AI Code Reviewer

How to Use AI Code Reviewer

When to Use AI Code Reviewer

AI Code Reviewer Examples

function login(user, pass) { return db.query('SELECT * FROM users WHERE name=' + user); }

🚨 SQL injection vulnerability. User input concatenated directly into query. Use parameterized queries instead — db.query('SELECT * FROM users WHERE name=?', [user])

for (let user of users) { const score = users.filter(u => u.id === user.id).length; }

⚠️ O(n²) complexity. Filtering inside the loop runs through the entire array on every iteration. Build a lookup map first — const map = new Map(users.map(u => [u.id, u])); — then look up by ID in constant time.

function getUserName(u) { if (u && u.name) { return u.name; } else { return 'Unknown'; } }

💡 Simplify with optional chaining and nullish coalescing — return u?.name ?? 'Unknown';

Tips & Best Practices for AI Code Reviewer

• 1.Treat AI review as a supplement to human review, not a replacement. The model misses architectural problems and anything that depends on business context, which is exactly what experienced reviewers catch.
• 2.Read the suggestions critically. The model occasionally proposes changes that break tests or don't apply to your codebase — accept what's correct, ignore what isn't.
• 3.For security-critical code, run dedicated scanners like Snyk or Semgrep alongside AI review. The model catches many issues but misses some that purpose-built tools handle reliably.
• 4.Give the model context in your prompt. Style guides, framework conventions, and the target environment all change what 'good' looks like, and the more you describe, the more useful the review.
• 5.Don't paste secrets. API keys, passwords, internal URLs in code being reviewed are a potential leak — sanitize before you submit.
• 6.For a tighter feedback loop, use an IDE plugin like Cursor, GitHub Copilot, or Gemini Code Assist instead of copy-pasting into a web tool. Inline suggestions are dramatically faster to act on.

Frequently Asked Questions