Multi-Agent Synergy Optimizer
Ki · Single Ability
The Problem
The isolated analysis of each bird's flight pattern explains the swarm's emergent behavior.
The Operation
The cognitive operation intervenes. When multiple agents, actors, or components interact, ask: what behavior emerges from their interaction that none would produce alone? Identify cooperation patterns, where individual actions align to produce collective benefit. Identify conflict patterns, where individual optimization undermines collective outcomes. Check for emergent properties: is the system behavior predictable from individual behaviors, or does something qualitatively new appear at the collective level? Suppress the tendency to analyze multi-actor systems by analyzing actors in isolation and then summing the results. Isolated analysis birds flight pattern explains swarms is rejected.
The Structure
Structurally, this is an emergence detector that watches for new patterns arising from the interaction of components. Processing continues until the input space is covered or stagnation is detected.
If multi-agent behavior is predicted from individual properties alone without modeling their interactions, emergence reasoning was bypassed.
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