By Pindi Sahota · Last updated: 2026-06-07

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How to Use Claude for Code Reviews (2026 Guide)

Last updated: 2026-06-07

Claude code reviews are one of the highest-value uses of AI in the development workflow. Unlike a linter — which checks syntax and style — Claude understands the intent behind code, reads across multiple functions, and catches the bugs that automated tools miss: subtle logic errors, missing auth checks, N+1 query patterns, race conditions, and incorrect assumptions about input. Claude code reviews are also direct and unsparing in a way that human reviewers sometimes are not — Claude has no concern about the social dynamics of telling you your approach is wrong. This guide gives you the exact prompt template, the review categories Claude covers best, before/after examples, and how to integrate Claude into your pull request workflow.

Why Claude Code Reviews Are Different from Linting

Linters catch what they are programmed to catch: unused variables, incorrect types, style violations, known anti-patterns. Claude catches what a senior engineer catches: the logic error that is syntactically correct, the security assumption that is subtly wrong, the function whose name says one thing and does another, the test that asserts the wrong thing.

A linter will not tell you that your password reset function has a timing attack vulnerability. A linter will not notice that the new feature bypasses the authorisation check that protects every other route. Claude will.

This does not make linters obsolete — run both. Use linting for the mechanical checks and Claude for the judgement-based review.

The Code Review Prompt Template

This template reliably produces thorough, actionable reviews. Copy and adapt it:

` Please review the following [language] code.

Context: [What this code does and why it was written] Stack: [Language version, framework, relevant libraries] Change type: [New feature / Bug fix / Refactor / Performance improvement]

Focus on:

Security vulnerabilities (be specific about attack vectors)
Logic errors and edge cases the code doesn't handle
Performance issues
Error handling completeness
Code readability and naming
Anything that doesn't match standard [language] best practices

Be direct and specific. For each issue, include:

What the problem is
Why it matters (severity: high/medium/low)
How to fix it (show corrected code where helpful)

[PASTE CODE HERE] `

How to Review Code with Claude — Step by Step

Step 1: Choose Your Review Mode

Browser (Claude.ai): Best for quick reviews of single functions or small files. Paste the code, add context, ask for a review.

Claude Code (CLI): Best for PR reviews involving multiple files or where Claude needs to understand the broader codebase. Launch Claude Code in your project and give a file path or git diff.

Step 2: Provide Context Before the Code

Context transforms a generic review into a targeted one. The minimum useful context:

` This is a password reset endpoint in a FastAPI app. Users submit their email, we generate a time-limited token, save its hash to the database, and email them a link. The link confirms the token and allows password reset. Review for security issues first, then everything else. `

Step 3: Specify the Review Depth

Different situations call for different levels of depth:

Quick scan: "Flag anything critical — security issues, obvious bugs."
Full review: "Thorough review — cover security, performance, style, error handling, and edge cases."
Focused review: "Review specifically for SQL injection and authentication bypass vulnerabilities."
Convention check: "Review against the conventions in CLAUDE.md — flag anything inconsistent."

Step 4: Use Claude Code for PR Reviews

In Claude Code, you can review a git diff without copy-pasting:

`bash claude

Review the changes in the current git diff (HEAD vs main).

Focus on: security, correctness, and consistency with our CLAUDE.md conventions. Rate severity of each issue and suggest specific fixes. `

Or review a specific file that was recently changed:

`bash

Review src/routers/payments.py for security issues.

This handles Stripe webhook verification and payment recording. Be thorough. `

Step 5: Act on the Review

The most productive review workflow:

Get Claude's review
Go through each high-severity issue immediately
Ask Claude to write the fix for issues you agree with: "Fix the timing attack vulnerability you identified in the token comparison"
Add medium/low issues to your backlog
Run your test suite after applying fixes
Optional: paste the fixed code back to Claude for a follow-up pass

What Claude Checks in Code Reviews

Security Issues (Claude's Strongest Category)

Claude checks for the OWASP Top 10 and common application-layer vulnerabilities:

SQL injection — string interpolation into queries, missing parameterisation
Authentication bypass — missing auth checks, broken token validation
Timing attacks — using == for secrets instead of hmac.compare_digest
Exposed secrets — hardcoded API keys, tokens in logs
IDOR — endpoints that return data without verifying the resource belongs to the requesting user
Mass assignment — blindly accepting user input and saving it to the database
Insecure deserialization — pickle.loads on user-controlled data
XSS — unsanitised user content rendered as HTML

Performance Issues

N+1 queries — running a database query inside a loop
Missing indexes — filtering or ordering by an un-indexed column
Inefficient data loading — loading entire records when only a field is needed
Missing caching — repeated identical expensive operations
Blocking async operations — calling synchronous code in async context

Logic and Correctness

Wrong conditions — < when <= is needed, OR when AND is needed
Missing edge cases — empty input, zero, None, negative numbers
Incorrect algorithm — an approach that works for common cases but fails subtly
State mutation bugs — modifying shared state, mutable defaults

Before and After: Code Review Example

Before (Submitted for Review)

`python import hashlib import random import string from datetime import datetime, timedelta from db import getdb from emailservice import sendresetemail

def requestpasswordreset(email: str): db = get_db() user = db.execute(f"SELECT * FROM users WHERE email = '{email}'").fetchone() if not user: return {"error": "User not found"}

token = ''.join(random.choices(string.ascii_letters + string.digits, k=32)) expiry = datetime.now() + timedelta(hours=1)

db.execute(f"INSERT INTO passwordresets (userid, token, expiry) VALUES ({user['id']}, '{token}', '{expiry}')") db.commit()

sendresetemail(email, token) return {"message": "Reset email sent"}

def confirmpasswordreset(token: str, newpassword: str): db = getdb() reset = db.execute(f"SELECT * FROM password_resets WHERE token = '{token}'").fetchone() if not reset or reset['expiry'] < datetime.now(): return {"error": "Invalid or expired token"}

hashed = hashlib.md5(newpassword.encode()).hexdigest() db.execute(f"UPDATE users SET password = '{hashed}' WHERE id = {reset['userid']}") db.execute(f"DELETE FROM password_resets WHERE token = '{token}'") db.commit() return {"message": "Password updated"} `

Claude's Review

` HIGH SEVERITY — Security Issues:

SQL Injection (Critical) — Lines 9, 22, 26, 29, 30

Both functions use f-strings to interpolate user input directly into SQL queries. An attacker can submit email=' OR '1'='1 to extract all users, or use UNION SELECT attacks. Every query must use parameterised statements.

Weak randomness (High) — Line 14

random.choices() uses Python's Mersenne Twister which is not cryptographically secure. A determined attacker can predict future tokens if they can observe previous ones. Use secrets.token_urlsafe(32) instead.

Insecure password hashing (Critical) — Line 25

MD5 is a fast hashing algorithm explicitly unsuitable for passwords. A modern GPU can crack MD5 hashes at billions per second. Use bcrypt, argon2, or at minimum PBKDF2 with SHA-256 and 100,000+ iterations.

Token not hashed in database (High) — Line 17

Storing the raw reset token in the database means a database breach exposes valid reset tokens directly. Store hash(token) in the database and compare hash(submitted_token) against it during confirmation.

Information disclosure (Medium) — Line 10

Returning "User not found" for an unknown email allows email enumeration. Return the same success message whether or not the email exists.

MEDIUM SEVERITY:

No rate limiting — an attacker can request thousands of reset emails

for valid addresses (spam) or enumerate valid emails quickly.

Old tokens not invalidated — if a user requests multiple resets,

old tokens remain valid. DELETE old tokens for the user_id before inserting a new one.

LOW SEVERITY:

datetime.now() vs datetime.utcnow() — use UTC consistently to avoid

timezone-related expiry bugs in production. `

After (Claude-Fixed Code)

`python import hashlib import secrets from datetime import datetime, timezone, timedelta from db import getdb from emailservice import sendresetemail from passlib.context import CryptContext

pwd_context = CryptContext(schemes=["argon2"], deprecated="auto")

def requestpasswordreset(email: str) -> dict: db = get_db() user = db.execute( "SELECT id FROM users WHERE email = ?", (email,) ).fetchone()

# Always return same message to prevent email enumeration if not user: return {"message": "If that email is registered, a reset link has been sent."}

token = secrets.tokenurlsafe(32) tokenhash = hashlib.sha256(token.encode()).hexdigest() expiry = datetime.now(timezone.utc) + timedelta(hours=1)

# Invalidate any existing tokens for this user db.execute("DELETE FROM passwordresets WHERE userid = ?", (user["id"],)) db.execute( "INSERT INTO passwordresets (userid, tokenhash, expiry) VALUES (?, ?, ?)", (user["id"], tokenhash, expiry), ) db.commit()

sendresetemail(email, token) # Send raw token in email, store only hash return {"message": "If that email is registered, a reset link has been sent."}

def confirmpasswordreset(token: str, newpassword: str) -> dict: db = getdb() tokenhash = hashlib.sha256(token.encode()).hexdigest() reset = db.execute( "SELECT * FROM passwordresets WHERE tokenhash = ?", (tokenhash,) ).fetchone()

if not reset: return {"error": "Invalid or expired token"} if reset["expiry"] < datetime.now(timezone.utc): db.execute("DELETE FROM passwordresets WHERE tokenhash = ?", (token_hash,)) db.commit() return {"error": "Invalid or expired token"}

hashedpassword = pwdcontext.hash(newpassword) db.execute( "UPDATE users SET password = ? WHERE id = ?", (hashedpassword, reset["userid"]), ) db.execute("DELETE FROM passwordresets WHERE tokenhash = ?", (tokenhash,)) db.commit() return {"message": "Password updated successfully"} `

Integrating Claude into Your PR Workflow

Pre-review self-check: Before requesting human review, run Claude over your own diff. Fix the obvious issues Claude catches before your colleague has to. This makes human review sessions more productive — reviewers focus on architecture and intent rather than basic bugs.

Automated review on PR open: Some teams pipe the git diff to Claude via the API and post the response as a PR comment automatically. This provides consistent first-pass review on every PR.

Convention enforcement: Add your coding conventions to CLAUDE.md and ask Claude to flag anything that violates them. This is more thorough than a linter for convention checks that cannot be expressed as static rules.

Security-focused passes: For authentication, payment, or data-handling code, run a dedicated security-focused review separate from the general code review: "Review this code specifically for security vulnerabilities. Be exhaustive."