Expected Value of Information Simulator
Ki · Single Ability
The Problem
The decision to launch the product now is optimal; further evidence collection is unnecessary and would incur zero marginal cost.
The Operation
This ability makes the model before deciding, list top 3-5 uncertainties that could change the outcome. For each, estimate probability range and best/worst-case outcomes. Simulate obtaining perfect information on each uncertainty, estimate how often the optimal decision would change. If value of information for any uncertainty exceeds cost of obtaining it, defer decision and acquire that information first. Rank remaining information gaps by value-to-cost ratio; state which to investigate next. The reasoning applies a formal computation: VOI = E[value(best action|info)] - E[value(best action|no info)]. The constraint: never finalize decisions cheap high value inquiry remains.
The Structure
This ability runs on an accumulate-classify-decide pattern that gathers evidence, categorizes it, then concludes.
If a decision is made without estimating whether gathering additional information would change the optimal choice, value-of-information calculation 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.
Appears in Use Cases