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.
一息もつけない…子どもの付き添い入院 国の支援も進まず なぜ
，详情可参考WPS下载最新地址
Source: Computational Materials Science, Volume 267
近日，lululemon 上新 Define Jacket 夹克系列，该系列采用标志性缝线设计，并选用 Nulu 和 Luon 面料，旨在为日常动态提供柔韧感受与丰富的版型选择。