Claude Code Agent: Code Reviewer — Automated PR Review

What it is

This Claude Code agent automates code reviews by analyzing pull requests for security vulnerabilities, performance issues, maintainability concerns, and adherence to best practices. It installs with a single command and integrates into your development workflow.

The agent targets development teams that want consistent, thorough code reviews without bottlenecking on human reviewers. It supplements human review by catching issues that are easy to miss during manual inspection.

The project is actively maintained and suitable for both individual developers and teams looking to integrate it into their existing toolchain. Documentation and community support are available for onboarding.

How it saves time or tokens

Manual code reviews take 30-60 minutes per PR for thorough coverage. This agent completes an initial review in seconds, highlighting the areas that need human attention. It catches common security patterns (SQL injection, XSS, hardcoded secrets), performance anti-patterns, and style violations automatically.

How to use

1. Install the code reviewer skill in your Claude Code environment.
2. Open a pull request or have code changes ready for review.
3. Invoke the reviewer with /code-review or configure it to run automatically on PR events.
4. Review the findings: each issue includes severity, location, explanation, and suggested fix.

Example

# Install the code reviewer agent
mkdir -p .claude/skills/code-reviewer
cat > .claude/skills/code-reviewer/SKILL.md << 'SKILL'
# Code Reviewer Agent

Trigger

• When user says /code-review
• When reviewing PR changes

Checks

1. Security: SQL injection, XSS, secrets, auth bypass
2. Performance: N+1 queries, missing indexes, large allocations
3. Maintainability: function length, cyclomatic complexity, naming
4. Best practices: error handling, logging, testing coverage

SKILL

# Run the review

claude /code-review

Related on TokRepo

• AI Tools for Coding — AI coding assistants and development tools.
• AI Tools for Security — Security scanning tools that complement code review.

Common pitfalls

• Treating AI review as a replacement for human review. The agent catches pattern-based issues but misses domain-specific business logic errors. Use it as the first pass before human review.
• Not customizing the review rules for your project. The default rules are generic. Add project-specific patterns (your ORM's query builder, your auth middleware) for more relevant findings.
• Ignoring low-severity findings. While individually minor, accumulated code quality issues compound into maintenance debt. Address them during the review rather than deferring.
• Applying the skill without reading the documentation first. Each skill has specific prerequisites and configuration requirements that affect the quality of results.