worker-management

To manage the full lifecycle of AI worker agents, you can use this skill to handle their creation, configuration, monitoring, and resetting. It automates provisioning and automatically stops idle workers to conserve resources.

Yes, you can provision worker agents by specifying their runtime, assigning necessary skills, and setting configurations. This ensures new specialized agents are ready to contribute to projects immediately upon creation.

Worker lifecycle management supports both openclaw for container-based runtimes and copaw for Python-based runtimes. This allows you to choose the appropriate execution environment based on your agent requirements.

You can automatically stop idle worker agents to save resources through built-in idle timeout management. The system monitors running workers and handles the automatic shutdown process without manual intervention.

The best way to integrate worker agents with Matrix and Higress is by using built-in setup features. The skill handles Matrix registration, Higress consumer setup, and AI route authorization for seamless deployment.