SkillGraph: Skill-Augmented Reinforcement Learning for Agents via Evolving Skill Graphs

ArXi:2605.12039v1 Announce Type: new Skill libraries enable large language model agents to reuse experience from past interactions, but most existing libraries skills as isolated entries and retrieve them only by semantic similarity. This leads to two key challenges for compositional tasks. Firstly, an agent must identify not only relevant skills but also how they depend on and build upon each other. Secondly, it also makes library maintenance difficult, since the system lacks structural cues for deciding when skills should be merged, split, or removed.