Select an option from a dropdown/menu using the canonical fallback chain: AX → CDP. Finds the control, opens it, and picks the specified option.
AI agents invoke select_with_fallback 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 triggers UI interactions (opening dropdowns and selecting options) via Accessibility APIs or Chrome DevTools Protocol. It performs active UI manipulation — an external operation whose effects depend on arguments — placing it in the Execute category. Misuse could cause unintended application state changes, but effects are generally reversible, warranting medium severity.
From the tool's definition 'Select an option from a dropdown/menu using the canonical fallback chain: AX → CDP. Finds the control, opens it, and picks the specified option.'
Documented attack patterns abuse exactly the kind of access select_with_fallback 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 select_with_fallback:
{
"version": "1",
"default": "deny",
"tools": {
"select_with_fallback": {
"limits": [
{
"counter": "select_with_fallback_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
} select_with_fallback 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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Select an option from a dropdown/menu using the canonical fallback chain: AX → CDP. Finds the control, opens it, and picks the specified option. 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 select_with_fallback: 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.
select_with_fallback 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 select_with_fallback 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 select_with_fallback. 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.
select_with_fallback 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.