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senior-fullstack

Comprehensive fullstack development skill for building complete web applications with React, Next.js, Node.js, GraphQL, and PostgreSQL. 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.

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查看安装方法

包含的文件(7)

  • SKILL.md4.4 KB
  • references/architecture_patterns.md1.6 KB
  • references/development_workflows.md1.6 KB
  • references/tech_stack_guide.md1.6 KB
  • scripts/code_quality_analyzer.py3.1 KB
  • scripts/fullstack_scaffolder.py3.1 KB
  • scripts/project_scaffolder.py3.1 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

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

3. 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

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