Medium Risk

create_experiment

Create an incrementality experiment for a campaign. Sets up a geo-holdout, ghost ads, or propensity score matching experiment to causally measure DOOH advertising lift. WHEN TO USE: - Setting up a new A/B test before or during a campaign - Defining treatment and control DMAs for geo-holdout tests...

Part of the Trillboards DOOH Advertising server.

create_experiment can modify Trillboards DOOH Advertising data, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents use create_experiment to create or modify resources in Trillboards DOOH Advertising. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.

Without a policy, an AI agent could call create_experiment repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Trillboards DOOH Advertising.

Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "create_experiment": {
      "limits": [
        {
          "counter": "create_experiment_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

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These attack patterns abuse exactly the kind of access create_experiment 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 create_experiment only ever does what you allow.

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Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the create_experiment tool do? +

Create an incrementality experiment for a campaign. Sets up a geo-holdout, ghost ads, or propensity score matching experiment to causally measure DOOH advertising lift. WHEN TO USE: - Setting up a new A/B test before or during a campaign - Defining treatment and control DMAs for geo-holdout tests - Configuring experiment parameters (holdout %, MDE, power) RETURNS: The created experiment object with experiment_id, status, and all parameters. EXAMPLE: create_experiment({ campaign_id: "camp_abc123", experiment_type: "geo_holdout", treatment_dmas: ["501", "504"], control_dmas: ["503", "505"], holdout_pct: 0.15, target_mde: 0.10 }). It is categorised as a Write tool in the Trillboards DOOH Advertising MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on create_experiment? +

Register the Trillboards DOOH Advertising MCP server in PolicyLayer and add a rule for create_experiment: 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 Trillboards DOOH Advertising. Nothing to install.

What risk level is create_experiment? +

create_experiment is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit create_experiment? +

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

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

create_experiment is provided by the Trillboards DOOH Advertising MCP server (https://api.trillboards.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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