Task-Specific AI Agent Platform for Cursor AI
Project description
Agent Task
A powerful task management platform for AI agents in Cursor AI (v0.1.0).
Overview
Agent Task is a platform that helps manage, organize, and share task-specific configurations for AI agents in Cursor. It provides a structured way to define rules, guidelines, and model context protocols (MCP) for different AI tasks.
Features
- Task Management: Create, load, archive, and import task configurations
- Structured Organization: Maintains a consistent directory structure for each task
- Rule Management: Store and manage task-specific guidelines and rules
- MCP Support: Handle Model Context Protocol servers for advanced AI configurations
- Cross-platform: Works across different operating systems using standard paths
Installation
pip install agent-task
Directory Structure
Each task follows this standard structure:
task_name/
├── README.md # Task documentation
├── rules/ # Task-specific guidelines
│ └── rule.mdc # Main rules file
└── mcp/ # Model Context Protocol servers
Usage
Initialize a New Task
agent-task init task_name
List Available Tasks
agent-task list
Archive a Task
agent-task archive task_name
Import a Task
agent-task import task_name
Clone a Task from Marketplace
agent-task clone [URL]
Show Task Archive Directory
agent-task path
Configuration
The platform uses standard application directories for storing tasks and configurations:
- App Data: User-specific application data
- Config: User-specific configuration files
- Cache: User-specific cache data
- Logs: User-specific log files
Development
Project Structure
agent_task/__init__.py- Package initialization and versionpaths.py- Path management functionalitytask_manager.py- Core task management logiccli.py- Command-line interface implementation
Requirements
- Python 3.6+
appdirsfor cross-platform path managementpyyamlfor configuration handling- Additional dependencies as specified in requirements.txt
License
[Add your license information here]
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
Project details
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