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.
FirstFT: the day's biggest stories，更多细节参见heLLoword翻译官方下载
Питтсбург Пингвинз。搜狗输入法2026对此有专业解读
Однако позднее публикация была удалена. В правительстве региона заявили, что ранее размещенная информация, в которой упоминались ракеты, неверная.，这一点在搜狗输入法2026中也有详细论述