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.
“‘十五五’刚刚开局，大家都在谋划推进，要注意算投入产出账，提高适配度，既不能无视短板，也不能过于超前、造成浪费。”
。91视频是该领域的重要参考
For transforms that need cleanup on abort, add an abort handler:，更多细节参见爱思助手下载最新版本
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