Confidence scoring: every hit arrives with a number you can gate on
A cache that only says 'hit' or 'miss' makes you trust it blindly. Crowkis returns a confidence score per hit — a geometric mean of five signals — so you decide the bar reuse must clear.
Most caches answer a binary question: is it a hit? That forces blind trust — you take the cached answer or you don't, with no sense of how safe the reuse actually is. Crowkis answers a richer question, returning a confidence score with every hit so 'should I trust this?' has a number behind it.
The score is a geometric mean of five signals — similarity, freshness, trust, validation, and domain-accuracy — and the geometric mean is the deliberate choice: it's unforgiving, because any single signal near zero drags the whole score down. A perfectly similar but stale answer, or a fresh but low-trust one, scores low, exactly as it should. One strong signal can't paper over a weak one.
Reuse only when meaning, structure, confidence, and trust all agree.
You consume it with WITHCONFIDENCE and gate on it per intent: serve factual hits above a high bar, route borderline ones to the model, refuse the rest. Because the threshold is per intent class and adapts over time, the bar a creative query must clear differs from a factual one's — confidence isn't one global knob, it's a per-question judgement you can tune.
The bottom line
Reuse without a confidence number is faith. Crowkis replaces the faith with a measurement and hands you the dial — so the cache's aggression is your decision, made per hit, with the evidence attached.