HN 提问：是否存在一种针对 NEGATIVESKILLS.md 文件的新兴模式？
3 分•作者: mehmetoguzderin•11 天前
我越来越频繁地遇到这种情况：代理（agents）选择技能的一部分原因在于基于正则表达式的读取，因为将所有内容都放入上下文中效率较低，会忽略负面情况，并导致结果与预期完全相反。就像扩散模型（diffusion models）的负面提示（negative prompts）一样，我认为一个列出明确的反模式（antipattens）和不良版本的“负面技能”（negative-skills）文件，可以使节点更少的执行器（harnesses）表现得更好。
我可能错过了某些进展，但对于最近的模型，是否有公认的或正在形成的处理此问题的方法？
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I am increasingly hitting cases where agents pick something from skills in part due to regex-based reading, since putting them all in context would be less efficient, leave out the negative, and do something exactly opposite of what is intended. Just like negative prompts for diffusion models, I feel like a negative-skills file listing explicit antipatterns and bad versions could enable harnesses with fewer graph nodes to perform better.<p>I might be missing some developments, but is there an accepted/shaping way to do this with recent models?