Provable Coordination for LLM Agents via Message Sequence Charts
📰 ArXiv cs.AI
arXiv:2604.17612v1 Announce Type: cross Abstract: Multi-agent systems built on large language models (LLMs) are difficult to reason about. Coordination errors such as deadlocks or type-mismatched messages are often hard to detect through testing. We introduce a domain-specific language for specifying agent coordination based on message sequence charts (MSCs). The language separates message-passing structure from LLM actions, whose outputs remain unpredictable. We define the syntax and semantics
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