Uncertainty Meta-Orchestrator
Ki · Reasoning
The Problem
The project's success is uncertain; it depends on various factors without clear classification.
The Operation
The model is directed to identify all sources of uncertainty in the current analysis, data gaps, model limitations, ambiguous premises. Classify each uncertainty as aleatory, epistemic, or structural. Rank uncertainties by their potential impact on the conclusion. Verify that high-impact uncertainties have been explicitly addressed. Constrain confidence intervals to reflect the classified uncertainty levels. If it detects suppress minimize uncertainties project false precision, it halts and corrects.
The Structure
Structurally, this is an accumulate-classify-decide pattern that gathers evidence, categorizes it, then concludes.
If vague hedging is used without classifying whether the uncertainty stems from missing data, model limits, or inherent randomness, uncertainty classification was not performed.
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.