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
Record details
Published: 10 August 2026
Source: HuggingFace Daily Papers
Category: Research
Topics: Agents & autonomy
Retrieved: 12 August 2026
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How to cite this record
ethics.ai (10 August 2026), “SkillZip: Evaluation-Free Skill Compression for Self-Evolving Agents by Discovering Reusable Structure,” evidence record 18378, https://ethics.ai/record/18378 (originally published by HuggingFace Daily Papers).
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