摘要：AI 购物助手正日益改变消费者发现商品的路径，因此迫切需要能够支持卖家侧竞争决策的工具。我们提出了一套多智能体 AI 系统，用于自动化衡量 LLM 中介电商中的竞争可见度并诊断根本原因。该系统引入 Agentic Share-of-Search（ASoS）作为决策目标，在领先的 AI 平台上部署查询智能体，并利用基于 ReAct 的诊断智能体推荐按优先级排序的商品运营干预措施。一项包含 100 次试验的消融研究以该原型的可行性评估形式呈现，结果显示，该智能体在 39% 的试验中恢复了被消融的信号（95% CI：30.0% - 48.8%，为随机水平的 5.5 倍）；在高相关性消融样本中，这一比例升至 63.9%。

Abstract:AI shopping assistants increasingly redirect consumer discovery, creating an urgent need for tools that support seller-side competitive decision-making. We present a multi-agent AI system that automates competitive visibility measurement and root cause diagnosis in LLM-mediated ecommerce. The system introduces Agentic Share-of-Search (ASoS) as the decision target, deploys query agents across leading AI platforms, and uses a ReAct-based diagnostic agent to recommend prioritized merchandising interventions. A 100-trial ablation study, presented as a feasibility evaluation of this prototype, shows the agent recovers the ablated signal in 39% of trials (95% CI: 30.0% - 48.8%, 5.5x over chance), rising to 63.9% among high-correlation ablations.