Query the universal observation stream using natural language or structured filters. Returns multi-modal sensing data (audience, vehicle, environment, commerce) from physical-world observations across the screen network. WHEN TO USE: - Exploring raw observation data from edge AI sensors on screen...
Risk signalsAccepts freeform code/query input (query) · High parameter count (11 properties)
Part of the Trillboards DOOH Advertising server.
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AI agents call query_observations 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 query_observations 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": {
"query_observations": {}
}
}See the full Trillboards DOOH Advertising policy for all 74 tools.
These attack patterns abuse exactly the kind of access query_observations 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.
Query the universal observation stream using natural language or structured filters. Returns multi-modal sensing data (audience, vehicle, environment, commerce) from physical-world observations across the screen network. WHEN TO USE: - Exploring raw observation data from edge AI sensors on screens - Filtering observations by venue type, device, time range, or geography - Getting audience, vehicle, environment, or commerce observation data - Answering natural language questions about what screens are sensing RETURNS: - data: Array of observation objects with device, venue, payload, confidence, model versions - metadata: { observation_count, time_range, coverage_pct, model_versions } - suggested_next_queries: Contextual follow-up queries Each observation includes: - observation_id, device_id, screen_mongo_id, venue_type - observed_at: Timestamp of the observation - observation_family: audience | vehicle | environment | commerce - payload: JSONB with model outputs (face_count, emotion, vehicle_count, etc.) - confidence: Model confidence score (0-1) - evidence_grade: Quality grade of the observation - model_versions: Which ML models produced this data EXAMPLE: User: "Show me audience observations at QSR venues in the last hour" query_observations({ query: "audience observations at QSR venues", filters: { observation_family: ["audience"], venue_type: ["restaurant_qsr"], time_range: { start: "2026-03-16T14:00:00Z", end: "2026-03-16T15:00:00Z" } }, limit: 50 }) User: "What are screens sensing right now?" query_observations({ query: "latest observations from all screens", limit: 20 }). 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 query_observations: 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.
query_observations 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 query_observations 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 query_observations. 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.
query_observations 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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