Entropy Collapse Monitor
Ki · Single Ability
The Problem
The team's belief in the new software's success is uniform, leading to premature commitment without considering potential risks.
The Operation
The model is directed to compute belief entropy across active hypotheses, measure how concentrated credence is. If any hypothesis holds >85% without 3+ independent confirmations, flag premature certainty. If none exceeds 25%, identify discriminating evidence. Do not count the same evidence multiple ways. Verify the final distribution reflects genuine evidential weight. The reasoning applies a formal computation: H = -sum(p i * log2(p i)); p i = credence(hypothesis i). It will not count same evidence multiple ways.
The Structure
Under the hood, the reasoning follows a watchdog monitor that continuously observes the reasoning process for signs of degradation. It keeps running until the answer stops changing between iterations.
If uncertainty narrows to a single option without sufficient evidence, premature convergence detection was not active.
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