Generate predictive insights from observation patterns. Predict whether a venue is likely to see increased foot traffic based on current patterns. Uses historical observation_stream data to compute trend analysis via linear regression on time-bucketed metrics. Generates predictions with confidenc...
Part of the Trillboards DOOH Advertising server.
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AI agents call predictive_query to retrieve information from Trillboards DOOH Advertising 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 predictive_query 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.
{
"version": "1",
"default": "deny",
"tools": {
"predictive_query": {}
}
}See the full Trillboards DOOH Advertising policy for all 74 tools.
These attack patterns abuse exactly the kind of access predictive_query gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
Generate predictive insights from observation patterns. Predict whether a venue is likely to see increased foot traffic based on current patterns. Uses historical observation_stream data to compute trend analysis via linear regression on time-bucketed metrics. Generates predictions with confidence intervals based on the observed trend, variance, and sample size. WHEN TO USE: - Predicting future audience patterns at a venue or screen - Forecasting foot traffic trends for campaign planning - Understanding whether metrics are trending up, down, or stable - Making data-driven decisions about inventory and pricing RETURNS: - prediction: The predicted trend and expected values - trend: 'increasing' | 'decreasing' | 'stable' - current_avg: Current average metric value - predicted_avg: Predicted average over the time horizon - change_pct: Expected percentage change - confidence_interval: { lower, upper } bounds - confidence: Overall prediction confidence (0-1) - supporting_data: Recent data points that inform the prediction - data_points: Array of { bucket, avg_value, sample_count } - total_observations: Total observations analyzed - methodology: Description of the prediction approach - suggested_next_queries: Follow-up queries to refine the prediction EXAMPLE: User: "Will this QSR venue see more foot traffic next week?" predictive_query({ question: "Will foot traffic increase at QSR venues?", venue_type: "restaurant_qsr", time_horizon: "7d" }) User: "Predict audience attention trends for this screen" predictive_query({ question: "What will audience attention look like?", screen_id: "507f1f77bcf86cd799439011", time_horizon: "3d" }). It is categorised as a Read tool in the Trillboards DOOH Advertising MCP Server, which means it retrieves data without modifying state.
Register the Trillboards DOOH Advertising MCP server in PolicyLayer and add a rule for predictive_query: 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.
predictive_query is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the predictive_query 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.
Set action: deny in the PolicyLayer policy for predictive_query. 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.
predictive_query 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.
Deterministic rules across all 74 Trillboards DOOH Advertising tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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