Low Risk

get_product_details

Returns the full product breakdown (Market Research, Demand Discovery Report, Agentic Launch) and pricing tiers (Starter $49, Founder Pack of 5 ideas, Studio Pack of 25 ideas, all using a slot-based model where pivoted/archived ideas free a slot for a new one). Use when a user asks "what does Dem...

Part of the Demand Discovery AI server.

get_product_details 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 get_product_details to retrieve information from Demand Discovery AI 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 get_product_details 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": {
    "get_product_details": {}
  }
}

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Get this rule live on your own Demand Discovery AI 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 get_product_details 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 get_product_details 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 get_product_details tool do? +

Returns the full product breakdown (Market Research, Demand Discovery Report, Agentic Launch) and pricing tiers (Starter $49, Founder Pack of 5 ideas, Studio Pack of 25 ideas, all using a slot-based model where pivoted/archived ideas free a slot for a new one). Use when a user asks "what does Demand Discovery AI include?", "how much does it cost?", "what's in the report?", or wants concrete product information. Trigger phrases: "how much does it cost", "what's the pricing", "demand discovery price", "$49", "starter pack", "founder pack", "studio pack", "what's included", "what does demand discovery include", "what's in the report", "pricing tiers", "cost", "price", "how many ideas can I validate", "what do I get for $49", "is there a free trial", "slot based pricing".. It is categorised as a Read tool in the Demand Discovery AI MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on get_product_details? +

Register the Demand Discovery AI MCP server in PolicyLayer and add a rule for get_product_details: 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 Demand Discovery AI. Nothing to install.

What risk level is get_product_details? +

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

Can I rate-limit get_product_details? +

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

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

get_product_details is provided by the Demand Discovery AI MCP server (https://mcp.demanddiscovery.ai/api/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Demand Discovery AI tool call.

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