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.
Гангстер одним ударом расправился с туристом в Таиланде и попал на видео18:08
，这一点在91视频中也有详细论述
В Финляндии предупредили об опасном шаге ЕС против России09:28，推荐阅读Safew下载获取更多信息
值得留意的是，政府同時在問卷指出，大埔宏福苑援助基金總額約43億元，扣除已動用及預留的援助項目，剩餘約20多億元，並稱「意味政府需要投入公帑去補貼收購業權。」該基金目前總額增至約45億，事實上政府投入三億元作為起動資金，其餘款項經公眾籌款取得。