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This paper introduces Group of Skills (GoSkills), a retrieval method that organizes atomic skills into role-labeled execution contexts to improve agent performance within limited context budgets.
This paper introduces SkillRet, a large-scale benchmark for evaluating skill retrieval in LLM agents, addressing the challenge of selecting relevant skills from large libraries. It provides a dataset of over 17,000 skills and demonstrates that task-specific fine-tuning significantly improves retrieval performance.