SkillOpt
Optimize agent skills against measured task batches
An open-source system for optimizing agent skill documents as tunable external artifacts against measured batches of tasks, rather than fine-tuning model weights.
Recent stories
Microsoft open-sourced SkillOpt, a system that treats agent skill documents as tunable artifacts and improves them against measured task batches. It matters because practitioners are already standardizing shared /research, QA, and packageable skills across harnesses, turning skill files into a new optimization surface alongside models.
Microsoft Research released SkillOpt, which optimizes external skill files instead of fine-tuning model weights and reports best-or-tied results across 52 evaluation cells. The method matters because it improved Codex and Claude Code accuracy without extra inference-time calls.