Code Reviewer
Code review automation for TypeScript, JavaScript, Python, Go, Swift, Kotlin. Analyzes PRs for complexity and risk, checks code quality for SOLID violations and code smells, generates review reports. Use when reviewing pull requests, analyzing code quality, identifying issues, generating review checklists.
$ npx promptcreek add code-reviewerAuto-detects your installed agents and installs the skill to each one.
What This Skill Does
This skill provides automated code review tools for analyzing pull requests and detecting code quality issues. It generates review reports, identifies potential risks, and assesses code complexity. It's designed to help developers improve code quality and reduce the risk of introducing bugs.
When to Use
- Analyze a pull request for code quality.
- Detect hardcoded secrets in code.
- Identify SQL injection patterns.
- Check for long functions and large files.
- Assess code complexity and risk.
- Enforce coding standards and best practices.
Key Features
Installation
$ npx promptcreek add code-reviewerAuto-detects your installed agents (Claude Code, Cursor, Codex, etc.) and installs the skill to each one.
View Full Skill Content
Code Reviewer
Automated code review tools for analyzing pull requests, detecting code quality issues, and generating review reports.
Table of Contents
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
anytypes - 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:
| Issue | Threshold |
|-------|-----------|
| Long function | >50 lines |
| Large file | >500 lines |
| God class | >20 methods |
| Too many params | >5 |
| Deep nesting | >4 levels |
| High complexity | >10 branches |
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:
| Score | Verdict |
|-------|---------|
| 90+ with no high issues | Approve |
| 75+ with ≤2 high issues | Approve with suggestions |
| 50-74 | Request changes |
| <50 or critical issues | Block |
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
| Language | Extensions |
|----------|------------|
| Python | .py |
| TypeScript | .ts, .tsx |
| JavaScript | .js, .jsx, .mjs |
| Go | .go |
| Swift | .swift |
| Kotlin | .kt, .kts |
Supported Agents
Attribution
Details
- License
- MIT
- Source
- seeded
- Published
- 3/17/2026
Tags
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