Senior Fullstack Complete toolkit for senior fullstack with modern tools and best practices. Quick Start Main Capabilities This skill provides three core capabilities through automated scripts:
Script 1: Fullstack Scaffolder
python scripts/fullstack_scaffolder.py [ options ]
Script 2: Project Scaffolder
python scripts/project_scaffolder.py [ options ]
Script 3: Code Quality Analyzer
python scripts/code_quality_analyzer.py [ options ] Core Capabilities 1. Fullstack Scaffolder Automated tool for fullstack scaffolder tasks. Features: Automated scaffolding Best practices built-in Configurable templates Quality checks Usage: python scripts/fullstack_scaffolder.py < project-path
[ options ] 2. Project Scaffolder Comprehensive analysis and optimization tool. Features: Deep analysis Performance metrics Recommendations Automated fixes Usage: python scripts/project_scaffolder.py < target-path
[ --verbose ] 3. Code Quality Analyzer Advanced tooling for specialized tasks. Features: Expert-level automation Custom configurations Integration ready Production-grade output Usage: python scripts/code_quality_analyzer.py [ arguments ] [ options ] Reference Documentation Tech Stack Guide Comprehensive guide available in references/tech_stack_guide.md : Detailed patterns and practices Code examples Best practices Anti-patterns to avoid Real-world scenarios Architecture Patterns Complete workflow documentation in references/architecture_patterns.md : Step-by-step processes Optimization strategies Tool integrations Performance tuning Troubleshooting guide Development Workflows Technical reference guide in references/development_workflows.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
Install dependencies
npm install
or
pip install -r requirements.txt
Configure environment
cp .env.example .env 2. Run Quality Checks
Use the analyzer script
python scripts/project_scaffolder.py .
Review recommendations
Apply fixes
- Implement Best Practices Follow the patterns and practices documented in: references/tech_stack_guide.md references/architecture_patterns.md references/development_workflows.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
Development
npm run dev npm run build npm run test npm run lint
Analysis
python scripts/project_scaffolder.py . python scripts/code_quality_analyzer.py --analyze
Deployment
docker build -t app:latest . docker-compose up -d kubectl apply -f k8s/ Troubleshooting Common Issues Check the comprehensive troubleshooting section in references/development_workflows.md . Getting Help Review reference documentation Check script output messages Consult tech stack documentation Review error logs Resources Pattern Reference: references/tech_stack_guide.md Workflow Guide: references/architecture_patterns.md Technical Guide: references/development_workflows.md Tool Scripts: scripts/ directory When to Use This skill is applicable to execute the workflow or actions described in the overview.