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Includes project scaffolding, code quality analysis, architecture patterns, and complete tech stack guidance. Use when building new projects, analyzing code quality, implementing design patterns, or setting up development workflows.\n---\n\n# Senior Fullstack\n\nComplete toolkit for senior fullstack with modern tools and best practices.\n\n## Quick Start\n\n### Main Capabilities\n\nThis skill provides three core capabilities through automated scripts:\n\n```bash\n# Script 1: Fullstack Scaffolder\npython scripts\u002Ffullstack_scaffolder.py [options]\n\n# Script 2: Project Scaffolder\npython scripts\u002Fproject_scaffolder.py [options]\n\n# Script 3: Code Quality Analyzer\npython scripts\u002Fcode_quality_analyzer.py [options]\n```\n\n## Core Capabilities\n\n### 1. Fullstack Scaffolder\n\nAutomated tool for fullstack scaffolder tasks.\n\n**Features:**\n- Automated scaffolding\n- Best practices built-in\n- Configurable templates\n- Quality checks\n\n**Usage:**\n```bash\npython scripts\u002Ffullstack_scaffolder.py \u003Cproject-path> [options]\n```\n\n### 2. Project Scaffolder\n\nComprehensive analysis and optimization tool.\n\n**Features:**\n- Deep analysis\n- Performance metrics\n- Recommendations\n- Automated fixes\n\n**Usage:**\n```bash\npython scripts\u002Fproject_scaffolder.py \u003Ctarget-path> [--verbose]\n```\n\n### 3. Code Quality Analyzer\n\nAdvanced tooling for specialized tasks.\n\n**Features:**\n- Expert-level automation\n- Custom configurations\n- Integration ready\n- Production-grade output\n\n**Usage:**\n```bash\npython scripts\u002Fcode_quality_analyzer.py [arguments] [options]\n```\n\n## Reference Documentation\n\n### Tech Stack Guide\n\nComprehensive guide available in `references\u002Ftech_stack_guide.md`:\n\n- Detailed patterns and practices\n- Code examples\n- Best practices\n- Anti-patterns to avoid\n- Real-world scenarios\n\n### Architecture Patterns\n\nComplete workflow documentation in `references\u002Farchitecture_patterns.md`:\n\n- Step-by-step processes\n- Optimization strategies\n- Tool integrations\n- Performance tuning\n- Troubleshooting guide\n\n### Development Workflows\n\nTechnical reference guide in `references\u002Fdevelopment_workflows.md`:\n\n- Technology stack details\n- Configuration examples\n- Integration patterns\n- Security considerations\n- Scalability guidelines\n\n## Tech Stack\n\n**Languages:** TypeScript, JavaScript, Python, Go, Swift, Kotlin\n**Frontend:** React, Next.js, React Native, Flutter\n**Backend:** Node.js, Express, GraphQL, REST APIs\n**Database:** PostgreSQL, Prisma, NeonDB, Supabase\n**DevOps:** Docker, Kubernetes, Terraform, GitHub Actions, CircleCI\n**Cloud:** AWS, GCP, Azure\n\n## Development Workflow\n\n### 1. Setup and Configuration\n\n```bash\n# Install dependencies\nnpm install\n# or\npip install -r requirements.txt\n\n# Configure environment\ncp .env.example .env\n```\n\n### 2. Run Quality Checks\n\n```bash\n# Use the analyzer script\npython scripts\u002Fproject_scaffolder.py .\n\n# Review recommendations\n# Apply fixes\n```\n\n### 3. Implement Best Practices\n\nFollow the patterns and practices documented in:\n- `references\u002Ftech_stack_guide.md`\n- `references\u002Farchitecture_patterns.md`\n- `references\u002Fdevelopment_workflows.md`\n\n## Best Practices Summary\n\n### Code Quality\n- Follow established patterns\n- Write comprehensive tests\n- Document decisions\n- Review regularly\n\n### Performance\n- Measure before optimizing\n- Use appropriate caching\n- Optimize critical paths\n- Monitor in production\n\n### Security\n- Validate all inputs\n- Use parameterized queries\n- Implement proper authentication\n- Keep dependencies updated\n\n### Maintainability\n- Write clear code\n- Use consistent naming\n- Add helpful comments\n- Keep it simple\n\n## Common Commands\n\n```bash\n# Development\nnpm run dev\nnpm run build\nnpm run test\nnpm run lint\n\n# Analysis\npython scripts\u002Fproject_scaffolder.py .\npython scripts\u002Fcode_quality_analyzer.py --analyze\n\n# Deployment\ndocker build -t app:latest .\ndocker-compose up -d\nkubectl apply -f k8s\u002F\n```\n\n## Troubleshooting\n\n### Common Issues\n\nCheck the comprehensive troubleshooting section in `references\u002Fdevelopment_workflows.md`.\n\n### Getting Help\n\n- Review reference documentation\n- Check script output messages\n- Consult tech stack documentation\n- Review error logs\n\n## Resources\n\n- Pattern Reference: `references\u002Ftech_stack_guide.md`\n- Workflow Guide: `references\u002Farchitecture_patterns.md`\n- Technical Guide: `references\u002Fdevelopment_workflows.md`\n- Tool Scripts: `scripts\u002F` directory\n","# Senior Fullstack\n\nComplete toolkit for senior fullstack with modern tools and best practices.\n\n## Quick Start\n\n### Main Capabilities\n\nThis skill provides three core capabilities through automated scripts:\n\n```bash\n# Script 1: Fullstack Scaffolder\npython scripts\u002Ffullstack_scaffolder.py [options]\n\n# Script 2: Project Scaffolder\npython scripts\u002Fproject_scaffolder.py [options]\n\n# Script 3: Code Quality Analyzer\npython scripts\u002Fcode_quality_analyzer.py [options]\n```\n\n## Core Capabilities\n\n### 1. Fullstack Scaffolder\n\nAutomated tool for fullstack scaffolder tasks.\n\n**Features:**\n- Automated scaffolding\n- Best practices built-in\n- Configurable templates\n- Quality checks\n\n**Usage:**\n```bash\npython scripts\u002Ffullstack_scaffolder.py \u003Cproject-path> [options]\n```\n\n### 2. Project Scaffolder\n\nComprehensive analysis and optimization tool.\n\n**Features:**\n- Deep analysis\n- Performance metrics\n- Recommendations\n- Automated fixes\n\n**Usage:**\n```bash\npython scripts\u002Fproject_scaffolder.py \u003Ctarget-path> [--verbose]\n```\n\n### 3. Code Quality Analyzer\n\nAdvanced tooling for specialized tasks.\n\n**Features:**\n- Expert-level automation\n- Custom configurations\n- Integration ready\n- Production-grade output\n\n**Usage:**\n```bash\npython scripts\u002Fcode_quality_analyzer.py [arguments] [options]\n```\n\n## Reference Documentation\n\n### Tech Stack Guide\n\nComprehensive guide available in `references\u002Ftech_stack_guide.md`:\n\n- Detailed patterns and practices\n- Code examples\n- Best practices\n- Anti-patterns to avoid\n- Real-world scenarios\n\n### Architecture Patterns\n\nComplete workflow documentation in `references\u002Farchitecture_patterns.md`:\n\n- Step-by-step processes\n- Optimization strategies\n- Tool integrations\n- Performance tuning\n- Troubleshooting guide\n\n### Development Workflows\n\nTechnical reference guide in `references\u002Fdevelopment_workflows.md`:\n\n- Technology stack details\n- Configuration examples\n- Integration patterns\n- Security considerations\n- Scalability guidelines\n\n## Tech Stack\n\n**Languages:** TypeScript, JavaScript, Python, Go, Swift, Kotlin\n**Frontend:** React, Next.js, React Native, Flutter\n**Backend:** Node.js, Express, GraphQL, REST APIs\n**Database:** PostgreSQL, Prisma, NeonDB, Supabase\n**DevOps:** Docker, Kubernetes, Terraform, GitHub Actions, CircleCI\n**Cloud:** AWS, GCP, Azure\n\n## Development Workflow\n\n### 1. Setup and Configuration\n\n```bash\n# Install dependencies\nnpm install\n# or\npip install -r requirements.txt\n\n# Configure environment\ncp .env.example .env\n```\n\n### 2. Run Quality Checks\n\n```bash\n# Use the analyzer script\npython scripts\u002Fproject_scaffolder.py .\n\n# Review recommendations\n# Apply fixes\n```\n\n### 3. Implement Best Practices\n\nFollow the patterns and practices documented in:\n- `references\u002Ftech_stack_guide.md`\n- `references\u002Farchitecture_patterns.md`\n- `references\u002Fdevelopment_workflows.md`\n\n## Best Practices Summary\n\n### Code Quality\n- Follow established patterns\n- Write comprehensive tests\n- Document decisions\n- Review regularly\n\n### Performance\n- Measure before optimizing\n- Use appropriate caching\n- Optimize critical paths\n- Monitor in production\n\n### Security\n- Validate all inputs\n- Use parameterized queries\n- Implement proper authentication\n- Keep dependencies updated\n\n### Maintainability\n- Write clear code\n- Use consistent naming\n- Add helpful comments\n- Keep it simple\n\n## Common Commands\n\n```bash\n# Development\nnpm run dev\nnpm run build\nnpm run test\nnpm run lint\n\n# Analysis\npython scripts\u002Fproject_scaffolder.py .\npython scripts\u002Fcode_quality_analyzer.py --analyze\n\n# Deployment\ndocker build -t app:latest 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