Uncertainty Meta-Orchestrator
Ki · Single Ability
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 · Multi Ability
Synergy Topology
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, these four abilities don't run in sequence. They merge into a single injection where the dependency grounds the reasoning context, the amplifier sharpens the primary's output, and the alternative provides a fallback path if the primary's topology cannot converge. The result is a multi-angle reasoning scaffold that covers failure modes no single ability can reach alone.