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SkillApt: Learning When to Activate Agent Skills from Counterfactual Evidence
Large language model agents increasingly retrieve reusable Skills and inject them into the active context. However, a retrieved Skill can be relevant yet unnecessary, costly, or even harmful in the current execution state. We present SkillApt, a post-retrieval activation framework that decides wheth
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