AI RESEARCH
AgensFlow: A Coordination-Policy Substrate for Multi-Agent Systems
arXiv CS.AI
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ArXi:2605.27466v1 Announce Type: cross Multi-agent systems built on large language models (LLMs) require many coordination choices that are difficult to fix a priori: which skill protocol to invoke, which agent role should perform a subtask, which model to bind to each role, how roles should interact, when to use retrieval or verification, and when to omit a step entirely. These choices interact with task regime and operational constraints, so static pipelines and one-off model comparisons provide only a limited view of the design space.