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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.，推荐阅读WPS下载最新地址获取更多信息
居民选举委员会成员退出居民选举委员会或者因其他原因出缺的，按照原推选结果依次递补，也可以另行推选。。业内人士推荐雷电模拟器官方版本下载作为进阶阅读
Daventry Community Larder，推荐阅读同城约会获取更多信息
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