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
- Fullstack Scaffolder
Automated tool for fullstack scaffolder tasks.
Features:
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Automated scaffolding
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Best practices built-in
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Configurable templates
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Quality checks
Usage:
python scripts/fullstack_scaffolder.py <project-path> [options]
- Project Scaffolder
Comprehensive analysis and optimization tool.
Features:
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Deep analysis
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Performance metrics
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Recommendations
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Automated fixes
Usage:
python scripts/project_scaffolder.py <target-path> [--verbose]
- Code Quality Analyzer
Advanced tooling for specialized tasks.
Features:
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Expert-level automation
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Custom configurations
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Integration ready
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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 :
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Detailed patterns and practices
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Code examples
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Best practices
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Anti-patterns to avoid
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Real-world scenarios
Architecture Patterns
Complete workflow documentation in references/architecture_patterns.md :
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Step-by-step processes
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Optimization strategies
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Tool integrations
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Performance tuning
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Troubleshooting guide
Development Workflows
Technical reference guide in references/development_workflows.md :
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Technology stack details
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Configuration examples
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Integration patterns
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Security considerations
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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
- Setup and Configuration
Install dependencies
npm install
or
pip install -r requirements.txt
Configure environment
cp .env.example .env
- 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:
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references/tech_stack_guide.md
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references/architecture_patterns.md
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references/development_workflows.md
Best Practices Summary
Code Quality
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Follow established patterns
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Write comprehensive tests
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Document decisions
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Review regularly
Performance
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Measure before optimizing
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Use appropriate caching
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Optimize critical paths
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Monitor in production
Security
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Validate all inputs
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Use parameterized queries
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Implement proper authentication
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Keep dependencies updated
Maintainability
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Write clear code
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Use consistent naming
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Add helpful comments
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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
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Review reference documentation
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Check script output messages
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Consult tech stack documentation
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Review error logs
Resources
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Pattern Reference: references/tech_stack_guide.md
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Workflow Guide: references/architecture_patterns.md
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Technical Guide: references/development_workflows.md
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Tool Scripts: scripts/ directory