To use Claude for code review, paste your code or diff into Claude.ai or run Claude Code from your terminal, then ask it to review for bugs, style, and security. For ongoing work, connect the Claude GitHub Action to your repo so every pull request gets an automatic review. Treat Claude like a junior engineer who never sleeps, give it clear instructions, and always verify the suggestions before merging.

That short version is the whole game. The rest of this article is the practical setup, the prompts that actually work, and the mistakes that turn a helpful reviewer into a noisy one.

What “using Claude for code review” actually means

There are three common ways teams run Claude over their code, and each one fits a different part of your workflow.

The first is Claude.ai in your browser. You copy a function, a diff, or a whole file into the chat box and ask for a review. This is the fastest way to get a second opinion on a tricky block of code, and it costs nothing extra if you already have a paid plan.

The second is Claude Code, the terminal-based agent from Anthropic. You run it inside a project folder, point it at the files you care about, and it reads the surrounding code for context before responding. This is the right tool when the change is spread across multiple files or you want Claude to spot patterns across the codebase.

The third is the Claude GitHub Action. You install it as a workflow in your repo, and it comments on pull requests automatically. Every time someone opens a PR, Claude reads the diff, reviews it against your instructions, and posts inline comments where it sees issues.

Most teams end up using all three. The browser version for ad hoc questions, Claude Code for deeper local reviews, and the GitHub Action as the always-on safety net on every pull request.

Why code review with Claude matters for your business

Human code review is one of the most expensive bottlenecks in software delivery. Senior engineers spend a meaningful slice of their week reading other people’s diffs, and small teams often skip review entirely because nobody has the time.

Claude changes the trade-off. A review bot can scan every pull request in seconds, catch the obvious issues, and leave the human reviewer to focus on architecture, business logic, and the calls only a domain expert can make. That shift is the difference between shipping twice a week and shipping twice a day, especially for small teams where the founder is also the lead reviewer.

There is also a quality floor that comes with a consistent reviewer. Junior developers learn faster when every PR gets specific, written feedback. Onboarding gets shorter. Standards stop drifting between repos. None of this replaces a strong senior engineer, but it removes the boring, repetitive part of their job.

The business case is simple. Faster reviews, fewer regressions, and a more consistent codebase, all without adding headcount.

Step-by-step: how to set up Claude for code review

The order below goes from a five-minute win to a fully wired pull request pipeline. Start where it makes sense for your team.

Step 1: Get access to the right surface area

If you only want to try this out, sign in to Claude.ai with a paid plan and you have everything you need for a manual review. If you want Claude to read your whole project, install Claude Code through your terminal using the official installer from Anthropic. If you want automatic pull request reviews, you will need an Anthropic API key and admin access to your GitHub repo.

Step 2: Set up custom instructions or a project knowledge base

This is the step most teams skip, and it is the one that determines whether Claude is useful or annoying. In Claude.ai you can attach a project with custom instructions. In Claude Code you can drop a CLAUDE.md file at the root of your repo. In the GitHub Action you configure instructions in the workflow file or a referenced markdown file.

Write your instructions in plain language. Tell Claude what language and framework you use, what your style rules are, what kinds of issues you care about, and what you want it to ignore. A short example for a Python API team might look like this: “We use FastAPI and SQLAlchemy. Prefer type hints everywhere. Flag any use of print for logging, any query that lacks a limit clause, and any endpoint missing input validation. Do not comment on formatting, the linter handles that.”

Step 3: Run your first manual review in Claude.ai

Open a new chat in your project, paste in a function or a diff, and ask for a review. Start with one specific question rather than an open-ended “review this.” Good first prompts are “find bugs in this function,” “check this diff for security issues,” or “does this match the patterns we use elsewhere in the project.”

Read the response critically. Note where Claude was right, where it was wrong, and where it missed context. That feedback is what you fold back into your instructions file.

Step 4: Try Claude Code for a multi-file change

Open your terminal, navigate to the project root, and run claude to start a session. Ask it to review the diff between your branch and main, or to look at a specific set of files. Claude Code reads surrounding files, so you can ask questions like “does this new endpoint follow the pattern in routes/?” and get a useful answer. This is where Claude starts to feel like a real teammate, because it has the context to spot inconsistencies a browser chat never could.

Step 5: Wire up the Claude GitHub Action

Add the official workflow file to .github/workflows/. Point it at your API key stored as a repository secret, set the trigger to pull_request, and reference your instructions file. The first PR after setup will feel slow, because Claude is reading the repo structure for the first time. By the third PR it is reviewing with real context, and the comments start landing in useful places.

Step 6: Triage the noise

The first week of automated reviews is loud. You will get suggestions you disagree with, comments on tests you wanted to keep verbose, and the occasional false positive on a security rule. Every disagreement is a chance to update your instructions file. After two or three rounds of tuning, the signal-to-noise ratio settles down and the reviews feel like they came from someone who knows your codebase.

Writing prompts that get useful review feedback

The difference between a useless Claude review and a great one almost always comes down to the prompt. Vague prompts get vague answers.

Instead of “review this code,” try prompts that name the role, the goal, and the constraints. For example: “You are a senior backend engineer reviewing a pull request on a payments service. Flag any race condition, any place we touch user money without an idempotency key, and any missing audit log. Ignore style and formatting.”

A few prompt patterns I keep coming back to:

• The bug hunt: “Find every possible bug in this function. For each one, give the line number, the failure mode, and a suggested fix.”
• The security pass: “Review this diff for OWASP top 10 issues. For each finding, rate severity and give a concrete patch.”
• The standards check: “Compare this new module to the patterns in the rest of the repo. List any places it breaks the conventions we use.”
• The readability pass: “Pretend you are a new hire reading this for the first time. What would confuse you, and how would you rename or restructure to make it obvious?”
• The test gap: “Look at this diff and tell me what cases are not covered by the existing tests. Suggest specific test names I should add.”

The pattern is consistent. Name the role, name the focus, name the output format, and tell Claude what to ignore. Each of those cuts down on unhelpful feedback.

Where to plug Claude into your existing workflow

The best place to slot Claude in is wherever a human reviewer is currently overloaded. For most teams that is the small-to-medium pull requests that block the queue. Let humans review the high-stakes changes like schema migrations, billing logic, and auth flows, and let Claude handle the long tail of refactors, doc updates, and bug fixes.

In practice this often looks like a label on the PR. Pull requests tagged claude-review trigger the bot, and the human reviewer only kicks in once the bot has signed off. Other teams use Claude as a first pass on every PR and treat the human review as the second pass. Both work, and which one fits depends on how much your team trusts the bot to catch real issues.

You can also use Claude to draft the review for you. If you are a senior engineer doing a manual review, paste the diff into Claude and ask for a list of concerns, then write your own comments using that as a starting point. This cuts a 20-minute review down to 5.

Common mistakes when using Claude for code review

Treating it as a replacement for human review. Claude is good at pattern matching, catching missing edge cases, and enforcing conventions. It is bad at understanding product intent, weighing trade-offs, and asking the uncomfortable question about whether a feature should exist at all. Keep a human in the loop for anything that touches product judgment.

Letting the instructions file go stale. The day your team adopts a new framework, the CLAUDE.md should change with it. Treat it like a config file, not a one-time write. Review it every quarter, or whenever the kind of feedback you are getting starts to drift.

Asking Claude to review code it cannot see. Pasting a 2,000-line file into the browser and asking for a full review is a recipe for shallow feedback. Use Claude Code for anything larger than a single screen, or break the change into smaller PRs. Smaller diffs get better reviews, from humans and from Claude.

Ignoring the false positives. Every automated review system will be wrong sometimes. The mistake is not the false positive, it is failing to capture it. When Claude flags something that is actually fine, update the instructions so it does not flag that pattern again. The system gets sharper every time you do this.

Letting Claude auto-merge or auto-fix without a human. Some teams wire Claude to push commits back to the PR. That can be useful for tiny lint fixes, but it is risky for anything substantive. Treat Claude’s suggestions as proposals, not patches, until a human has approved them.

Forgetting the cost angle. Long context reviews of large repos are not free. If you find yourself burning through tokens, narrow the scope of the review. Tell Claude which files to look at, which directories to ignore, and what kind of issues you care about. A focused review is faster and cheaper than a broad one.

Measuring whether the review is actually helping

The point of all this is not to have a chatbot commenting on your PRs. It is to ship better software with less friction. Track a few simple signals.

Look at the rate of bugs caught in production that should have been caught in review. If that number trends down over the months after you adopt Claude, the system is doing real work. Look at the median time from PR open to PR merge. If that drops without a corresponding rise in escaped bugs, your reviewers are getting faster, which is the whole goal. Look at the comments Claude leaves that humans actually mark as helpful in GitHub, and prune the instructions that lead to unhelpful comments.

One honest test is to turn Claude off for a week and see what slips through. If nothing material changes, your instructions file is too vague. If suddenly a class of bugs reappears, you have your answer.

Bringing it together

A useful Claude code review setup has three layers. A CLAUDE.md or custom instructions file that encodes your standards. A local Claude Code workflow for deep reviews when you want a second pair of eyes. A GitHub Action that runs on every pull request so the small stuff never blocks the queue. Each layer feeds the others, and each one gets sharper the more you use it.

The mistake is to think of Claude as a magic box. It is closer to a junior engineer you are training in public. Give it the right context, give it clear feedback, and it will surprise you with what it catches. Leave it to figure out your standards on its own, and it will waste everyone’s time.

Free download: Working With Claude — Field Guide We put together a practical guide covering this and more. Download it here.

For a structured walkthrough of building this into your operations, book a 60-min Omni Audit , https://calendly.com/sam-mckay/discovery-call?utm_source=edna-landing&utm_medium=blog&utm_campaign=product-keywords