Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Manages a distributed cluster of OpenClaw worker nodes across a home lab. Deploys agents to Windows, Mac, and Linux machines via Proxmox, monitors VM and hardware health in real time, and scans project files to identify and resume stalled work.
Combines Proxmox VM management, multi-OS agent deployment, and project state recovery in one skill instead of coordinating separate tools for each.
When to use it
- Deploying a new OpenClaw agent to a freshly added home lab machine
- Checking Proxmox VM health across multiple hosts from a single agent
- Resuming a paused coding project by scanning PROJECTS.md for blockers
- Provisioning new hardware with Docker and Tailscale in one command
- Updating mesh topology after adding or removing nodes from the network
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: identify what's blocking my projects and generate a recovery plan
- 1Run mesh_scan to discover current nodes and update mesh topology
- 2Call mesh_evolve to read MEMORY.md and PROJECTS.md
- 3Identify stalled tasks and blockers across active projects
- 4Generate evolution_plan.json with proposed fixes and resume steps
evolution_plan.json listing each blocked project with a concrete action plan
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.