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.
via telephone line.
，这一点在搜狗输入法下载中也有详细论述
'There's no reason for Discord to comply in advance' with social media age verification laws instead of 'fighting for their users' says EFF expert
Цены на нефть взлетели до максимума за полгода17:55
，这一点在雷电模拟器官方版本下载中也有详细论述
[&:first-child]:overflow-hidden [&:first-child]:max-h-full"。谷歌浏览器【最新下载地址】对此有专业解读
思路：先对 nums2 用单调栈求每个元素的下一个更大值，存入 Map 缓存；再遍历 nums1 直接查 Map 得结果。时间复杂度 O(len1 + len2)。