Future Uncertainty Modeler
Ki · Single Ability
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 · 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.
Appears in Use Cases