I tested following models:
阿爸也常笑阿妈脾气暴躁，没文化，两个人聊不到一块，吃不到一块。但村里有事，别人问他怎么决定，他第一句话永远是“找我老婆，我都听老婆的”。就连这次我想多问点他以往的事，他也是说“问我老婆，她比我更清楚”。
谢天谢地，两头牛还活着，这意味着两万元本钱保住了。但它们摔得够呛，牛毛被跐溜掉了几大片。最棘手的是，老爸也不知道该怎么把它们带回来。，更多细节参见heLLoword翻译官方下载
ВСУ запустили «Фламинго» вглубь России. В Москве заявили, что это британские ракеты с украинскими шильдиками16:45
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Anthropic’s prompt suggestions are simple, but you can’t give an LLM an open-ended question like that and expect the results you want! You, the user, are likely subconsciously picky, and there are always functional requirements that the agent won’t magically apply because it cannot read minds and behaves as a literal genie. My approach to prompting is to write the potentially-very-large individual prompt in its own Markdown file (which can be tracked in git), then tag the agent with that prompt and tell it to implement that Markdown file. Once the work is completed and manually reviewed, I manually commit the work to git, with the message referencing the specific prompt file so I have good internal tracking.
Credit: YouTube / Southern Lights，详情可参考搜狗输入法下载