This record as markdown: /tools/openclaw/qa.md
What qa does on OpenClaw
AI agents invoke qa to trigger actions in OpenClaw. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
Why qa is rated High
This tool executes QA scenarios (test automation/code execution) and launches a debugger UI, which are Execute-category operations. The severity is medium because QA debuggers can access internal system state and potentially be abused to inspect sensitive data or trigger unintended test paths, but the blast radius is limited by the fact that it appears to be test-focused rather than production-affecting.
From the tool's definition Tool name 'qa' with description 'Run QA scenarios and launch the private QA debugger UI' indicates execution of predefined test scenarios and launching of a debugging interface.
Attacks that exploit this kind of access
The rule that runs qa 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 qa, this is the rule to start with:
qa stays usable, but rate-capped: a runaway agent can't fire it dozens of times 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 qa call is checked against it from then on.
Questions about qa
Run QA scenarios and launch the private QA debugger UI. It is categorised as a Execute tool in the OpenClaw MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the OpenClaw MCP server in PolicyLayer and add a rule for qa: 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.
qa is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the qa 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 qa. 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.
qa 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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