Hands-on crash course for Claude Code with branch-based projects on MCP, subagents, hooks, and automation. For operations teams looking to streamline workflows and integrate AI-driven automation into their processes.
git clone https://github.com/emarco177/claude-code-crash-course.gitHands-on crash course for Claude Code with branch-based projects on MCP, subagents, hooks, and automation. For operations teams looking to streamline workflows and integrate AI-driven automation into their processes.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/emarco177/claude-code-crash-courseCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
I want a hands-on crash course for Claude Code. Focus on branch-based projects, MCP, subagents, hooks, and automation. Use [COMPANY] as the example organization. Provide clear step-by-step instructions with code examples.
# Claude Code Crash Course for [COMPANY]
## 1. Setting Up Your Environment
- Install the latest version of Claude Code
- Set up your MCP (Multi-Channel Platform) environment
- Create a new branch for your project: `git checkout -b automation-project`
## 2. Creating Subagents
```python
# Example subagent for data processing
class DataProcessorSubagent:
def __init__(self):
self.data = []
def process_data(self, input_data):
# Add your data processing logic here
self.data.append(input_data)
return f"Processed: {input_data}"
```
## 3. Implementing Hooks
- Use hooks to automate tasks in your workflow
- Example hook for data validation:
```python
def validate_data(data):
if not data:
raise ValueError("Data cannot be empty")
return True
```
## 4. Automating Workflows
- Use MCP to automate your workflows
- Example automation script:
```python
# Automate data processing and validation
processor = DataProcessorSubagent()
input_data = "sample data"
if validate_data(input_data):
result = processor.process_data(input_data)
print(result)
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