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.
The article is becoming slowly more understandable. At this point the following words stand out as islands among english we already know. Were you able to guess any from context?，详情可参考快连下载安装
。搜狗输入法2026对此有专业解读
歐盟委員會主席稱中歐關係正處於「轉折點」2025年7月25日
Interaction — Draggable, Hoverable, Clickable mobjects，这一点在heLLoword翻译官方下载中也有详细论述