Low Risk

predict_moment_quality

Predict the VAS (Viewability Attention Score) a specific creative would achieve at a given moment, based on historical data and causal modeling. Uses the CausalPredictionService which: 1. Embeds the moment description to find historically similar moments 2. If >= 5 similar moments exist with the ...

Part of the Trillboards DOOH Advertising server.

predict_moment_quality 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 predict_moment_quality 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 predict_moment_quality 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": {
    "predict_moment_quality": {}
  }
}

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

Predict the VAS (Viewability Attention Score) a specific creative would achieve at a given moment, based on historical data and causal modeling. Uses the CausalPredictionService which: 1. Embeds the moment description to find historically similar moments 2. If >= 5 similar moments exist with the same creative, uses weighted-average prediction 3. If insufficient data, falls back to Gemini generative prediction 4. Always decomposes the prediction into causal factors WHEN TO USE: - Evaluating whether a creative will perform well in a specific context - A/B testing creative placement hypotheses before committing budget - Understanding which causal factors drive VAS for a creative - Comparing expected performance across different moment types RETURNS: - prediction: { predictedVAS (0-1), confidence (0-1), method ('historical'|'model'), sampleSize } - causal_factors: { audienceMatch, contextMatch, attentionState, socialPotential } (each 0-1) - metadata: { creative_id, moment_description } - suggested_next_queries: Follow-up queries EXAMPLE: User: "How would a coffee ad perform at a transit station during morning rush?" predict_moment_quality({ moment_description: "transit venue, morning commute, 12 viewers, high attention, mostly 25-34 age range", creative_id: "coffee-brand-morning-30s" }). 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 predict_moment_quality? +

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

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

Can I rate-limit predict_moment_quality? +

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

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

predict_moment_quality 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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