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

• Generate Project Structure - Scaffold with optimal tech stack

Create project

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

• Configure Environment - Setup environment variables, database connection cd my-app cp .env.example .env

Edit .env with configuration

• Start Development Services - Launch Docker containers docker-compose up -d

• Run Database Migrations - Initialize database schema npm run migrate

• 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

• Run Comprehensive Analysis - Analyze entire codebase python scripts/code_quality_analyzer.py ./

• Review Recommendations - Prioritize issues by severity

• Fix Security Vulnerabilities - Update dependencies npm audit fix

• Fix Linting Errors - Automated fixes where possible npm run lint -- --fix

• Run Test Suite - Ensure all tests pass npm test

• Build for Production - Verify production build succeeds npm run build

• Re-analyze - Verify improvements python scripts/code_quality_analyzer.py ./ --json > quality-report.json

3. Production Deployment

Time: 1-2 hours for initial deployment

• Quality Checks - Ensure tests and build pass npm test && npm run build

• Build Docker Image - Create production container docker build -t my-app:latest .

• Deploy with Docker Compose - Production deployment docker-compose -f docker-compose.prod.yml up -d

Or deploy to Kubernetes: kubectl apply -f k8s/

• Verify Deployment - Health check and smoke tests curl https://your-app.com/health

• 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

• Architecture questions: Review architecture-patterns.md

• Technology selection: Consult tech-stacks.md

• Code quality issues: Run code quality analyzer and review output

• Best practices: See best-practices.md

• Tool usage: Run any script with --help flag

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