:
9
10### Correctness
11- [ ] All imports resolve to existing modules
12- [ ] Return types match the function contract
13- [ ] Edge cases handled (null, empty array, zero)
14- [ ] Async functions have try/catch or .catch()
15
16### Security
17- [ ] No hardcoded secrets, URLs, or API keys
18- [ ] SQL queries use parameterized statements
19- [ ] User input is validated/sanitized
20- [ ] No eval() or innerHTML with user data
21
22### Quality
23- [ ] No console.log in production code
24- [ ] No unused variables or imports
25- [ ] Function names match their behavior
26- [ ] Comments are accurate (not stale)

Expected result: A reusable checklist that standardizes code review for AI-generated output.

4

Use BugBot for automated review

If you have Cursor Pro+, enable BugBot to automatically scan changes on feature branches. BugBot compares against main and flags potential bugs with confidence ratings.

BugBot workflow
1// BugBot automatically reviews when you push to a branch.
2// To manually trigger a review in Cursor:
3// 1. Commit your changes to a feature branch
4// 2. Push to remote: git push origin feature-branch
5// 3. BugBot scans the diff against main
6// 4. Issues appear with confidence ratings
7// 5. Click 'Fix in Cursor' for one-click fixes
8//
9// BugBot Autofix has a 35%+ merge rate — it can
10// fix many issues automatically.

Expected result: Automated AI review catching issues before human PR review.

5

Do a final manual sanity check

After automated checks, do a quick manual review of the actual behavior. Run the code, check the UI, test the API endpoint. AI-generated code can be syntactically perfect but logically wrong.

Terminal
1// Quick sanity checks:
2// 1. Does the code compile? npx tsc --noEmit
3// 2. Do tests pass? npm test
4// 3. Does it work in the browser/API?
5// 4. Does the git diff look reasonable for the task?
6// (small task = small diff, big diff = suspicious)
7
8// If the diff is unexpectedly large:
9// Cursor Chat: @git Why are there changes in 15 files
10// when I only asked to update the UserProfile component?
11// List all files that changed and explain each change.

Expected result: Code compiles, tests pass, and the actual behavior matches the intended change.

Complete working example

.cursor/commands/review.md
1---
2description: Review all AI-generated changes before commit
3---
4
5Review all uncommitted changes in this project:
6
71. List every modified and new file
82. For each file, check:
9 - All imports resolve to existing modules in package.json or src/
10 - All async functions have error handling
11 - No hardcoded secrets, URLs, or credentials
12 - No console.log statements in production code
13 - All functions have explicit TypeScript return types
14 - No unused variables or dead code
153. Check for cross-file issues:
16 - Circular imports between modified files
17 - Inconsistent naming between related files
18 - Missing exports that other files depend on
194. Rate each issue as High/Medium/Low severity
205. Provide a one-line summary: PASS or NEEDS FIXES
21
22Use @git for the diff context.

Common mistakes when reviewing Cursor-generated code

Why it's a problem: Accepting Cursor changes without reviewing the diff

How to avoid: Always review the diff in Cursor's panel before clicking Accept. Check red lines (deletions) first.

Why it's a problem: Only reviewing the files you asked Cursor to change

How to avoid: Use @git to review ALL uncommitted changes, not just the files you expected to change.

Why it's a problem: Trusting that AI-generated code compiles equals correct

How to avoid: Run tests and manually verify behavior after every Cursor session before committing.

Best practices

  • Review every diff before accepting Cursor changes
  • Use @git context to review all changes across files
  • Check for deletions first (red lines) as they often indicate unintended removals
  • Run the TypeScript compiler and test suite before committing
  • Create a /review custom command for standardized AI code review
  • Enable BugBot for automated review on feature branches
  • Keep commits small and review after each Cursor task, not after multiple tasks

Still stuck?

Copy one of these prompts to get a personalized, step-by-step explanation.

ChatGPT Prompt

Create a code review checklist specifically for AI-generated code. Include checks for: hallucinated imports, missing error handling, hardcoded secrets, unused variables, incorrect types, security vulnerabilities (SQL injection, XSS), and logic errors. Format as a markdown checklist.

Cursor Prompt

In Cursor Chat (Cmd+L): @git Review all uncommitted changes. Check for: missing error handling, hardcoded values, hallucinated imports, security issues, and unused code. Rate each issue High/Medium/Low. Provide a PASS/NEEDS FIXES verdict.

Frequently asked questions

How long should I spend reviewing AI-generated code?

At minimum 30 seconds per file for a diff scan. For security-sensitive code (auth, payments, data access), spend 2-5 minutes per file. The review time should be proportional to the risk.

Can Cursor review its own code?

Yes. Using @git in Ask mode to review changes works surprisingly well. Cursor catches issues like missing error handling and hallucinated imports in its own output.

Should I review AI code differently than human code?

Yes. AI code is more likely to have: hallucinated imports, removed existing logic, hardcoded values, and missing edge case handling. Focus your review on these patterns.

What percentage of AI-generated code needs changes?

In practice, about 20-30% of Cursor-generated code needs minor adjustments. Major issues occur in roughly 5-10% of generations. The review workflow catches both.

Is there a way to automate the review?

BugBot provides automated review on branches. You can also create a .cursor/commands/review.md custom command that runs a standardized review prompt with one slash command.

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