Register a dialog watch rule: when a dialog matching the pattern appears, auto-execute an action.
AI agents invoke watch_dialog 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 registers an automated trigger that executes actions autonomously whenever a matching dialog appears. It creates persistent, automated execution rules that can perform UI interactions without further human approval, representing a significant Execute-category risk with high blast radius since a misconfigured rule could auto-dismiss security dialogs, confirmation prompts, or permission requests.
From the tool's definition 'auto-execute an action' when a dialog matching the pattern appears
Documented attack patterns abuse exactly the kind of access watch_dialog 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 watch_dialog:
{
"version": "1",
"default": "deny",
"tools": {
"watch_dialog": {
"limits": [
{
"counter": "watch_dialog_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}watch_dialog 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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Register a dialog watch rule: when a dialog matching the pattern appears, auto-execute an action. 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 watch_dialog: 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.
watch_dialog 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 watch_dialog 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 watch_dialog. 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.
watch_dialog 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.