Accumulate anomalies on a running list — trigger schema…

Accumulate anomalies (observations that don't fit the schema) in a running list and trigger full schema review when the count reaches a pre-defined threshold, rather than treating each anomaly as requiring immediate action.

When This Fires

When an observation doesn't fit your current schema but isn't dramatic enough to warrant immediate review
During any ongoing schema monitoring when individual anomalies feel ambiguous
When you want to balance responsiveness with stability in schema management
Complements Pre-commit to prediction failure thresholds (X out of Y)… (prediction failure thresholds) with an anomaly-based trigger

Common Failure Mode

Explaining away each anomaly individually: "This one was unusual circumstances. That one was an edge case. The other one was bad data." Each explanation is plausible in isolation. But 5 individually-explained anomalies might share a common cause that only becomes visible when you look at the set rather than each one independently.

The Protocol

(1) Create a running anomaly list for each important schema. (2) When an observation doesn't fit → log it: date, what you expected, what happened, which schema was involved. Do NOT investigate or revise the schema yet. (3) Set a threshold (default: 5 anomalies). (4) When the threshold is reached → trigger full schema review. Look at the accumulated anomalies as a set: do they share a pattern? Point to a common cause? Reveal a systematic boundary condition? The set analysis produces insights that individual anomaly analysis cannot.