Landmark Salience Mapper
Ki · Reasoning
The Problem
In the featureless desert, all points seem equal, leading to disorientation risk due to anchor deficiency.
The Operation
Under this ability, the model must scan the spatial description and extract all candidate landmarks including permanent structures and distinctive boundaries. Rank each candidate by salience using persistence, distinctiveness, and visibility as criteria. Filter out transient or ambiguous features that could shift between observations. Verify that selected landmarks provide adequate coverage. Map relationships between landmarks to build a stable reference network. It will not treat features equally reliable.
The Structure
Under the hood, the reasoning follows a convergence funnel where multiple candidates enter, evidence narrows them, and only survivors exit. Execution repeats until the reasoning locks onto a stable conclusion.
If the spatial analysis lacks distinguishing reference landmarks to anchor orientation and navigation, salience mapping was omitted.
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.