set_target_window
AI agents invoke set_target_window to trigger actions in Openowl. 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.
Based on the server context (desktop automation with 'hands'), setting a target window likely directs subsequent Execute-level actions (clicks, typing) to a specific window. This is an Execute-tier operation as it configures the active target for automation. Description is empty, so confidence is reduced.
From the tool's definition Tool name 'set_target_window' on a server described as providing 'clicking, typing, OCR, window management, accessibility-tree queries, workflow recording' — implies targeting/focusing a specific window for subsequent automation actions.
Documented attack patterns abuse exactly the kind of access set_target_window gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Openowl, and nothing reaches the server without passing your rules. This is the rule we recommend for set_target_window:
{
"version": "1",
"default": "deny",
"tools": {
"set_target_window": {
"limits": [
{
"counter": "set_target_window_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}set_target_window 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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set_target_window. It is categorised as a Execute tool in the Openowl MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Openowl MCP server in PolicyLayer and add a rule for set_target_window: 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 Openowl. Nothing to install.
set_target_window 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 set_target_window 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 set_target_window. 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.
set_target_window is provided by the Openowl MCP server (mihir-kanzariya/openowl). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Openowl, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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40 Openowl tools catalogued and risk-classified — across an index of 43,000+ MCP servers.