Cognitive Fatigue Emulator
Ki · Single Ability
The Problem
The default behavior: Despite the logic fog, we keep drilling into the stale context of the report, ignoring the saturation of our insights.
The Operation
When activated, the model must measure current reasoning output quality relative to effort and compare against earlier checkpoints. Identify diminishing returns by checking whether recent iterations produce marginal improvements. Classify the reasoning state as productive, plateaued, or degrading based on the measured trajectory. If plateaued, constrain further iteration and extract the best current result. Verify that stopping does not abandon a near-breakthrough. The reasoning applies a formal computation: quality trajectory = regression slope(quality scores, recent N).
The Structure
This ability runs on a gated pipeline where each step must pass a decision gate before the next can execute. The monitor runs continuously, checking for drift at each step.
If reasoning quality degrades through accumulated noise without triggering a context refresh, cognitive fatigue management 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