claude-code-engingeering

🥈Silver

@huangjia2019

This repository demonstrates how to use Claude Code to do real engineering work, not just writing code. 本项目是极客时间专栏《Claude Code 工程化实战》的官方配套示例仓库，目标很明确： 👉 把 Claude Code 从“对话式编码工具”，变成可设计、可复用、可治理的工程系统。

11040Updated Today

Intermediate30min to implementautomation

Saves ~30 min per use

Quick InstallView Source

git clone https://github.com/huangjia2019/claude-code-engingeering.git

Works with:

Claude

Overview

About This Skill

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/huangjia2019/claude-code-engingeering

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Act as a senior software engineer. I'm working on a [PROJECT] for [COMPANY] in the [INDUSTRY] sector. I need your help to [SPECIFIC TASK]. Here's the [DATA/CODE/REQUIREMENTS] I have so far: [INSERT DATA]. Please provide a detailed plan including architecture, implementation steps, and potential challenges. Use best practices and industry standards.

Example Output

## Project Plan: Customer Data Processing System for RetailCo

### Architecture Overview
- **Microservices**: Customer Service, Data Processing Service, Reporting Service
- **Database**: PostgreSQL for relational data, MongoDB for unstructured data
- **Message Queue**: RabbitMQ for asynchronous processing
- **Containerization**: Docker for deployment

### Implementation Steps
1. **Customer Service**:
   - Create RESTful API endpoints for customer data management
   - Implement authentication and authorization using JWT
   - Set up unit tests with Jest
2. **Data Processing Service**:
   - Develop ETL pipelines for data transformation
   - Implement data validation and error handling
   - Set up integration tests with Postman
3. **Reporting Service**:
   - Create dashboards using Grafana
   - Implement data aggregation and analysis
   - Set up performance tests with k6

### Potential Challenges
- **Data Consistency**: Implementing eventual consistency across services
- **Scalability**: Ensuring the system can handle peak loads during sales events
- **Security**: Protecting sensitive customer data and complying with GDPR

### Timeline
- Phase 1: Research and Planning (2 weeks)
- Phase 2: Development (6 weeks)
- Phase 3: Testing (2 weeks)
- Phase 4: Deployment (1 week)