Agentic Cursorrules : Practical methods for managing multiple AI agents in the cursor.

Agentic Cursorrules

Development & Tools Coding Assistants #AI agent management #Codebase partitioning #Conflict prevention #File tree management #Domain-specific rules Standard Picks Open Source

Overview :

agentic-cursorrules is a Python-based tool that manages multiple AI agents within large codebases by employing strict directory partitioning and domain boundaries. It aims to prevent merge conflicts and maintain consistency in the codebase by partitioning the library, generating domain-specific Markdown files, and providing clear context and access rules for AI agents. This tool enhances project management efficiency in AI-assisted development, especially in complex projects, by reducing conflicts and improving code maintainability. Key benefits include reduced code conflicts, enhanced development efficiency, and improved maintainability, making it ideal for large projects that require AI assistance in different code segments.

Target Users :

This tool is designed for software developers and teams, particularly in scenarios where AI assistance is essential for enhancing efficiency and minimizing code conflicts during large project development. It is suitable for large projects that require AI assistance across different code sections, helping developers maintain a clear code structure and reduce conflicts during development.

Total Visits： 492.1M

Top Region： US(19.34%)

Website Views ： 54.1K

Use Cases

In a large web development project, frontend and backend developers use agentic-cursorrules to manage their respective code sections, reducing conflicts during merges.

Database developers utilize this tool to focus on database-layer code without impacting other service layers.

In microservices architecture projects, each service is managed by a dedicated AI agent, utilizing agentic-cursorrules to ensure no code conflicts arise between services.

Features

- Codebase partitioning: Define clear boundaries using YAML configuration and generate separate file trees for each domain.

- Access control: Each agent only receives information pertinent to its specific domain file tree and operates within defined boundaries.

- Conflict prevention: Achieve physical separation through intelligent file tree partitioning, significantly reducing the risk of overlapping modifications.

- Flexible domain configuration: Adapt to different project needs by configuring domains through YAML files.

- Support for up to 4 concurrent agents: Optimize performance and management efficiency in multi-agent environments.

- Markdown-based instruction set: Provide agents with detailed operational instructions and contextual information.

- Context-aware file tree: Agents can comprehend the file tree structure, offering more precise code assistance.

How to Use

1. Clone the project locally: Use the `git clone` command to clone the agentic-cursorrules project to your local directory.

2. Install dependencies: Create and activate a virtual environment in the project directory, then install the required dependencies using `pip install -r requirements.txt`.

3. Configure the .cursorrules file: Copy the .example configuration file and rename it to .cursorrules, adjusting the settings as needed.

4. Define domains: Specify the project's domains and architectural boundaries in the config.yaml file.

5. Run the agent generator: Execute `python main.py` to generate the agent files or use the `--recurring` option for regular updates.

6. Reference agent files: In your development environment, reference the generated agent Markdown files to enable AI agent functionalities for specific domains.