Add random delays and timing variations
AI agents invoke randomize_timing to trigger actions in Pydoll. 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 executes timing control logic within an automated browser session. It affects the execution behavior of automation scripts by injecting randomized delays, commonly used to evade bot detection. While not directly destructive or financial, it actively modifies the runtime behavior of ongoing automation, placing it in Execute.
From the tool's definition 'Add random delays and timing variations' — introduces programmatic timing manipulation into browser automation flows
Documented attack patterns abuse exactly the kind of access randomize_timing gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Pydoll, and nothing reaches the server without passing your rules. This is the rule we recommend for randomize_timing:
{
"version": "1",
"default": "deny",
"tools": {
"randomize_timing": {
"limits": [
{
"counter": "randomize_timing_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}randomize_timing 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.
Free to start. No card required.
Add random delays and timing variations. It is categorised as a Execute tool in the Pydoll MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Pydoll MCP server in PolicyLayer and add a rule for randomize_timing: 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 Pydoll. Nothing to install.
randomize_timing 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 randomize_timing 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 randomize_timing. 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.
randomize_timing is provided by the Pydoll MCP server (jinsongroh/pydoll-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Pydoll, 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.
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