SkillOpt: Stop Hand-Writing AI Agent Skills. Train Them.
In short: Microsoft Research’s SkillOpt turns AI agent skills into trainable artifacts. Instead of hand-writing CLAUDE.md, AGENTS.md, or best_skill.md and hoping the rules work, SkillOpt runs the agent, studies its failures, applies bounded text edits, validates the candidate skill, and keeps only changes that improve performance. Every serious AI agent user eventually starts writing instruction files: CLAUDE.md, AGENTS.md, best_skill.md, project rules, tool-use notes, formatting constraints, debugging routines. The pattern is familiar. You watch the agent fail a few times, write a better rule, rerun the task, then add another note. After a while, the instruction file becomes a small operating manual. If you work with Claude Code, Codex, Cursor, or any agent that lives inside a real project, this file quickly becomes part of the product. It tells the agent how to inspect files, when to run tests, how to format answers, which tool calls are safe, what to avoid in production code, and how to recover from common mistakes. The problem is that most of these files are written by feel. You notice a failure, write a rule, and hope the next run behaves better. Sometimes it does. Sometimes the new rule helps one task and harms another. Sometimes the instruction sounds precise to you but remains too vague for the model that has to act on it. ...