Wang et al. address a key inefficiency in self-evolving LLM agents: agents learn in isolation and repeatedly rediscover similar behaviors. SkillX automatically constructs shared skill knowledge bases across agents, enabling cross-agent skill transfer. This tackles the cold-start problem for new agents and reduces redundant exploration across agent populations — a practical architecture for anyone running multiple agent instances.