collaborating-with-claude-code

🥈Silver

Collaborate with Claude Code for code review, debugging, and solution comparison. Operations teams use this to integrate Claude Code's capabilities into their workflows via a JSON bridge script. Connects to Codex CLI for structured JSON results.

3000Updated Today

Intermediate30min to implementautomation

Saves ~120 min per use

Quick InstallView Source

git clone https://github.com/ZhenHuangLab/collaborating-with-claude-code.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/ZhenHuangLab/collaborating-with-claude-code

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

I'm working on a [PROGRAMMING_LANGUAGE] script for [COMPANY] in the [INDUSTRY] sector. Here's the code I'm reviewing:

[CODE_SNIPPET]

Please analyze this code and provide feedback on:
1. Potential bugs or issues
2. Performance optimization opportunities
3. Best practice improvements
4. Security considerations

Format your response as a JSON object with these keys: 'analysis', 'suggestions', 'best_practices', and 'security'.

Example Output

```json
{
  "analysis": {
    "potential_issues": [
      "The function 'process_data' may have a memory leak due to unclosed file handles.",
      "The SQL query in 'fetch_records' is vulnerable to SQL injection.",
      "The error handling in 'main' function is incomplete."
    ],
    "performance": "The nested loops in 'calculate_stats' could be optimized using vectorized operations."
  },
  "suggestions": {
    "code_improvements": [
      "Consider using context managers for file operations in 'process_data'.",
      "Implement parameterized queries in 'fetch_records'.",
      "Add comprehensive error handling in 'main' function."
    ],
    "optimizations": "Refactor 'calculate_stats' to use NumPy arrays for better performance."
  },
  "best_practices": {
    "documentation": "Add docstrings to all functions to improve code readability.",
    "testing": "Implement unit tests for critical functions."
  },
  "security": {
    "vulnerabilities": "Address SQL injection vulnerability in 'fetch_records'.",
    "recommendations": "Implement input validation for all user-provided data."
  }
}
```