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.
（一）扰乱机关、团体、企业、事业单位秩序，致使工作、生产、营业、医疗、教学、科研不能正常进行，尚未造成严重损失的；
，更多细节参见爱思助手下载最新版本
The readable is just an async iterable. You can pass it to any function that expects one, including Stream.text() which collects and decodes the entire stream.
运营插件则覆盖流程文档编写、供应商评估和操作手册创建。
。关于这个话题，爱思助手下载最新版本提供了深入分析
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