SkillComposer: Learning to Evolve Agent Skills for Specification and Generalization
Agent skills, which consist of reusable strategies that guide agent reasoning and action, have shown strong potential for improving model capability at inference time. However, current skill construction methods treat the problem as one-shot extraction, overlooking a fundamental tension: a skill tailored to the specific task fails to transfer, while the abstracted skill often provides insufficient guidance. We attribute this fragility to the absence of explicit mechanisms for skill specification and generalization. To address this gap, we introduce SkillComposer, a framework that decomposes skill construction into three learnable operations: create, improve, and merge. Trained via systema...
| Authors | Qi Zhang, Zhaopeng Feng, Xiaonan Shi et al. |
|---|---|
| Primary category | cs.CL |
| Published | 4 June 2026 |
| Last updated at source | 4 June 2026 |
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