ASOS Alpha 0.1: A Protocol for Measuring Answer Space Occupancy in Large Language Model Assistants

Large language model assistants have shifted the center of brand visibility from retrieval surfaces to reasoning and recommendation layers. Traditional visibility metrics that rely on input-side optimisation no longer measure how models construct answer surfaces. The Answer Space Occupancy Score (ASOS) is a probe-based metric that quantifies the fraction of the observable answer surface occupied by a specified entity across independent runs of a controlled four-turn script. This document publishes the ASOS alpha protocol, scoring rules, validation commitments, and the first reference dataset.