This record as markdown: /tools/openclaw/onboard.md
What onboard does on OpenClaw
AI agents use onboard to create or update resources in OpenClaw, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your OpenClaw environment.
Why onboard is rated Medium
Onboarding typically involves creating new configurations, registering entities, and setting up workspaces — all reversible write operations. It could span into Execute territory if it triggers provisioning scripts, but the description emphasizes 'interactive onboarding' (setup/configuration) rather than running arbitrary code. No destructive or financial signals present.
From the tool's definition 'Interactive onboarding for gateway, workspace, and skills' — onboarding implies initial setup/configuration, which creates or modifies system state (gateway, workspace, skills registration).
Attacks that exploit this kind of access
The rule that runs onboard safely
PolicyLayer is an MCP gateway: it sits between your AI agents and OpenClaw, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For onboard, this is the rule to start with:
onboard stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect OpenClaw, apply this rule, and every onboard call is checked against it from then on.
Questions about onboard
Interactive onboarding for gateway, workspace, and skills. It is categorised as a Write tool in the OpenClaw MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the OpenClaw MCP server in PolicyLayer and add a rule for onboard: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches OpenClaw. Nothing to install.
onboard is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the onboard rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for onboard. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
onboard is provided by the OpenClaw MCP server (openclaw). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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