Wait for a condition before proceeding. Supports: element visible, text appears, network idle, URL navigation, JS expression truthy. Returns a fresh snapshot after the wait completes.
Risk signalsAccepts freeform code/query input (js)
Part of the Leapfrog server.
Free to start. No card required.
AI agents invoke wait_for to trigger processes or run actions in Leapfrog. 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.
wait_for 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": {
"wait_for": {
"limits": [
{
"counter": "wait_for_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}See the full Leapfrog policy for all 37 tools.
These attack patterns abuse exactly the kind of access wait_for 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.
Wait for a condition before proceeding. Supports: element visible, text appears, network idle, URL navigation, JS expression truthy. Returns a fresh snapshot after the wait completes.. It is categorised as a Execute tool in the Leapfrog MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Leapfrog MCP server in PolicyLayer and add a rule for wait_for: 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 Leapfrog. Nothing to install.
wait_for 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 wait_for 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 wait_for. 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.
wait_for is provided by the Leapfrog MCP server (leapfrog-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 37 Leapfrog tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
4,600+ MCP servers and 31,000+ tools scanned and risk-classified.