SkillZip: Evaluation-Free Skill Compression for Self-Evolving Agents by Discovering Reusable Structure

Self-evolving agents accumulate reusable skills by appending successful procedures and failure fixes. Over time, the same requirement is often restated in several branches, examples, and warnings, while common action sequences are copied rather than reused. The resulting skill becomes expensive to inject and difficult to maintain. Generic prompt compression is ill-suited to this setting because a skill is not a flat passage: its name and description define when it applies, its workflow controls

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ethics.ai (11 August 2026), “SkillZip: Evaluation-Free Skill Compression for Self-Evolving Agents by Discovering Reusable Structure,” evidence record 18652, https://ethics.ai/record/18652 (originally published by arXiv cs.AI).

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