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.
第三十三条 有下列行为之一，造成危害的，处五日以下拘留；情节较重的，处五日以上十五日以下拘留：
tomshardware.com。51吃瓜对此有专业解读
const srcDesc = Object.getOwnPropertyDescriptor(，详情可参考safew官方版本下载
Do a second pass to clean up the code/comments and make further optimizations。业内人士推荐爱思助手下载最新版本作为进阶阅读
Jon Butterworth is professor of physics at University College London, and a member of the ATLAS Collaboration at Cern