Uncertainty Mapper
Ki · Single Ability
The Problem
This is what breaks. The project's success is certain; we've accounted for all risks, leaving no room for ignorance or unknown factors.
The Operation
The model is directed to identify all claims in the analysis and classify each as known-certain, known-uncertain with quantifiable bounds, or unknown-unknown. For each known-uncertain claim, extract the confidence interval or probability range. Flag any claim presented as certain that lacks sufficient evidence, strip false certainty. Probe for unknown unknowns by asking what categories of information are entirely absent from the model. Map all uncertainties onto the decision, trace which unknowns could flip the conclusion.
The Structure
The reasoning structure is an accumulate-classify-decide pattern that gathers evidence, categorizes it, then concludes.
If the analysis proceeds without separating quantified uncertainties from non-modeled risk factors, epistemic boundary mapping was not established.
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.