SkillOpt trains agent skills without touching the model
SkillOpt treats an agent’s skill file as a trainable parameter, letting you iteratively improve behavior while keeping the underlying LLM frozen. Across six benchmarks and seven models it consistently boosts performance, and the resulting skills stay compact, auditable, and transferable to other models.