The ARC engine evaluates model recall by firing three directional probe types without live search tools: Entity-to-Brand (E2B), Brand-to-Entity (B2E), and Query-to-Brand (Q2B). The extracted entity and brand responses are parsed, deduplicated, and organized using a Matryoshka hierarchy algorithm to aggregate sub-brands into parent entities before calculating a rank-weighted visibility score.