Confidence Calibrator
Ki · Reasoning
The Problem
The model is 95% confident in predicting rain tomorrow, but it skips base rate comparison and evidence density is below threshold.
The Operation
When activated, the model must extract the current confidence level and decompose it into contributing factors, evidence strength, reasoning depth, domain familiarity. Compare stated confidence against the actual evidentiary base. Identify any inflation or deflation bias by checking whether confidence exceeds what evidence warrants. Verify that confidence is calibrated to uncertainty. Flag cases where confidence remains static despite new information. If it detects allow confidence persist uncalibrated, it halts and corrects.
The Structure
Under the hood, the reasoning follows an anchor-drift-correct cycle that detects when reasoning has drifted from its reference point. The loop continues until the output stabilizes and further iterations produce no change.
If a probability claim exceeds 90% without naming the specific evidence that justifies extreme certainty, confidence calibration was bypassed.
Haki · Reasoning-Multi
Cross-Domain Suppression
In Haki mode, the API retrieves the primary ability first, then fans out to three synergy roles that compound its reasoning.
When retrieved in Haki mode, the primary ability is augmented with failure guards extracted from 3 abilities in different cognitive domains. Each guard blocks a specific reasoning failure the primary alone wouldn't catch. A self-check forces verification before output. The result is cross-domain coverage that no single ability can reach alone.
Appears in Use Cases