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.

1,864 stars

Best use case

code-reviewer is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

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.

Teams using code-reviewer should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/cs-code-reviewer/SKILL.md --create-dirs "https://raw.githubusercontent.com/LeoYeAI/openclaw-master-skills/main/skills/cs-code-reviewer/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/cs-code-reviewer/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How code-reviewer Compares

Feature / Agentcode-reviewerStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Code Reviewer

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

---

## Table of Contents

- [Tools](#tools)
  - [PR Analyzer](#pr-analyzer)
  - [Code Quality Checker](#code-quality-checker)
  - [Review Report Generator](#review-report-generator)
- [Reference Guides](#reference-guides)
- [Languages Supported](#languages-supported)

---

## Tools

### PR Analyzer

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

```bash
# 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.

```bash
# 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.

```bash
# 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` |

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