Claude Reflect System enables Claude Code to learn from corrections and avoid repeating mistakes. Operations teams benefit from continuous improvement in code generation. It connects to Claude Code workflows and integrates with Python-based systems.
git clone https://github.com/haddock-development/claude-reflect-system.gitClaude Reflect System enables Claude Code to learn from corrections and avoid repeating mistakes. Operations teams benefit from continuous improvement in code generation. It connects to Claude Code workflows and integrates with Python-based systems.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/haddock-development/claude-reflect-systemCopy 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.
Enable the Claude Reflect System for my [COMPANY]'s [INDUSTRY] workflow. I want to integrate it with our [PYTHON_BASED_SYSTEM] to improve code generation accuracy. Please provide step-by-step instructions for setup and initial configuration.
# Claude Reflect System Integration Guide
## Step 1: Initial Setup
1. Install the Claude Reflect System package using pip:
```bash
pip install claude-reflect-system
```
2. Configure the system by editing the `config.json` file:
```json
{
"api_key": "your_api_key_here",
"learning_rate": 0.75,
"feedback_threshold": 0.5
}
```
## Step 2: Connect to Claude Code
1. Link the Reflect System to your Claude Code workflow by adding the following to your `main.py`:
```python
from claude_reflect_system import ReflectSystem
reflect = ReflectSystem(api_key='your_api_key_here')
reflect.connect_to_claude_code()
```
2. Monitor the integration status:
```python
print(reflect.connection_status)
```
## Step 3: Enable Continuous Learning
1. Activate the learning feature:
```python
reflect.enable_learning()
```
2. Set up feedback collection:
```python
reflect.setup_feedback_collection(threshold=0.5)
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