Risk Quantifier
Ki · Reasoning
The Problem
The probability of a data center failure is only 0.1% per year, so we can dismiss it from our risk model, it's not worth planning for such low severity.
The Operation
When activated, the model must enumerate all identified risks for the decision under evaluation. For each risk, compute expected value as probability multiplied by impact magnitude. Do not dismiss low-probability events without computing expected damage, scan for fat-tailed distributions. Rank risks by expected value and verify that tail risks receive disproportionate mitigation. Simulate the mitigation strategy and measure residual risk. The reasoning applies a formal computation: EV = P(risk event) * impact magnitude.
The Structure
Under the hood, the reasoning follows an accumulate-classify-decide pattern that gathers evidence, categorizes it, then concludes.
If risks are listed without probability-times-impact scores or tail risk identification, quantitative risk assessment 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.
Appears in Use Cases