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  "text": "New research from Microsoft Research\n\nI see a lot of AI engineers handwriting agent skill docs and hope they generalize.\n\nProbably not optimal. This works show why.\n\nIt treats the skill doc as a trainable external state of a frozen agent instead.\n\nIt introduces SkillOpt, where an optimizer model makes validation-gated edits to the skill file. It adds, deletes, or replaces instructions, with a textual learning rate that controls how aggressively each round rewrites the doc. The agent itself never changes.\n\nSkillOpt is best or tied on all 52 (model, benchmark, harness) cells.\n\nOn GPT-5.5 it adds 23.5 points in direct chat, 24.8 with Codex, and 19.1 with Claude Code over no skill. It beats human-written skills, TextGrad, GEPA, and EvoSkill, carries zero extra inference-time cost, and the learned skills transfer across models and harnesses.\n\nPaper: https://t.co/mNgTmmT32U\n\nLearn to build effective AI agents in our academy: https://t.co/1e8RZKs4uX",
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