HEXIS: Compiling Skills into Extended Finite State Machines
Quick summary
arXiv:2609.30123v1 Announce Type: new Abstract: Agent skills provide reusable knowledge and instructions, yet agents must repeatedly infer how to apply them and which operation should follow. This couples task reasoning with control decisions, allowing prescribed steps to be omitted or applied incorrectly. We introduce HEXIS, which compiles agent skills into extended finite state machines that separate knowledge from control flow. Skill knowledge is incorporated into local instructions that guide reasoning and generation within states. The machine records execution progress and intermediate re
Key takeaways
- arXiv:2609.30123v1 Announce Type: new Abstract: Agent skills provide reusable knowledge and instructions, yet agents must repeatedly infer how to apply them and which operation should follow.
- This couples task reasoning with control decisions, allowing prescribed steps to be omitted or applied incorrectly.
- We introduce HEXIS, which compiles agent skills into extended finite state machines that separate knowledge from control flow.
Why it matters
“HEXIS: Compiling Skills into Extended Finite State Machines” should be evaluated beyond branding and benchmark scores. Its practical importance will emerge in task accuracy, latency, unit cost, safety and integration with real workflows.
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