Code Reviewer

Automated code review tools for analyzing pull requests, detecting code quality issues, and generating review reports.

Table of Contents

• Tools
• PR Analyzer
• Code Quality Checker
• Review Report Generator
• Reference Guides
• Languages Supported

Tools

PR Analyzer

Analyzes git diff between branches to assess review complexity and identify risks.

# Analyze current branch against main
python scripts/pr_analyzer.py /path/to/repo

# Compare specific branches
python scripts/pr_analyzer.py . --base main --head feature-branch

# JSON output for integration
python scripts/pr_analyzer.py /path/to/repo --json

What it detects:

• Hardcoded secrets (passwords, API keys, tokens)
• SQL injection patterns (string concatenation in queries)
• Debug statements (debugger, console.log)
• ESLint rule disabling
• TypeScript any types
• TODO/FIXME comments

Output includes:

• Complexity score (1-10)
• Risk categorization (critical, high, medium, low)
• File prioritization for review order
• Commit message validation

Code Quality Checker

Analyzes source code for structural issues, code smells, and SOLID violations.

# Analyze a directory
python scripts/code_quality_checker.py /path/to/code

# Analyze specific language
python scripts/code_quality_checker.py . --language python

# JSON output
python scripts/code_quality_checker.py /path/to/code --json

What it detects:

• Long functions (>50 lines)
• Large files (>500 lines)
• God classes (>20 methods)
• Deep nesting (>4 levels)
• Too many parameters (>5)
• High cyclomatic complexity
• Missing error handling
• Unused imports
• Magic numbers

Thresholds:

Review Report Generator

Combines PR analysis and code quality findings into structured review reports.

# Generate report for current repo
python scripts/review_report_generator.py /path/to/repo

# Markdown output
python scripts/review_report_generator.py . --format markdown --output review.md

# Use pre-computed analyses
python scripts/review_report_generator.py . \
  --pr-analysis pr_results.json \
  --quality-analysis quality_results.json

Report includes:

• Review verdict (approve, request changes, block)
• Score (0-100)
• Prioritized action items
• Issue summary by severity
• Suggested review order

Verdicts:

Reference Guides

Code Review Checklist

references/code_review_checklist.md

Systematic checklists covering:

• Pre-review checks (build, tests, PR hygiene)
• Correctness (logic, data handling, error handling)
• Security (input validation, injection prevention)
• Performance (efficiency, caching, scalability)
• Maintainability (code quality, naming, structure)
• Testing (coverage, quality, mocking)
• Language-specific checks

Coding Standards

references/coding_standards.md

Language-specific standards for:

• TypeScript (type annotations, null safety, async/await)
• JavaScript (declarations, patterns, modules)
• Python (type hints, exceptions, class design)
• Go (error handling, structs, concurrency)
• Swift (optionals, protocols, errors)
• Kotlin (null safety, data classes, coroutines)

Common Antipatterns

references/common_antipatterns.md

Antipattern catalog with examples and fixes:

• Structural (god class, long method, deep nesting)
• Logic (boolean blindness, stringly typed code)
• Security (SQL injection, hardcoded credentials)
• Performance (N+1 queries, unbounded collections)
• Testing (duplication, testing implementation)
• Async (floating promises, callback hell)

Languages Supported