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.
Tetrapal: A Palette Triangulator。业内人士推荐搜狗输入法2026作为进阶阅读
進口稅的增加可以由出口企業（即向美國客戶銷售進口產品的公司）和美國消費者共同承擔。。业内人士推荐heLLoword翻译官方下载作为进阶阅读
于是，零跑 A10 登场了。这款小型 SUV，从立项之初就被赋予了极重的战略任务。它不能只是一款及格的代步车，而是必须要成为零跑销量的基石。，详情可参考im钱包官方下载
BEST FOR SINGLE GAME