SkillEvo: Self-Renewing Evolution Gradients from Multi-Turn Interaction Feedback
Agent Skills are today either hand-authored or produced in a single LLM generation pass, and consequently possess no closed loop through which they might improve from the interaction failures they actually cause. Recent work does close this loop, but derives its feedback from single-turn question-answering evaluation. The consequence is a sharp asymmetry: once the first round has patched the gaps that a single exchange can reveal, the evolution gradient decays, the defects that surface only acro
Record details
Published: 13 August 2026
Source: arXiv
Category: Research
Topics: Agents & autonomy
Retrieved: 14 August 2026
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ethics.ai (13 August 2026), “SkillEvo: Self-Renewing Evolution Gradients from Multi-Turn Interaction Feedback,” evidence record 19180, https://ethics.ai/record/19180 (originally published by arXiv).
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