Dotai is a context manager for AI agents, enabling integration and management of multiple agents within operations workflows. It connects to Claude and other AI tools, allowing teams to automate complex tasks and improve efficiency.
git clone https://github.com/udecode/dotai.githttps://github.com/udecode/dotai
Generate comprehensive app design documentation to streamline development processes.
Automate the creation and updating of technology stack documentation for better project management.
Utilize the debugging framework to identify and resolve issues in code systematically.
Create and manage pull requests with detailed descriptions and automated reviews.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/udecode/dotaiCopy 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'm working on a project for [COMPANY] in the [INDUSTRY] sector. I need to manage multiple agents with different plugins and commands. Can you help me set up a Dotai context manager to streamline this process? I have the following agents: [AGENT_LIST] and these plugins: [PLUGIN_LIST].
## Dotai Context Manager Setup Guide
### 1. Initialization
```python
from dotai import ContextManager
# Initialize the context manager
context = ContextManager()
```
### 2. Adding Agents and Plugins
```python
# Add agents
context.add_agent('Chatbot', 'chatbot_agent')
context.add_agent('DataProcessor', 'data_processor_agent')
# Add plugins
context.add_plugin('Chatbot', 'sentiment_analysis', 'sentiment_plugin')
context.add_plugin('DataProcessor', 'data_cleaning', 'cleaner_plugin')
```
### 3. Managing Commands
```python
# Define commands
commands = {
'Chatbot': {
'analyze_sentiment': {'plugin': 'sentiment_analysis', 'params': {'text': 'input_text'}}
},
'DataProcessor': {
'clean_data': {'plugin': 'data_cleaning', 'params': {'data': 'input_data'}}
}
}
# Add commands to context
context.add_commands(commands)
```
### 4. Executing Commands
```python
# Execute a command
result = context.execute('Chatbot', 'analyze_sentiment', {'input_text': 'I love this product!'})
print(result)
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