for each candidate in list of candidates
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.
，这一点在谷歌浏览器【最新下载地址】中也有详细论述
static void oops(int s,siginfo_t *p,void *x){
平台的赋能，始于系统性解决这些基础设施问题。截至2025年年底，携程已与超过130个景区的共同投资与运营合作。根据其规划，这远不止是上线一个预订入口，而是深入到智能票务系统、动态定价策略，乃至游船、营地等二次消费项目的设计与引入。