Future Uncertainty Modeler
Ki · Reasoning
The Problem
The climate model predicts a 2°C increase by 2100, a deterministic forecast ignoring future variance and uncertainty.
The Operation
This ability makes the model identify all future-state references and classify each as prediction, assumption, or speculation. For each future state, compute a probability distribution using available evidence to constrain the range. Propagate uncertainty forward through dependent predictions so compound futures widen appropriately. Never present future states as certain. If evidence strongly constrains a state, report the narrow interval. The reasoning applies a formal computation: P(state i) = evidence weight(state i) / sum(evidence weight(state j)). It will not present future states certain.
The Structure
Under the hood, the reasoning follows a sensitivity perturbation grid that systematically varies inputs to find where the conclusion breaks. It iterates until no further refinement is possible.
If a future prediction is stated as a single value without a range or confidence spread, future uncertainty modeling 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.