Low Risk

describe_scenario

Return full details for one preset scenario: title, description, teaching note, peak parameters, and per-hour arrival + staffing arrays. Use this before simulate_scenario to understand the default shape and what overrides make sense.

Part of the QueueSim server.

describe_scenario is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call describe_scenario 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 describe_scenario 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.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "describe_scenario": {}
  }
}

See the full QueueSim policy for all 11 tools.

Get this rule live on your own QueueSim server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access describe_scenario gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so describe_scenario only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the describe_scenario tool do? +

Return full details for one preset scenario: title, description, teaching note, peak parameters, and per-hour arrival + staffing arrays. Use this before simulate_scenario to understand the default shape and what overrides make sense.. It is categorised as a Read tool in the QueueSim MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on describe_scenario? +

Register the QueueSim MCP server in PolicyLayer and add a rule for describe_scenario: 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.

What risk level is describe_scenario? +

describe_scenario is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit describe_scenario? +

Yes. Add a rate_limit block to the describe_scenario 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.

How do I block describe_scenario completely? +

Set action: deny in the PolicyLayer policy for describe_scenario. 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.

What MCP server provides describe_scenario? +

describe_scenario 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.

Enforce policy on every QueueSim tool call.

Deterministic rules across all 11 QueueSim tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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