get_audience_forecast

shallow

io.github.snehdhruv/trillboards-dooh · Verify this server

Predict what the audience will look like at a screen at a specific time. WHEN TO USE: - Planning campaigns for specific time slots - Estimating audience composition before buying - Comparing audience at different times of day Uses historical audience data to predict typical audience patterns. RETURNS: - predicted_face_count: Expected number of viewers - predicted_attention: Expected attention score - typical_income: Most common income level at that time - typical_lifestyle: Most common lifestyle segment at that time - confidence: Prediction confidence (0-1, based on sample count) - sample_count: Number of historical data points used EXAMPLE: User: "What's the typical audience at this screen on Monday at 3pm?" get_audience_forecast({ screen_id: "507f1f77bcf86cd799439011", hour: 15, day: 1, lookback_days: 30 })

100.0/100

1 trials · measured 8 days ago

get_audience_forecast scores 100.0/100 on Vouch's measured behaviour index, from 1 real invocation trials against io.github.snehdhruv/trillboards-dooh, measured 25 Aug 2026 under methodology v0.2.0. Every measured component scored 100.

Component breakdown

ComponentWeightValue
Reliability35%not applicable
Schema integrity25%100.0
Failure behaviour15%not applicable
Latency15%not applicable
Concurrency10%not applicable

Tool details

Transport
remote
Credential class
self-provisionable
Input schema
not declared
Output schema
not declared
Side-effect classification
unclassified

Score history

DayScoreTierMethodology
2026-08-25100.0shallowv0.2.0

Probe evidence

ProbeOutcomes
schema_integritypass: 1

Raw request/response logs are not archived yet — the outcome counts above are drawn directly from every recorded trial.

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Vouch score: get_audience_forecast
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get_audience_forecast — Vouch