Code Reviewer

---
name: "code-reviewer"
description: "Implement — 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, genera"
executor: HYBRID
skill_id: engineering.cs-engineering-team.code-reviewer
status: ADOPTED
security: {level: standard, pii: false, approval_required: false}
anchors:
  - engineering
  - code
  - automation
tier: 2
input_schema:
  - name: code_or_task
    type: string
    description: "Code snippet, script, or task description to process"
    required: true
output_schema:
  - name: report
    type: string
    description: "Analysis report or summary from code reviewer"
---

# 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` |

---

## Why This Skill Exists

Implement — 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, genera

<!-- SR_40: auto-generated from frontmatter `purpose`/`description` (OPP-Phase3). Expand with domain-specific rationale. -->

## When to Use

Use this skill when the task requires code reviewer capabilities.

<!-- SR_40: auto-generated from frontmatter `when`/`description` (OPP-Phase3). -->

## What If Fails

If this skill fails to produce the expected output: (1) verify input completeness, (2) retry with more specific context, (3) fall back to the parent workflow without this skill.

<!-- SR_40: auto-generated from frontmatter `what_if_fails` (OPP-Phase3). -->