INVERSE of simulate_mmc — given an arrival rate, service rate, and a target average wait time, returns the SMALLEST number of servers needed to meet the target. Use this when the user asks 'how many servers do I need?' / 'what staffing keeps wait under N minutes?'. The tool runs a binary search o...
Part of the QueueSim server.
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AI agents call recommend_staffing to retrieve information from QueueSim without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.
Even though recommend_staffing only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.
Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.
{
"version": "1",
"default": "deny",
"tools": {
"recommend_staffing": {}
}
}See the full QueueSim policy for all 11 tools.
These attack patterns abuse exactly the kind of access recommend_staffing gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
INVERSE of simulate_mmc — given an arrival rate, service rate, and a target average wait time, returns the SMALLEST number of servers needed to meet the target. Use this when the user asks 'how many servers do I need?' / 'what staffing keeps wait under N minutes?'. The tool runs a binary search over candidate server counts (up to maxServers, default 50), invoking the simulator for each candidate. Saves Claude from iterating simulate_mmc 3-5 times by hand. If even maxServers servers can't meet the target, the recommendation is null and the response includes the achieved wait so Claude can explain that the target is infeasible at the given load. ANTI-FABRICATION: recommendedServers and achievedAvgWaitMinutes come from real DES runs. Quote them VERBATIM. Do not propose a different number you think 'feels right'; this tool already binary-searches for the minimum that meets the target. If the user asks 'what if c=N?' for a specific N, call simulate_mmc with that c.. It is categorised as a Read tool in the QueueSim MCP Server, which means it retrieves data without modifying state.
Register the QueueSim MCP server in PolicyLayer and add a rule for recommend_staffing: 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 QueueSim. Nothing to install.
recommend_staffing is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the recommend_staffing 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 recommend_staffing. 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.
recommend_staffing is provided by the QueueSim MCP server (https://queuesim.com/mcp/v1). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 11 QueueSim tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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