semantic_search

shallow

io.github.CumulativeWebInc/cwi-discovery-engine · Verify this server

Semantic search over the CWI catalog embedding matrix: cosine similarity against 384-dim bge-small-en-v1.5 vectors (55 tracks). The query is embedded at request time with Workers AI @cf/baai/bge-small-en-v1.5 — the same model that produced the matrix, so catalog and query vectors are directly cosine-comparable. No inference needed on your side; just call this tool. FALLBACK (documented, never silent): if the Workers AI [ai] binding is unavailable at runtime, the tool DEGRADES to keyword scoring over the matrix text fields and says so in its response (method "fallback:keyword", plus a fallback_note). Fallback scores are keyword weights (title 3x, genre/descriptor 2x, mood 1x) — they are NOT cosine similarity and are never presented as semantic scores.

100.0/100

1 trials · measured 2 days ago

semantic_search scores 100.0/100 on Vouch's measured behaviour index, from 1 real invocation trials against io.github.CumulativeWebInc/cwi-discovery-engine, measured 6 Oct 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
open
Input schema
not declared
Output schema
not declared
Side-effect classification
unclassified

Score history

DayScoreTierMethodology
2026-10-06100.0shallowv0.2.0

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_search
[![Vouch score](https://vouch.tools/api/tools/af5577db-f037-413e-b6a8-9e684181549e/badge.svg)](https://vouch.tools/tools/af5577db-f037-413e-b6a8-9e684181549e)