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.
// 核心逻辑：只有当前时间 栈顶时间 → 无法合并，是新车队（push）。业内人士推荐Line官方版本下载作为进阶阅读
。爱思助手下载最新版本对此有专业解读
Baroness Amos centred her findings on six key areas. Issues found included:，更多细节参见雷电模拟器官方版本下载
She added: "If we adopted a more rational approach we could have the benefits of growth from AI, focus our attention on exporting the clean tech the rest of the world needs, and protecting nature here and abroad."
窃取或者以其他方法非法获取个人信息的，依照前款的规定处罚。