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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.。业内人士推荐服务器推荐作为进阶阅读
Мощный удар Израиля по Ирану попал на видео09:41
。爱思助手下载最新版本对此有专业解读
"Full of little nooks and crannies where they can roost, big open flight spaces, dry spaces inside, away from the rain, where they can fly around. It is really just an absolutely perfect environment."，详情可参考Line官方版本下载
第一盏灯：位置在左上方 (-1, 2, 4)，负责照亮物体的正面。