SkillSpec: Consensus-Gated Agent Skill Evolution via Representation Specialization
SkillSpec is a two-phase framework for optimizing AI agent skills without changing model weights. Phase I uses consensus-gated evolution to refine knowledge using four editing intents, committing updates only upon peer agreement. Phase II selects an optimal representation—flat, graph, or hybrid—based on trajectory signals like process sensitivity and redundancy sensitivity to structure the learned skill.