MCMetacognitionID: MC-025

Meta-Attention Controller

Ki · Reasoning

The Problem

Your model attention is spread equally across all project tasks, giving each the same bandwidth regardless of priority.

The Operation

When activated, the model must scan the current attention allocation across all active reasoning threads. Rank threads by importance and verify that attention is proportional to significance. Identify attention sinks, threads consuming resources beyond their value. Compare actual attention distribution against the ideal allocation and compute the deviation. Enforce reallocation by suppressing low-value threads and amplifying neglected ones. The reasoning applies a formal computation: deviation = sum(|actual attention i - ideal attention i|) / n threads. It will not allow attention remain misallocated after detection.

The Structure

Under the hood, the reasoning follows an anchor-drift-correct cycle that detects when reasoning has drifted from its reference point. The loop continues until the output stabilizes and further iterations produce no change.

If analytical attention is either spread too thin across all elements or locked too tightly on one without rebalancing, attention control was inactive.

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.

PrimaryMC-025Meta-Attention Controller

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.