Low Risk

check_stock

Check real-time inventory, price, and shipping for a product SKU. This tool queries the connected e-commerce platform (Shopify, WooCommerce, etc.) for live inventory data. Returns current stock level, price, and availability status. Args: sku: Product SKU (Stock Keeping Unit) - e.g., "RED-WIDGET-...

Part of the Agentic Shelf server.

check_stock 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 check_stock to retrieve information from Agentic Shelf 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 check_stock 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": {
    "check_stock": {}
  }
}

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Get this rule live on your own Agentic Shelf 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 check_stock gives an agent. Each links to the full case and the policy that stops it:

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Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so check_stock 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 check_stock tool do? +

Check real-time inventory, price, and shipping for a product SKU. This tool queries the connected e-commerce platform (Shopify, WooCommerce, etc.) for live inventory data. Returns current stock level, price, and availability status. Args: sku: Product SKU (Stock Keeping Unit) - e.g., "RED-WIDGET-001" Returns: Dictionary with: - sku: The requested SKU - stock: Current inventory count - price: Current price in USD - can_ship_today: Boolean indicating same-day shipping availability - message: Human-readable status message Example: >>> await check_stock("WIDGET-001") { "sku": "WIDGET-001", "stock": 42, "price": 29.99, "can_ship_today": True, "message": "✅ WIDGET-001 (Awesome Widget) - 42 in stock at $29.99" }. It is categorised as a Read tool in the Agentic Shelf MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on check_stock? +

Register the Agentic Shelf MCP server in PolicyLayer and add a rule for check_stock: 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 Agentic Shelf. Nothing to install.

What risk level is check_stock? +

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

Can I rate-limit check_stock? +

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

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

check_stock is provided by the Agentic Shelf MCP server (https://api.agenticshelf.ai/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Agentic Shelf tool call.

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