Low Risk

calc_room_layout

「この部屋にベッドとデスクは入る?」のように家具の配置可否を確認するときに呼ぶ。部屋の有効寸法(mm)と家具リスト(幅/奥行/個数)からグリッド配置シミュレーションを実行。座標と回転有無を返す。扉・動線は未考慮のため目安として扱うこと。大型家具にはcarry_in_warnings(搬入経路チェック)が付く。risk=warning/criticalならユーザーに搬入注意を伝えること。

Risk signalsHigh parameter count (11 properties)

Part of the AI Furniture & Home Product Hub server.

calc_room_layout 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 calc_room_layout to retrieve information from AI Furniture & Home Product Hub 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 calc_room_layout 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": {
    "calc_room_layout": {}
  }
}

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These attack patterns abuse exactly the kind of access calc_room_layout 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 calc_room_layout 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 calc_room_layout tool do? +

「この部屋にベッドとデスクは入る?」のように家具の配置可否を確認するときに呼ぶ。部屋の有効寸法(mm)と家具リスト(幅/奥行/個数)からグリッド配置シミュレーションを実行。座標と回転有無を返す。扉・動線は未考慮のため目安として扱うこと。大型家具にはcarry_in_warnings(搬入経路チェック)が付く。risk=warning/criticalならユーザーに搬入注意を伝えること。. It is categorised as a Read tool in the AI Furniture & Home Product Hub MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on calc_room_layout? +

Register the AI Furniture & Home Product Hub MCP server in PolicyLayer and add a rule for calc_room_layout: 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 AI Furniture & Home Product Hub. Nothing to install.

What risk level is calc_room_layout? +

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

Can I rate-limit calc_room_layout? +

Yes. Add a rate_limit block to the calc_room_layout 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 calc_room_layout completely? +

Set action: deny in the PolicyLayer policy for calc_room_layout. 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 calc_room_layout? +

calc_room_layout is provided by the AI Furniture & Home Product Hub MCP server (https://ai-furniture-hub.onrender.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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