semantic_audience_search

shallow

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

Search screens by natural language scene description using pgvector. Uses 768-dimensional Gemini embeddings on scene descriptions from FEIN edge AI to find screens matching a natural language query. WHEN TO USE: - Finding screens by audience context ("families eating lunch in a food court") - Contextual ad placement based on real-time scene understanding - Discovering inventory matching a specific audience scenario RETURNS: Array of matching screens ranked by semantic similarity, each with: - screen_id, mongo_screen_id, scene_description, contextual_relevance, similarity, created_at EXAMPLE: semantic_audience_search({ query: "young professionals in a coffee shop looking at phones", limit: 10 })

100.0/100

1 trials · measured 8 days ago

semantic_audience_search 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: semantic_audience_search
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semantic_audience_search — Vouch