Openclaw Architect

Design, configure, debug, and optimize OpenClaw AI agent deployments. Master guide for gateway configuration, openclaw.json settings, model routing and fallb...

This skill appears coherent for auditing and health-checking an OpenClaw deployment. Before installing or running it: 1) Verify OPENCLAW_WORKSPACE points to the intended workspace. 2) Inspect the two included scripts (config_analyzer.py and health_check.py) yourself — they are stdlib Python and readable. 3) Run health checks locally and in a trusted environment because the health_check script executes shell commands and checks files/sockets (Docker, /var/run/docker.sock, tailscale, local HTTP endpoints) and will print local configuration and status to stdout. 4) The analyzer will warn about API keys found in openclaw.json (it reports key locations, not values); if you keep secrets in config files, consider moving them to environment variables or secret storage. 5) Only proceed if you trust the skill source and are comfortable exposing the resulting diagnostic output to the agent or logs where the agent runs.

Type: OpenClaw Skill Name: openclaw-architect Version: 1.0.0 The bundle is a comprehensive administrative and diagnostic tool for OpenClaw deployments, containing scripts for configuration auditing and system health monitoring. It includes scripts like `config_analyzer.py`, which reads the main `openclaw.json` configuration file (containing API keys and bot tokens), and `health_check.py`, which executes shell commands to verify the status of Docker, Tailscale, and system processes. While these risky capabilities (file access to secrets, shell execution, and local network requests) are clearly aligned with the stated purpose of the skill and are implemented with safety considerations (e.g., not printing secret values), they meet the criteria for a suspicious classification due to the broad system access required for their operation.