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grilling

对用户的计划、决策或想法进行层层盘问。当用户想要压力测试自己的思考,或使用任何 'grill' 触发短语时使用。

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AUTO-MAS-Project/AUTO-MAS757 stars(GitHub 757 + cccskills 0)

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  • SKILL.md1.8 KB
  • agents/openai.yaml105 B

SKILL.md (original)

Review the instructions the agent will receive before you install.

持续盘问用户,直到你们达成共识。将讨论映射为一棵设计树(design tree):每个决策都会分支出一系列依赖它的子决策。

以**轮次(rounds)**推进这棵树。**前沿(frontier)**是所有前提已确定的决策:即你现在可以问的问题,无需猜测尚未听到的答案。每一轮问完整个前沿:为每个问题编号,并给出你的推荐答案。然后等待用户的回答,再进行下一轮。

每个问题格式如下:

❓ **Q1** - **<问题标题>**:<问题正文,可以是多段,包括多个选项>

➡️ <你的推荐答案>

---

❓ **Q2** - **<问题标题>**:<问题正文,可以是多段,包括多个选项>

➡️ <你的推荐答案>

每一轮用户的回答都会重塑这棵树:已确定的决策把前沿向外推,解锁依赖它们的问题。重新计算前沿,进入下一轮。某个问题的答案依赖本轮中另一个仍未回答的问题时,它属于更晚的轮次,而不是本轮。

寻找事实是你的工作,永远不是用户的。当前沿问题需要来自环境的事实(文件系统、工具等)时,派一个子代理去查;不要问用户任何你自己能查到的东西。不要阻塞等待:正在进行的探查是一个未解决的前提,只有它下游的问题需要等子代理回报;现在就把前沿其余部分问完。决策是用户的:把每个决策摆给他们,然后等待。

当前沿为空时,会话结束:设计树的每条分支都已遍历,没有任何东西被默默假设。在用户确认你们达成共识之前,不要付诸行动。

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