Classify trigger firings as true/false positives for one…

When This Fires

• After deploying any new trigger, before making the first calibration adjustment
• When tempted to adjust a trigger because "it fired at the wrong time today"
• During the initial calibration phase of any behavioral agent (first 2-4 weeks)
• When a trigger feels "off" but you can't articulate whether it's too sensitive or not sensitive enough

Common Failure Mode

Adjusting after every frustrating misfire: "The trigger went off during my meeting — I'll change the conditions." Maybe meetings are a genuine false-positive pattern (change is warranted). Maybe it was a one-time scheduling overlap (change would overfit). You can't distinguish these without a week of data showing whether meeting-time firings are rare or systematic.

The Protocol

(1) For one week, log every trigger firing with a binary classification: TP (true positive — the trigger fired and you should have acted) or FP (false positive — the trigger fired but the action wasn't appropriate for this moment). (2) Also log suspected FN (false negatives — moments the trigger should have fired but didn't). (3) After one week, compute: TP rate = TP / (TP + FP). This is your trigger's precision. (4) If precision ≥ 80% → trigger is well-calibrated. Leave it alone. (5) If precision < 80% → identify the pattern in false positives. What context produced them? Add a guard clause for that context (When false positives exceed 30%, add guard clauses…). (6) If false negatives are common → the trigger is too conservative. Gradually increase sensitivity (Start triggers conservatively — 3-5 daily activations… in reverse).