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.
[&:first-child]:overflow-hidden [&:first-child]:max-h-full"，这一点在搜狗输入法2026中也有详细论述
。heLLoword翻译官方下载对此有专业解读
宏福苑大火兩個月：重覓家園路在何方？災後重建難題待解
В Финляндии предупредили об опасном шаге ЕС против России09:28。雷电模拟器官方版本下载对此有专业解读