Execute a specific test case by dispatching an autonomous AI agent. The agent opens a real browser, navigates the web app, follows the test case steps, captures screenshots at each step, and reports pass/fail with detailed findings. Prerequisite: test cases must exist in the suite — generate them...
Part of the Wopee server.
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AI agents invoke wopee_dispatch_agent to trigger processes or run actions in Wopee. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.
wopee_dispatch_agent can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.
Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.
{
"version": "1",
"default": "deny",
"tools": {
"wopee_dispatch_agent": {
"limits": [
{
"counter": "wopee_dispatch_agent_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}See the full Wopee policy for all 11 tools.
These attack patterns abuse exactly the kind of access wopee_dispatch_agent gives an agent. Each links to the full case and the policy that stops it:
Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Execute a specific test case by dispatching an autonomous AI agent. The agent opens a real browser, navigates the web app, follows the test case steps, captures screenshots at each step, and reports pass/fail with detailed findings. Prerequisite: test cases must exist in the suite — generate them first with wopee_generate_artifact (type USER_STORIES_WITH_TEST_CASES). Do NOT use this to analyze or crawl an app — use wopee_dispatch_analysis for that. Side effects: creates execution records and screenshots on the Wopee.io platform. Rate limit: 10 seconds between dispatches per project; concurrent calls auto-retry with exponential backoff. On success, returns executed test case results. On failure (invalid suite/test case ID), returns an error message. Use wopee_fetch_executed_test_cases afterward to get full results.. It is categorised as a Execute tool in the Wopee MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Wopee MCP server in PolicyLayer and add a rule for wopee_dispatch_agent: 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 Wopee. Nothing to install.
wopee_dispatch_agent 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 wopee_dispatch_agent 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 wopee_dispatch_agent. 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.
wopee_dispatch_agent is provided by the Wopee MCP server (wopee-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 11 Wopee tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
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