openclaw-anything_skill

Overview

This skill provides a single, practical control center for installing, configuring, and operating the full OpenClaw ecosystem: Gateway, Channels, Models, Automation, Nodes, and Deployments. It bundles a unified CLI, deployment recipes, connectivity drivers, and debugging utilities to get systems online quickly and keep them healthy. The skill targets both single-machine setups and distributed multi-node orchestrations.

How this skill works

The skill installs and manages OpenClaw components via a unified script interface (bash scripts/openclaw.sh) that exposes commands for setup, service control, Docker/Nix deployment, channel authentication, and advanced agent orchestration. It inspects local environment, scans for models and nodes, validates configuration (openclaw.json), and performs health checks and rollbacks when necessary. Channel and OAuth flows are handled through dedicated login and auth commands; device pairing and browser automation are supported for mobile and headless nodes.

When to use it

• Initial install or full upgrade of an OpenClaw gateway and services
• Connecting or troubleshooting messaging channels (WhatsApp, Telegram, Discord)
• Deploying containerized or Nix-based environments and performing rollbacks
• Managing models, OAuth credentials, and local model scanning
• Scheduling recurring tasks or running multi-agent automation with OpenProse

Best practices

• Run the onboarding wizard (setup) after install to populate openclaw.json and required tokens
• Use the doctor command regularly to detect config drift and permission problems
• Prefer Docker Compose or Nix flakes for repeatable deployments and fast rollbacks
• Store OAuth tokens and model aliases securely; use auth commands to refresh providers
• Run service commands (start/stop/restart/logs) via the unified script instead of interacting directly with process managers

Example use cases

• Quickly provision a gateway on a new server and connect Telegram and Discord channels
• Scan a machine for local models, alias them, and route inference to a selected model
• Set up mobile Nodes with camera and GPS pairing for remote data collection
• Schedule a cron job to run a periodic agent that monitors and reports system health
• Deploy an update via Docker Compose and roll back if the new release fails health checks