Workflow-to-Skill: Skill Creation via Routing-Workflow-Semantics-Attachments Decomposition
Large language model agents increasingly rely on Skills to encode procedural knowledge, yet high-quality Skills remain costly to hand-write. This paper studies automatic Skill construction from heterogeneous interaction evidence, including demonstrations, agent trajectories, tool traces, and execution logs. We argue that trace-to-skill construction is not simple summarization tasks, because traces are fragmented, redundant, and may miss rare but safety-critical behaviors. To address this, we introduce RWSA, a workflow-oriented intermediate representation that decomposes Skills into Workflow structure, execution Semantics, and runtime Attachments, capturing task decomposition, control flow...
| Authors | Yuyang Zhang, Xinyuan Han, Xudong Jiang et al. |
|---|---|
| Primary category | cs.AI |
| Published | 5 June 2026 |
| Last updated at source | 5 June 2026 |
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