Find historically similar audience moments across the screen network using embedding similarity search. Input a natural-language description of the target moment. Moment embeddings are 768-D vectors generated from multi-modal observation data (visual, audio, environmental, social) via the MomentE...
Risk signalsAccepts freeform code/query input (query)
Part of the Trillboards DOOH Advertising server.
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AI agents call find_similar_moments 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 find_similar_moments 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": {
"find_similar_moments": {}
}
}See the full Trillboards DOOH Advertising policy for all 74 tools.
These attack patterns abuse exactly the kind of access find_similar_moments 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.
Find historically similar audience moments across the screen network using embedding similarity search. Input a natural-language description of the target moment. Moment embeddings are 768-D vectors generated from multi-modal observation data (visual, audio, environmental, social) via the MomentEmbeddingService. This tool embeds your query text and finds the closest real-world moments via pgvector cosine similarity. WHEN TO USE: - Searching for historical moments similar to a target scenario - Finding "moments like this one" across different venues/times - Discovering when similar audience compositions or behaviors occurred - Planning ad placements based on past similar contexts RETURNS: - data: Array of matching observations with similarity scores - observation_id, observed_at, venue_type, device_id, screen_mongo_id - payload: full observation data - evidence_grade: quality of observation - similarity: cosine similarity score (0-1, higher = more similar) - metadata: { result_count, embedding_model, min_similarity_threshold } - suggested_next_queries: Follow-up queries EXAMPLE: User: "Find moments with high engagement in evening restaurants with families" find_similar_moments({ query: "evening restaurant venue with families present, high emotional engagement and attention" }) User: "When did we see young adults highly engaged at transit screens?" find_similar_moments({ query: "transit venue morning commute young adults high attention" }). 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 find_similar_moments: 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.
find_similar_moments 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 find_similar_moments 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 find_similar_moments. 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.
find_similar_moments 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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