senior-fullstack（高级全栈）

Senior Fullstack Developer

Expert-level fullstack development skill with production-ready tools for modern web application development. Covers architecture patterns, tech stack mastery, and automated quality analysis.

Overview

This skill provides comprehensive fullstack development capabilities through three core automation tools and extensive reference documentation. Whether you're scaffolding a new project, analyzing code quality, or implementing complex architecture patterns, this skill delivers production-ready solutions.

Use this skill when:

• Starting new fullstack projects with modern tech stacks
• Analyzing and improving code quality
• Implementing microservices or clean architecture
• Setting up development workflows and DevOps pipelines
• Making technology stack decisions

Core Capabilities

1. Project Scaffolder

Generate production-ready fullstack projects with complete infrastructure.

Features:

• Multiple stack templates (Next.js, React, Vue + GraphQL/REST)
• Docker Compose configuration
• CI/CD pipelines (GitHub Actions)
• Testing infrastructure (Jest, Cypress)
• Database setup and migrations
• TypeScript, ESLint, Prettier pre-configured

Usage:

python scripts/project_scaffolder.py my-project --type nextjs-graphql
cd my-project && docker-compose up -d

Supported Stacks:

• Next.js + GraphQL + PostgreSQL
• React + REST + MongoDB
• Vue + GraphQL + MySQL
• Express + TypeScript + PostgreSQL

2. Code Quality Analyzer

Comprehensive code analysis with actionable recommendations.

Features:

• Security vulnerability scanning
• Performance issue detection
• Test coverage assessment
• Documentation quality analysis
• Dependency audit
• Prioritized recommendations

Usage:

python scripts/code_quality_analyzer.py /path/to/project
python scripts/code_quality_analyzer.py /path/to/project --json

3. Fullstack Scaffolder

Rapid fullstack application generation with best practices built-in.

Usage:

python scripts/fullstack_scaffolder.py my-app --stack nextjs-graphql

Python Tools

1. Project Scaffolder

Generate production-ready fullstack projects with complete infrastructure.

Key Features:

• Multiple stack templates (Next.js, React, Vue + GraphQL/REST)
• Docker Compose configuration
• CI/CD pipelines (GitHub Actions)
• Testing infrastructure (Jest, Cypress)
• Database setup and migrations
• TypeScript, ESLint, Prettier pre-configured

Common Usage:

# Create Next.js + GraphQL project
python scripts/project_scaffolder.py my-project --type nextjs-graphql

# React + REST API
python scripts/project_scaffolder.py my-app --type react-rest

# Start services
cd my-project && docker-compose up -d

# Help
python scripts/project_scaffolder.py --help

Use Cases:

• Starting new fullstack projects with best practices
• Creating proof-of-concept applications
• Standardizing project structure across teams

2. Code Quality Analyzer

Comprehensive code analysis with actionable recommendations.

Key Features:

• Security vulnerability scanning
• Performance issue detection
• Test coverage assessment
• Documentation quality analysis
• Dependency audit
• Prioritized recommendations

Common Usage:

# Analyze project
python scripts/code_quality_analyzer.py /path/to/project

# JSON output for CI/CD
python scripts/code_quality_analyzer.py /path/to/project --json

# Focus on security
python scripts/code_quality_analyzer.py /path/to/project --security-only

# Help
python scripts/code_quality_analyzer.py --help

Use Cases:

• Pre-deployment quality checks
• Technical debt identification
• Security audit automation

3. Fullstack Scaffolder

Rapid fullstack application generation with best practices built-in.

Key Features:

• Quick project setup
• Modern tech stack selection
• Best practices integration
• Ready-to-deploy configuration

Common Usage:

# Scaffold fullstack app
python scripts/fullstack_scaffolder.py my-app --stack nextjs-graphql

# Custom configuration
python scripts/fullstack_scaffolder.py my-app --frontend react --backend express --db postgresql

# Help
python scripts/fullstack_scaffolder.py --help

Use Cases:

• Rapid prototyping
• Hackathon projects
• Client POC development

See tech-stacks.md for comprehensive tool documentation.

Key Workflows

1. New Project Setup

Time: 30 minutes for complete setup

1. Generate Project Structure - Scaffold with optimal tech stack

   # Create project
   python scripts/project_scaffolder.py my-app --type nextjs-graphql

1. Configure Environment - Setup environment variables, database connection

   cd my-app
   cp .env.example .env
   # Edit .env with configuration

1. Start Development Services - Launch Docker containers

   docker-compose up -d

1. Run Database Migrations - Initialize database schema

   npm run migrate

1. Start Development Server - Begin development

   npm run dev

See architecture-patterns.md for architecture guidance.

2. Code Quality Assessment

Time: 15-20 minutes for full analysis

1. Run Comprehensive Analysis - Analyze entire codebase

   python scripts/code_quality_analyzer.py ./

1. Review Recommendations - Prioritize issues by severity
2. Fix Security Vulnerabilities - Update dependencies

   npm audit fix

1. Fix Linting Errors - Automated fixes where possible

   npm run lint -- --fix

1. Run Test Suite - Ensure all tests pass

   npm test

1. Build for Production - Verify production build succeeds

   npm run build

1. Re-analyze - Verify improvements

   python scripts/code_quality_analyzer.py ./ --json > quality-report.json

3. Production Deployment

Time: 1-2 hours for initial deployment

1. Quality Checks - Ensure tests and build pass

   npm test && npm run build

1. Build Docker Image - Create production container

   docker build -t my-app:latest .

1. Deploy with Docker Compose - Production deployment

   docker-compose -f docker-compose.prod.yml up -d

Or deploy to Kubernetes:

   kubectl apply -f k8s/

1. Verify Deployment - Health check and smoke tests

   curl https://your-app.com/health

1. Monitor - Setup logging and monitoring dashboards

See best-practices.md for deployment best practices.

Reference Documentation

Detailed guides available in the references/ directory:

Architecture Patterns

architecture-patterns.md - Comprehensive architecture guide covering:

• Microservices architecture and service design
• Clean architecture and layer patterns
• Domain-driven design (DDD)
• Frontend architecture (atomic design, state management)
• Backend patterns (service layer, repository pattern)
• Performance optimization strategies
• Security patterns and deployment approaches

Technology Stacks

tech-stacks.md - Complete technology reference including:

• Languages (TypeScript, Python, Go, Kotlin, Swift)
• Frontend frameworks (React, Next.js, React Native, Flutter)
• Backend frameworks (Node.js, Express, GraphQL, REST)
• Databases (PostgreSQL, Prisma, NeonDB, Supabase, MongoDB)
• DevOps tools (Docker, Kubernetes, Terraform, CI/CD)
• Cloud platforms (AWS, GCP, Azure, Vercel, Railway)
• Testing frameworks and development tools

Best Practices

best-practices.md - Industry standards and guidelines for:

• Code quality and SOLID principles
• Testing strategies (unit, integration, e2e)
• Performance optimization (frontend and backend)
• Security best practices (authentication, authorization, validation)
• Error handling and logging
• Documentation standards
• Git workflow and deployment practices

Quick Start Workflows

Workflow 1: New Project Setup

# 1. Generate project structure
python scripts/project_scaffolder.py my-app --type nextjs-graphql

# 2. Configure environment
cd my-app
cp .env.example .env
# Edit .env with your configuration

# 3. Start development services
docker-compose up -d

# 4. Run database migrations
npm run migrate

# 5. Start development server
npm run dev

Workflow 2: Code Quality Assessment

# 1. Run comprehensive analysis
python scripts/code_quality_analyzer.py ./

# 2. Review recommendations and fix issues
npm audit fix                    # Security vulnerabilities
npm run lint -- --fix           # Linting errors
npm test                        # Run test suite

# 3. Build for production
npm run build

# 4. Re-analyze to verify improvements
python scripts/code_quality_analyzer.py ./ --json

Workflow 3: Production Deployment

# 1. Ensure quality checks pass
npm test && npm run build

# 2. Build Docker image
docker build -t my-app:latest .

# 3. Deploy with Docker Compose
docker-compose -f docker-compose.prod.yml up -d

# Or deploy to Kubernetes
kubectl apply -f k8s/

# 4. Verify deployment
curl https://your-app.com/health

Tech Stack Summary

Frontend: React, Next.js, TypeScript, Tailwind CSS Backend: Node.js, Express, GraphQL, REST APIs Database: PostgreSQL, Prisma ORM, NeonDB, Supabase DevOps: Docker, Kubernetes, Terraform, GitHub Actions Cloud: AWS, GCP, Azure, Vercel Testing: Jest, React Testing Library, Cypress

For detailed technology guides, see tech-stacks.md.

Common Use Cases

1. E-commerce Platform

• Next.js for SEO-optimized storefront
• GraphQL API for product catalog
• PostgreSQL for transactions
• Stripe integration for payments

2. SaaS Dashboard

• React SPA with complex state management
• REST API with Node.js/Express
• Real-time updates with WebSockets
• Role-based access control

3. Mobile + Web App

• React Native for iOS/Android
• Next.js for web presence
• Shared GraphQL API
• Supabase for backend services

4. Content Management System

• Next.js with ISR (Incremental Static Regeneration)
• Headless CMS integration
• PostgreSQL for structured data
• CDN distribution via Vercel

Additional Resources

• Architecture Guide: references/architecture-patterns.md
• Technology Reference: references/tech-stacks.md
• Best Practices: references/best-practices.md
• Python Tools: scripts/ directory

Getting Help

1. Architecture questions: Review architecture-patterns.md
2. Technology selection: Consult tech-stacks.md
3. Code quality issues: Run code quality analyzer and review output
4. Best practices: See best-practices.md
5. Tool usage: Run any script with --help flag

Version: 1.0.0 Last Updated: 2025-11-08 Documentation Structure: Progressive disclosure with references/