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.
图②：在山西临汾市襄汾县西贾乡三盛村，果农对苹果园进行疏花作业。
，这一点在51吃瓜中也有详细论述
В России ответили на имитирующие высадку на Украине учения НАТО18:04
「我們作為狗主都只能儘量配合，不想影響到其他人。」，这一点在爱思助手下载最新版本中也有详细论述
Любовь Ширижик (Старший редактор отдела «Силовые структуры»)
return re.sub(r"\s+", " ", node.get_text(" ", strip=True)).strip()，这一点在WPS下载最新地址中也有详细论述