Automating Code Review with Claude Code Skills

Code review is essential but time-consuming. Senior developers spend hours reviewing PRs, often catching the same issues repeatedly. Junior developers wait for feedback. The whole team moves slower.

What if you could automate the mechanical parts of code review? Catch the obvious issues automatically, so human reviewers can focus on architecture, business logic, and mentoring?

This tutorial shows you how to build a comprehensive code review automation skill that integrates with your development workflow.

What Can Be Automated in Code Review?

Good Candidates for Automation

Style violations: Inconsistent formatting, naming conventions
Security issues: Hardcoded secrets, SQL injection patterns
Performance problems: N+1 queries, unnecessary loops
Common bugs: Null pointer patterns, off-by-one errors
Documentation gaps: Missing comments, outdated docs
Test coverage: Untested functions, missing edge cases

What Should Stay Human

Architecture decisions: Is this the right approach?
Business logic: Does this solve the problem correctly?
User experience: Will users understand this interface?
Mentoring opportunities: How can this developer grow?

Building the Review Skill

Core Review Command

.claude/commands/review.md:

---
description: Comprehensive code review automation
arguments:
  - name: target
    description: File, directory, or PR number to review
    required: true
  - name: focus
    description: Review focus (security, performance, style, all)
    required: false
    default: all
  - name: output
    description: Output format (inline, report, github)
    required: false
    default: report
---

# Automated Code Review

When the user runs /review [target], perform a comprehensive code review.

## Determine Review Scope

If target is a PR number:
1. Fetch PR details: `gh pr view [number]`
2. Get changed files: `gh pr diff [number] --name-only`
3. Review only changed lines

If target is a file or directory:
1. Find all source files
2. Review each file

## Review Process

For each file, analyze these categories:

### 1. Security Review

Check for:
- Hardcoded secrets (API keys, passwords, tokens)
- SQL injection vulnerabilities
- XSS vulnerabilities
- Insecure data handling
- Missing authentication/authorization
- Unsafe deserialization
- Path traversal risks

Severity levels:
- CRITICAL: Immediate security risk
- HIGH: Potential security issue
- MEDIUM: Best practice violation
- LOW: Minor concern

### 2. Performance Review

Check for:
- N+1 query patterns
- Unnecessary database calls
- Blocking operations in async code
- Memory leaks (event listeners, closures)
- Inefficient algorithms (nested loops on large data)
- Missing caching opportunities
- Large bundle imports

### 3. Code Quality Review

Check for:
- Functions over 50 lines
- Deep nesting (>3 levels)
- Magic numbers without constants
- Duplicated code
- Dead code
- Missing error handling
- Unclear variable names
- Missing type annotations

### 4. Documentation Review

Check for:
- Missing function documentation
- Outdated comments
- Unclear code without explanation
- Missing README updates for new features
- Undocumented environment variables

### 5. Testing Review

Check for:
- New code without tests
- Tests that don't test behavior
- Missing edge case tests
- Flaky test patterns
- Test code quality issues

## Generate Review

Format based on output argument:

### Output: report (default)

```markdown
# Code Review Report

**Target:** [file/PR]
**Date:** [date]
**Reviewer:** Claude Code

## Summary

- Critical issues: X
- High issues: Y
- Medium issues: Z
- Low issues: N

## Critical Issues (Must Fix)

### [Issue 1 Title]
**File:** path/to/file.ts:42
**Category:** Security
**Description:** [What's wrong]
**Recommendation:** [How to fix]
**Code:**

[problematic code]


## High Priority Issues

[...]

## Suggestions for Improvement

[...]

## Positive Observations

[What's done well]

Output: inline

Generate comments that can be added directly to code:

Add TODO comments for issues
Add explanatory comments for fixes
Use consistent format: // REVIEW: [category] - [issue]

Output: github

Generate GitHub review format for PR comments.


### Security-Focused Review

**.claude/commands/security-review.md:**

```markdown
---
description: Deep security analysis of code
arguments:
  - name: target
    description: File or directory to analyze
    required: true
---

# Security Code Review

Specialized security-focused code review.

## OWASP Top 10 Check

### A01: Broken Access Control
- Check authorization on all endpoints
- Verify user can only access their data
- Look for IDOR vulnerabilities
- Check for privilege escalation paths

### A02: Cryptographic Failures
- Identify sensitive data handling
- Check encryption algorithms (no MD5/SHA1 for passwords)
- Verify secure key storage
- Check TLS configuration

### A03: Injection
- SQL injection in database queries
- Command injection in shell calls
- LDAP injection
- XPath injection
- Template injection

### A04: Insecure Design
- Check business logic flaws
- Verify threat modeling was done
- Look for missing rate limiting

### A05: Security Misconfiguration
- Default credentials
- Unnecessary features enabled
- Missing security headers
- Verbose error messages

### A06: Vulnerable Components
- Check dependencies for known CVEs
- Outdated libraries
- Abandoned packages

### A07: Authentication Failures
- Weak password policies
- Missing MFA
- Session management issues
- Credential stuffing vulnerabilities

### A08: Software and Data Integrity
- Untrusted deserialization
- Missing integrity checks
- Insecure CI/CD

### A09: Logging and Monitoring
- Missing security logs
- Sensitive data in logs
- Missing alerting

### A10: Server-Side Request Forgery
- Unvalidated URLs
- Internal service access
- Cloud metadata access

## Output

Generate a security report with:
- Vulnerability classification
- CVSS score estimate
- Proof of concept if applicable
- Remediation steps
- References to security standards

Performance Review Skill

.claude/commands/perf-review.md:

---
description: Performance-focused code analysis
arguments:
  - name: target
    description: File or directory to analyze
    required: true
---

# Performance Code Review

Analyze code for performance issues.

## Database Performance

### Query Analysis
- Count database calls per operation
- Identify N+1 query patterns
- Check for missing indexes (based on WHERE clauses)
- Look for SELECT * usage
- Identify unneeded eager loading

### Example N+1 Detection

```javascript
// BAD: N+1 query pattern
const users = await User.findAll();
for (const user of users) {
  const orders = await Order.findByUser(user.id);  // N queries!
}

// GOOD: Single query with join
const users = await User.findAll({ include: Order });

Algorithm Complexity

Time Complexity

Flag O(n^2) or worse in hot paths
Identify unnecessary nested loops
Suggest more efficient alternatives

Space Complexity

Large object creation in loops
Memory leaks (closures, event listeners)
Unbounded caches

Frontend Performance

Bundle Size

Large imports: import _ from 'lodash' vs import { map } from 'lodash'
Unnecessary dependencies
Missing code splitting

Rendering

Unnecessary re-renders
Missing memoization
Heavy computations in render path

Network

Missing caching headers
Unoptimized images
Too many requests

Async Performance

Blocking Operations

Synchronous I/O in async code
Missing parallelization
Serial async when parallel possible

Example

// BAD: Serial execution
const a = await fetchA();
const b = await fetchB();
const c = await fetchC();

// GOOD: Parallel execution
const [a, b, c] = await Promise.all([
  fetchA(),
  fetchB(),
  fetchC()
]);

Output

Generate performance report with:

Issue classification
Performance impact estimate
Benchmarking suggestions
Optimized code examples


## Integrating with GitHub

### PR Review Workflow

**.claude/commands/review-pr.md:**

```markdown
---
description: Review a GitHub PR and post comments
arguments:
  - name: pr
    description: PR number
    required: true
  - name: post
    description: Whether to post review to GitHub
    required: false
    default: false
---

# GitHub PR Review

Review a PR and optionally post the review to GitHub.

## Fetch PR Information

1. Get PR details: `gh pr view [pr] --json title,body,author,files`
2. Get full diff: `gh pr diff [pr]`
3. Get existing comments: `gh pr view [pr] --comments`

## Analyze Changes

For each changed file:

1. Determine change type:
   - New file
   - Modified file
   - Deleted file
   - Renamed file

2. Review only changed lines:
   - Focus on additions (+)
   - Consider deletions (-) for context

3. Apply standard review criteria

## Compile Review

Structure the review:

### Summary
- Overall assessment: APPROVE / REQUEST_CHANGES / COMMENT
- Brief summary of the PR purpose
- Key concerns or praise

### File Comments
For each issue found:
- File path
- Line number (from diff)
- Comment text
- Suggestion if applicable

### General Comments
- Architecture observations
- Testing suggestions
- Documentation needs

## Post to GitHub (if --post)

Use GitHub CLI to submit review:

```bash
gh pr review [pr] --comment --body "Review body here"

# Or for specific line comments
gh api repos/{owner}/{repo}/pulls/{pr}/comments \
  -f body="Comment text" \
  -f path="file/path.ts" \
  -f line=42 \
  -f side="RIGHT"

Output Format

PR Review: #[number] - [title]
Author: @[username]
Files Changed: [count]

## Summary
[Brief assessment]

## Verdict: [APPROVE/REQUEST_CHANGES/COMMENT]

## Issues Found

### Critical
- file.ts:42 - [Issue description]

### Suggestions
- file.ts:100 - [Suggestion]

## Positive Notes
- Good test coverage
- Clear naming conventions

[Posted to GitHub: Yes/No]


### Automated PR Review Hook

**.claude/hooks/pr-opened.md:**

```markdown
---
trigger:
  event: pull_request
  action: opened
---

# Automatic PR Review

When a PR is opened, automatically run initial review.

## Process

1. Wait 30 seconds (let CI start)
2. Run /review-pr [number]
3. If critical issues found, add comment
4. If no critical issues, add approval

## Behavior

Only run on PRs that:
- Are from repository members (not forks)
- Are not marked as draft
- Are not from bots

## Comment Format

Automated Code Review

I've performed an initial automated review of this PR.

Summary

[Brief summary of findings]

Issues Found

[List of issues or "No significant issues found"]

This is an automated review. A human reviewer will follow up.

Building a Review Dashboard

Coverage Tracking

.claude/commands/review-stats.md:

---
description: Generate code review statistics
arguments:
  - name: period
    description: Time period (week, month, quarter)
    required: false
    default: week
---

# Review Statistics

Generate statistics about code reviews.

## Gather Data

1. Get merged PRs in period: `gh pr list --state merged --limit 100`
2. For each PR, analyze:
   - Time to first review
   - Time to merge
   - Number of review rounds
   - Issues found by automated review
   - Issues found by human review

## Calculate Metrics

### Review Efficiency
- Average time to first review
- Average time to merge
- Percentage of PRs with automated review issues

### Issue Categories
- Security issues found (automated vs human)
- Performance issues found
- Style issues found

### Review Quality
- PRs that required rework after merge
- Issues that slipped through review

## Generate Report

Code Review Statistics - [Period]

PRs Merged: 42 Average Time to Review: 4.2 hours Average Time to Merge: 18.6 hours

Issues Found by Automated Review: 127

Security: 12
Performance: 23
Style: 67
Documentation: 25

Issues Found by Human Review: 45

Architecture: 18
Business Logic: 15
Other: 12

Review Effectiveness:

94% of security issues caught before merge
87% of performance issues caught before merge

Top Issue Categories:

Missing error handling (23 occurrences)
Incomplete test coverage (19 occurrences)
Documentation gaps (17 occurrences)

Recommendations:

Add error handling checklist to PR template
Require test coverage report in CI
Schedule documentation review sessions

Review Standards Configuration

Create a configuration file for your review standards:

.claude/review-config.json:

{
  "security": {
    "enabled": true,
    "failOnCritical": true,
    "patterns": {
      "secrets": [
        "api[_-]?key",
        "secret[_-]?key",
        "password",
        "bearer"
      ],
      "sqlInjection": [
        "query\\(.*\\+.*\\)",
        "execute\\(.*\\+.*\\)"
      ]
    }
  },
  "performance": {
    "enabled": true,
    "maxFunctionLines": 50,
    "maxFileLines": 500,
    "flagPatterns": [
      "for.*for",
      "SELECT \\*"
    ]
  },
  "style": {
    "enabled": true,
    "requireTypes": true,
    "maxLineLength": 100,
    "namingConvention": "camelCase"
  },
  "documentation": {
    "enabled": true,
    "requireFunctionDocs": true,
    "requireClassDocs": true
  },
  "testing": {
    "enabled": true,
    "minCoverage": 80,
    "requireTestsForNewFiles": true
  }
}

Reference in your review skill:

## Load Configuration

Read `.claude/review-config.json` for review standards.
Apply configured rules and thresholds.
Skip disabled categories.

Best Practices

1. Start Non-Blocking

Begin with reviews that don't block PRs:

Add comments but don't require changes
Build trust in the system
Tune for false positives

2. Gradually Increase Enforcement

As confidence grows:

Week 1-2: Comment only
Week 3-4: Request changes on critical issues
Week 5+: Block PRs with unfixed critical issues

3. Track False Positives

Monitor when automated reviews are wrong:

Log dismissed comments
Review patterns in false positives
Update rules to reduce noise

4. Complement Humans

Automated review should:

Handle mechanical checks
Free humans for high-value review
Never replace architectural feedback
Support, not replace, mentoring

5. Make It Easy to Override

Sometimes rules should be broken. Provide clear override mechanisms:

// @review-ignore: security/hardcoded-secret
// This is an example for documentation, not a real secret
const EXAMPLE_API_KEY = 'example-key-12345';

Summary

Automated code review catches mechanical issues so human reviewers can focus on what matters: architecture, business logic, and developer growth.

Skills Created

Skill	Purpose
`/review`	Comprehensive code review
`/security-review`	Deep security analysis
`/perf-review`	Performance analysis
`/review-pr`	GitHub PR review
`/review-stats`	Review metrics

Integration Points

Pre-commit hooks for local review
CI/CD for automated PR review
GitHub Actions for comment posting
Dashboard for metrics tracking

Want to automate documentation too? Check out Documentation Generation Skills for doc automation.

Automating Code Review with Claude Code Skills

Code review is essential but time-consuming. Senior developers spend hours reviewing PRs, often catching the same issues repeatedly. Junior developers wait for feedback. The whole team moves slower.

What if you could automate the mechanical parts of code review? Catch the obvious issues automatically, so human reviewers can focus on architecture, business logic, and mentoring?

This tutorial shows you how to build a comprehensive code review automation skill that integrates with your development workflow.

What Can Be Automated in Code Review?

Good Candidates for Automation

Style violations: Inconsistent formatting, naming conventions
Security issues: Hardcoded secrets, SQL injection patterns
Performance problems: N+1 queries, unnecessary loops
Common bugs: Null pointer patterns, off-by-one errors
Documentation gaps: Missing comments, outdated docs
Test coverage: Untested functions, missing edge cases

What Should Stay Human

Architecture decisions: Is this the right approach?
Business logic: Does this solve the problem correctly?
User experience: Will users understand this interface?
Mentoring opportunities: How can this developer grow?

Building the Review Skill

Core Review Command

.claude/commands/review.md:

---
description: Comprehensive code review automation
arguments:
  - name: target
    description: File, directory, or PR number to review
    required: true
  - name: focus
    description: Review focus (security, performance, style, all)
    required: false
    default: all
  - name: output
    description: Output format (inline, report, github)
    required: false
    default: report
---

# Automated Code Review

When the user runs /review [target], perform a comprehensive code review.

## Determine Review Scope

If target is a PR number:
1. Fetch PR details: `gh pr view [number]`
2. Get changed files: `gh pr diff [number] --name-only`
3. Review only changed lines

If target is a file or directory:
1. Find all source files
2. Review each file

## Review Process

For each file, analyze these categories:

### 1. Security Review

Check for:
- Hardcoded secrets (API keys, passwords, tokens)
- SQL injection vulnerabilities
- XSS vulnerabilities
- Insecure data handling
- Missing authentication/authorization
- Unsafe deserialization
- Path traversal risks

Severity levels:
- CRITICAL: Immediate security risk
- HIGH: Potential security issue
- MEDIUM: Best practice violation
- LOW: Minor concern

### 2. Performance Review

Check for:
- N+1 query patterns
- Unnecessary database calls
- Blocking operations in async code
- Memory leaks (event listeners, closures)
- Inefficient algorithms (nested loops on large data)
- Missing caching opportunities
- Large bundle imports

### 3. Code Quality Review

Check for:
- Functions over 50 lines
- Deep nesting (>3 levels)
- Magic numbers without constants
- Duplicated code
- Dead code
- Missing error handling
- Unclear variable names
- Missing type annotations

### 4. Documentation Review

Check for:
- Missing function documentation
- Outdated comments
- Unclear code without explanation
- Missing README updates for new features
- Undocumented environment variables

### 5. Testing Review

Check for:
- New code without tests
- Tests that don't test behavior
- Missing edge case tests
- Flaky test patterns
- Test code quality issues

## Generate Review

Format based on output argument:

### Output: report (default)

```markdown
# Code Review Report

**Target:** [file/PR]
**Date:** [date]
**Reviewer:** Claude Code

## Summary

- Critical issues: X
- High issues: Y
- Medium issues: Z
- Low issues: N

## Critical Issues (Must Fix)

### [Issue 1 Title]
**File:** path/to/file.ts:42
**Category:** Security
**Description:** [What's wrong]
**Recommendation:** [How to fix]
**Code:**

[problematic code]


## High Priority Issues

[...]

## Suggestions for Improvement

[...]

## Positive Observations

[What's done well]

Output: inline

Generate comments that can be added directly to code:

Add TODO comments for issues
Add explanatory comments for fixes
Use consistent format: // REVIEW: [category] - [issue]

Output: github

Generate GitHub review format for PR comments.


### Security-Focused Review

**.claude/commands/security-review.md:**

```markdown
---
description: Deep security analysis of code
arguments:
  - name: target
    description: File or directory to analyze
    required: true
---

# Security Code Review

Specialized security-focused code review.

## OWASP Top 10 Check

### A01: Broken Access Control
- Check authorization on all endpoints
- Verify user can only access their data
- Look for IDOR vulnerabilities
- Check for privilege escalation paths

### A02: Cryptographic Failures
- Identify sensitive data handling
- Check encryption algorithms (no MD5/SHA1 for passwords)
- Verify secure key storage
- Check TLS configuration

### A03: Injection
- SQL injection in database queries
- Command injection in shell calls
- LDAP injection
- XPath injection
- Template injection

### A04: Insecure Design
- Check business logic flaws
- Verify threat modeling was done
- Look for missing rate limiting

### A05: Security Misconfiguration
- Default credentials
- Unnecessary features enabled
- Missing security headers
- Verbose error messages

### A06: Vulnerable Components
- Check dependencies for known CVEs
- Outdated libraries
- Abandoned packages

### A07: Authentication Failures
- Weak password policies
- Missing MFA
- Session management issues
- Credential stuffing vulnerabilities

### A08: Software and Data Integrity
- Untrusted deserialization
- Missing integrity checks
- Insecure CI/CD

### A09: Logging and Monitoring
- Missing security logs
- Sensitive data in logs
- Missing alerting

### A10: Server-Side Request Forgery
- Unvalidated URLs
- Internal service access
- Cloud metadata access

## Output

Generate a security report with:
- Vulnerability classification
- CVSS score estimate
- Proof of concept if applicable
- Remediation steps
- References to security standards

Performance Review Skill

.claude/commands/perf-review.md:

---
description: Performance-focused code analysis
arguments:
  - name: target
    description: File or directory to analyze
    required: true
---

# Performance Code Review

Analyze code for performance issues.

## Database Performance

### Query Analysis
- Count database calls per operation
- Identify N+1 query patterns
- Check for missing indexes (based on WHERE clauses)
- Look for SELECT * usage
- Identify unneeded eager loading

### Example N+1 Detection

```javascript
// BAD: N+1 query pattern
const users = await User.findAll();
for (const user of users) {
  const orders = await Order.findByUser(user.id);  // N queries!
}

// GOOD: Single query with join
const users = await User.findAll({ include: Order });

Algorithm Complexity

Time Complexity

Flag O(n^2) or worse in hot paths
Identify unnecessary nested loops
Suggest more efficient alternatives

Space Complexity

Large object creation in loops
Memory leaks (closures, event listeners)
Unbounded caches

Frontend Performance

Bundle Size

Large imports: import _ from 'lodash' vs import { map } from 'lodash'
Unnecessary dependencies
Missing code splitting

Rendering

Unnecessary re-renders
Missing memoization
Heavy computations in render path

Network

Missing caching headers
Unoptimized images
Too many requests

Async Performance

Blocking Operations

Synchronous I/O in async code
Missing parallelization
Serial async when parallel possible

Example

// BAD: Serial execution
const a = await fetchA();
const b = await fetchB();
const c = await fetchC();

// GOOD: Parallel execution
const [a, b, c] = await Promise.all([
  fetchA(),
  fetchB(),
  fetchC()
]);

Output

Generate performance report with:

Issue classification
Performance impact estimate
Benchmarking suggestions
Optimized code examples


## Integrating with GitHub

### PR Review Workflow

**.claude/commands/review-pr.md:**

```markdown
---
description: Review a GitHub PR and post comments
arguments:
  - name: pr
    description: PR number
    required: true
  - name: post
    description: Whether to post review to GitHub
    required: false
    default: false
---

# GitHub PR Review

Review a PR and optionally post the review to GitHub.

## Fetch PR Information

1. Get PR details: `gh pr view [pr] --json title,body,author,files`
2. Get full diff: `gh pr diff [pr]`
3. Get existing comments: `gh pr view [pr] --comments`

## Analyze Changes

For each changed file:

1. Determine change type:
   - New file
   - Modified file
   - Deleted file
   - Renamed file

2. Review only changed lines:
   - Focus on additions (+)
   - Consider deletions (-) for context

3. Apply standard review criteria

## Compile Review

Structure the review:

### Summary
- Overall assessment: APPROVE / REQUEST_CHANGES / COMMENT
- Brief summary of the PR purpose
- Key concerns or praise

### File Comments
For each issue found:
- File path
- Line number (from diff)
- Comment text
- Suggestion if applicable

### General Comments
- Architecture observations
- Testing suggestions
- Documentation needs

## Post to GitHub (if --post)

Use GitHub CLI to submit review:

```bash
gh pr review [pr] --comment --body "Review body here"

# Or for specific line comments
gh api repos/{owner}/{repo}/pulls/{pr}/comments \
  -f body="Comment text" \
  -f path="file/path.ts" \
  -f line=42 \
  -f side="RIGHT"

Output Format

PR Review: #[number] - [title]
Author: @[username]
Files Changed: [count]

## Summary
[Brief assessment]

## Verdict: [APPROVE/REQUEST_CHANGES/COMMENT]

## Issues Found

### Critical
- file.ts:42 - [Issue description]

### Suggestions
- file.ts:100 - [Suggestion]

## Positive Notes
- Good test coverage
- Clear naming conventions

[Posted to GitHub: Yes/No]


### Automated PR Review Hook

**.claude/hooks/pr-opened.md:**

```markdown
---
trigger:
  event: pull_request
  action: opened
---

# Automatic PR Review

When a PR is opened, automatically run initial review.

## Process

1. Wait 30 seconds (let CI start)
2. Run /review-pr [number]
3. If critical issues found, add comment
4. If no critical issues, add approval

## Behavior

Only run on PRs that:
- Are from repository members (not forks)
- Are not marked as draft
- Are not from bots

## Comment Format

Automated Code Review

I've performed an initial automated review of this PR.

Summary

[Brief summary of findings]

Issues Found

[List of issues or "No significant issues found"]

This is an automated review. A human reviewer will follow up.

Building a Review Dashboard

Coverage Tracking

.claude/commands/review-stats.md:

---
description: Generate code review statistics
arguments:
  - name: period
    description: Time period (week, month, quarter)
    required: false
    default: week
---

# Review Statistics

Generate statistics about code reviews.

## Gather Data

1. Get merged PRs in period: `gh pr list --state merged --limit 100`
2. For each PR, analyze:
   - Time to first review
   - Time to merge
   - Number of review rounds
   - Issues found by automated review
   - Issues found by human review

## Calculate Metrics

### Review Efficiency
- Average time to first review
- Average time to merge
- Percentage of PRs with automated review issues

### Issue Categories
- Security issues found (automated vs human)
- Performance issues found
- Style issues found

### Review Quality
- PRs that required rework after merge
- Issues that slipped through review

## Generate Report

Code Review Statistics - [Period]

PRs Merged: 42 Average Time to Review: 4.2 hours Average Time to Merge: 18.6 hours

Issues Found by Automated Review: 127

Security: 12
Performance: 23
Style: 67
Documentation: 25

Issues Found by Human Review: 45

Architecture: 18
Business Logic: 15
Other: 12

Review Effectiveness:

94% of security issues caught before merge
87% of performance issues caught before merge

Top Issue Categories:

Missing error handling (23 occurrences)
Incomplete test coverage (19 occurrences)
Documentation gaps (17 occurrences)

Recommendations:

Add error handling checklist to PR template
Require test coverage report in CI
Schedule documentation review sessions

Review Standards Configuration

Create a configuration file for your review standards:

.claude/review-config.json:

{
  "security": {
    "enabled": true,
    "failOnCritical": true,
    "patterns": {
      "secrets": [
        "api[_-]?key",
        "secret[_-]?key",
        "password",
        "bearer"
      ],
      "sqlInjection": [
        "query\\(.*\\+.*\\)",
        "execute\\(.*\\+.*\\)"
      ]
    }
  },
  "performance": {
    "enabled": true,
    "maxFunctionLines": 50,
    "maxFileLines": 500,
    "flagPatterns": [
      "for.*for",
      "SELECT \\*"
    ]
  },
  "style": {
    "enabled": true,
    "requireTypes": true,
    "maxLineLength": 100,
    "namingConvention": "camelCase"
  },
  "documentation": {
    "enabled": true,
    "requireFunctionDocs": true,
    "requireClassDocs": true
  },
  "testing": {
    "enabled": true,
    "minCoverage": 80,
    "requireTestsForNewFiles": true
  }
}

Reference in your review skill:

## Load Configuration

Read `.claude/review-config.json` for review standards.
Apply configured rules and thresholds.
Skip disabled categories.

Best Practices

1. Start Non-Blocking

Begin with reviews that don't block PRs:

Add comments but don't require changes
Build trust in the system
Tune for false positives

2. Gradually Increase Enforcement

As confidence grows:

Week 1-2: Comment only
Week 3-4: Request changes on critical issues
Week 5+: Block PRs with unfixed critical issues

3. Track False Positives

Monitor when automated reviews are wrong:

Log dismissed comments
Review patterns in false positives
Update rules to reduce noise

4. Complement Humans

Automated review should:

Handle mechanical checks
Free humans for high-value review
Never replace architectural feedback
Support, not replace, mentoring

5. Make It Easy to Override

Sometimes rules should be broken. Provide clear override mechanisms:

// @review-ignore: security/hardcoded-secret
// This is an example for documentation, not a real secret
const EXAMPLE_API_KEY = 'example-key-12345';

Summary

Automated code review catches mechanical issues so human reviewers can focus on what matters: architecture, business logic, and developer growth.

Skills Created

Skill	Purpose
`/review`	Comprehensive code review
`/security-review`	Deep security analysis
`/perf-review`	Performance analysis
`/review-pr`	GitHub PR review
`/review-stats`	Review metrics

Integration Points

Pre-commit hooks for local review
CI/CD for automated PR review
GitHub Actions for comment posting
Dashboard for metrics tracking

Want to automate documentation too? Check out Documentation Generation Skills for doc automation.