Low Risk

anomaly_detect

Detect anomalies in observation patterns. Alert when metrics deviate significantly from trailing averages. Computes trailing mean and standard deviation for a given metric from the observation_stream, then identifies observations that fall beyond the configured sigma threshold (z-score based anom...

Part of the Trillboards DOOH Advertising server.

anomaly_detect 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 anomaly_detect 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 anomaly_detect 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": {
    "anomaly_detect": {}
  }
}

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

Detect anomalies in observation patterns. Alert when metrics deviate significantly from trailing averages. Computes trailing mean and standard deviation for a given metric from the observation_stream, then identifies observations that fall beyond the configured sigma threshold (z-score based anomaly detection). WHEN TO USE: - Monitoring for unusual audience patterns (sudden spikes or drops in face count) - Detecting equipment anomalies (confidence drops indicating sensor issues) - Identifying unusual commerce or vehicle patterns - Finding outlier moments that may indicate events, incidents, or opportunities RETURNS: - anomalies: Array of anomalous observations with: - observation_id, device_id, venue_type, observed_at - metric_value: The observed value - z_score: How many standard deviations from the mean - direction: 'above' or 'below' the mean - payload: Full observation payload for context - baseline: { mean, stddev, sample_count, lookback_hours } - suggested_next_queries: Follow-up queries to investigate anomalies EXAMPLE: User: "Are there any unusual audience patterns at retail venues?" anomaly_detect({ metric: "face_count", venue_type: "retail", lookback_hours: 24, threshold_sigma: 2.0 }) User: "Detect anomalies in vehicle counts at this screen" anomaly_detect({ metric: "vehicle_count", screen_id: "507f1f77bcf86cd799439011", lookback_hours: 48, threshold_sigma: 2.5 }). It is categorised as a Read tool in the Trillboards DOOH Advertising MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on anomaly_detect? +

Register the Trillboards DOOH Advertising MCP server in PolicyLayer and add a rule for anomaly_detect: 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 anomaly_detect? +

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

Can I rate-limit anomaly_detect? +

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

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

anomaly_detect 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.

Enforce policy on every Trillboards DOOH Advertising tool call.

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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