Wait until a condition is met on screen: text appears, text disappears, or element becomes available. Polls at intervals using the fallback chain.
AI agents invoke wait_for_state 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 tool does not passively read data; instead, it executes a polling operation that manipulates control flow in an automation sequence. An agent could misuse it to wait indefinitely, consume resources, or synchronize malicious actions with screen changes. It falls under Execute rather than Read because it actively triggers conditional branching in workflows and interacts with the UI state machine.
From the tool's definition The tool 'wait_for_state' actively polls screen state and blocks execution until conditions are met. While framed as a utility, it controls timing and conditional logic flow in automated workflows, similar to how 'execute_script' or triggering external…
Documented attack patterns abuse exactly the kind of access wait_for_state 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_state:
{
"version": "1",
"default": "deny",
"tools": {
"wait_for_state": {
"limits": [
{
"counter": "wait_for_state_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}wait_for_state 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 until a condition is met on screen: text appears, text disappears, or element becomes available. Polls at intervals using the fallback chain. 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_state: 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_state 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_state 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_state. 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_state 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.
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89 ScreenHand tools catalogued and risk-classified — across an index of 43,000+ MCP servers.