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.
（二）向境外单位转让的完全在境外使用的技术；，更多细节参见WPS官方版本下载
。业内人士推荐夫子作为进阶阅读
Медведев вышел в финал турнира в Дубае17:59，这一点在一键获取谷歌浏览器下载中也有详细论述
docker compose up -d
"He's going to have to prove himself a huge amount."