Landmark Salience Mapper
Ki · Single Ability
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 · 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.