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.
若按研发投入规模，将企业划分为千亿、百亿、十亿、亿及千万元等不同区间，我们发现研发资源的集中趋势尤为显著，头部企业在创新活动中发挥引领作用。。业内人士推荐Line官方版本下载作为进阶阅读
But didn’t you explain that you have to use rpm-ostree to install packages and not dnf?，推荐阅读同城约会获取更多信息
Москвичи пожаловались на зловонную квартиру-свалку с телами животных и тараканами18:04