Wait for a condition: element appears/disappears, text appears, URL changes, window title matches, etc.
AI agents invoke wait_for to trigger actions in ScreenHand. 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.
This is classified as Execute rather than Read because it is not a passive observation tool. It actively waits for and reacts to changes in application/browser state, functioning as a control flow mechanism that orchestrates the automation workflow. While it doesn't directly modify data, it monitors external system state to trigger cascading actions.
From the tool's definition Tool enables waiting for conditions that trigger state changes in applications and browser sessions. The description explicitly lists monitoring for 'element appears/disappears, text appears, URL changes, window title matches'—all observable side effects of…
Documented attack patterns abuse exactly the kind of access wait_for gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and ScreenHand, and nothing reaches the server without passing your rules. This is the rule we recommend for wait_for:
{
"version": "1",
"default": "deny",
"tools": {
"wait_for": {
"limits": [
{
"counter": "wait_for_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}wait_for 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.
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Wait for a condition: element appears/disappears, text appears, URL changes, window title matches, etc. It is categorised as a Execute tool in the ScreenHand MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the ScreenHand 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 ScreenHand. 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 ScreenHand MCP server (manushi4/screenhand). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from ScreenHand, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
89 ScreenHand tools catalogued and risk-classified — across an index of 43,000+ MCP servers.