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.
Трамп высказался о непростом решении по Ирану09:14，这一点在同城约会中也有详细论述
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谷歌近日发布了2025年度热搜排行榜，人工智能技术突破、体育赛事对决与知名公众人物成为备受关注的话题，展现了全球民众当下关注的信息动态、文化趋势与各类关切。