Code Reviewer
Run automated PR analysis, quality checks, and review report generation across TypeScript, JavaScript, Python, Go, Swift, and Kotlin repos.
Overview
Code Reviewer is an agent skill most often used in Ship (also Build backend) that automates PR analysis, code quality checks, security-oriented scanning, and review report generation for multi-language repos.
Install
npx skills add https://github.com/davila7/claude-code-templates --skill code-reviewerWhat is this skill?
- Three Python automations: PR analyzer, code quality checker, and review report generator
- Multi-language coverage: TypeScript, JavaScript, Python, Swift, Kotlin, and Go
- Best-practice and security-oriented analysis with configurable templates
- Performance metrics and recommendations from the quality checker
- Review checklist generation for consistent human-or-agent feedback
- 3 core automated scripts (PR analyzer, quality checker, review report generator)
- 6 languages explicitly supported in the skill description
Adoption & trust: 697 installs on skills.sh; 27.8k GitHub stars; 3/3 security scanners passed (skills.sh audits).
What problem does it solve?
You are merging solo-built features without a consistent review pass, so quality and security feedback varies wildly PR to PR.
Who is it for?
Indie devs and tiny teams who want a repeatable, script-backed review ritual before merge or release.
Skip if: Repos with no Python runtime for the bundled scripts, or teams that need certified SAST/compliance sign-off only from vendor tooling.
When should I use this skill?
Reviewing pull requests, providing code feedback, identifying issues, or ensuring code quality standards.
What do I get? / Deliverables
You get script-driven PR analysis, quality findings, and a generated review report you can act on or paste into your review thread.
- PR analysis output
- Code quality metrics and recommendations
- Generated review report / checklist
Recommended Skills
Journey fit
Spans multiple journey phases - primary shelf plus alternate fits below.
Ship is the canonical home for pull-request review, security scanning, and checklist-driven feedback—the skill’s stated triggers are PR review and quality standards. Review subphase fits the three-script workflow: analyze the PR, check quality, emit a structured review report.
Where it fits
Run pr_analyzer.py and review_report_generator.py on a feature branch before merging to main.
Quality-check a new API module in Python or Go while it is still isolated from production routes.
Use the quality checker’s security-oriented passes as a pre-release gate on auth-related diffs.
How it compares
Complements manual judgment with runnable analyzers—use instead of purely conversational “please review my PR” with no checklist or metrics.
Common Questions / FAQ
Who is code-reviewer for?
Solo builders and small teams shipping TS/JS/Python/Go/Swift/Kotlin who want automated PR analysis and review reports without hiring a full-time reviewer.
When should I use code-reviewer?
In Ship before merging pull requests or cutting a release; in Build when hardening a new module you want checked against best practices before wider use.
Is code-reviewer safe to install?
Scripts run locally against your project path—inspect what each analyzer reads or modifies, and use the Security Audits panel on this Prism page before granting automated fix modes.
SKILL.md
READMESKILL.md - Code Reviewer
# Code Reviewer Complete toolkit for code reviewer with modern tools and best practices. ## Quick Start ### Main Capabilities This skill provides three core capabilities through automated scripts: ```bash # Script 1: Pr Analyzer python scripts/pr_analyzer.py [options] # Script 2: Code Quality Checker python scripts/code_quality_checker.py [options] # Script 3: Review Report Generator python scripts/review_report_generator.py [options] ``` ## Core Capabilities ### 1. Pr Analyzer Automated tool for pr analyzer tasks. **Features:** - Automated scaffolding - Best practices built-in - Configurable templates - Quality checks **Usage:** ```bash python scripts/pr_analyzer.py <project-path> [options] ``` ### 2. Code Quality Checker Comprehensive analysis and optimization tool. **Features:** - Deep analysis - Performance metrics - Recommendations - Automated fixes **Usage:** ```bash python scripts/code_quality_checker.py <target-path> [--verbose] ``` ### 3. Review Report Generator Advanced tooling for specialized tasks. **Features:** - Expert-level automation - Custom configurations - Integration ready - Production-grade output **Usage:** ```bash python scripts/review_report_generator.py [arguments] [options] ``` ## Reference Documentation ### Code Review Checklist Comprehensive guide available in `references/code_review_checklist.md`: - Detailed patterns and practices - Code examples - Best practices - Anti-patterns to avoid - Real-world scenarios ### Coding Standards Complete workflow documentation in `references/coding_standards.md`: - Step-by-step processes - Optimization strategies - Tool integrations - Performance tuning - Troubleshooting guide ### Common Antipatterns Technical reference guide in `references/common_antipatterns.md`: - Technology stack details - Configuration examples - Integration patterns - Security considerations - Scalability guidelines ## Tech Stack **Languages:** TypeScript, JavaScript, Python, Go, Swift, Kotlin **Frontend:** React, Next.js, React Native, Flutter **Backend:** Node.js, Express, GraphQL, REST APIs **Database:** PostgreSQL, Prisma, NeonDB, Supabase **DevOps:** Docker, Kubernetes, Terraform, GitHub Actions, CircleCI **Cloud:** AWS, GCP, Azure ## Development Workflow ### 1. Setup and Configuration ```bash # Install dependencies npm install # or pip install -r requirements.txt # Configure environment cp .env.example .env ``` ### 2. Run Quality Checks ```bash # Use the analyzer script python scripts/code_quality_checker.py . # Review recommendations # Apply fixes ``` ### 3. Implement Best Practices Follow the patterns and practices documented in: - `references/code_review_checklist.md` - `references/coding_standards.md` - `references/common_antipatterns.md` ## Best Practices Summary ### Code Quality - Follow established patterns - Write comprehensive tests - Document decisions - Review regularly ### Performance - Measure before optimizing - Use appropriate caching - Optimize critical paths - Monitor in production ### Security - Validate all inputs - Use parameterized queries - Implement proper authentication - Keep dependencies updated ### Maintainability - Write clear code - Use consistent naming - Add helpful comments - Keep it simple ## Common Commands ```bash # Development npm run dev npm run build npm run test npm run lint # Analysis python scripts/code_quality_checker.py . python scripts/review_report_generator.py --analyze # Deployment docker build -t app:latest . docker-compose up -d kubectl apply -f k8s/ ``` ## Troubleshooting ### Common Issues Check the comprehensive troubleshooting section