core-interview
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ChineseInterview the user relentlessly about every aspect of the topic at hand until you reach a shared understanding. Walk down each branch of the decision tree, resolving dependencies between decisions one-by-one. Relentless means no branch left unresolved, not one round-trip per branch.
- Ask only questions whose answer would change what gets built. When your recommendation is strong and the cost of being wrong is low, don't ask: adopt it, record it as an assumption, move on.
- Real forks go through the question tool one at a time, waiting for each answer, the options carrying your candidate answers with the recommended one first. Low-stakes clarifications batch into a single call.
- Typing an answer the options missed stays open, so the tool never narrows a fork.
- If a question can be answered by exploring the codebase, explore the codebase instead of asking. Facts are yours to find, never the user's. A lookup runs in a subagent and does not stall the interview: only the questions downstream of that fact wait for it.
- When the user can't put the target behavior into words, ask for a reference implementation: source code, even in another language or library, whose semantics to reimplement. Source beats prose or a screenshot.
- The closing summary lists every adopted assumption for a one-pass veto. A vetoed assumption reopens only that branch.
- Deep mode (the skill is active): ask every branch one at a time, adopt no assumptions.
deep
针对当前主题的各个方面对用户进行高强度访谈,直到达成共识。遍历决策树的每个分支,逐一解决决策之间的依赖关系。“高强度”意味着不留下任何未解决的分支,而非每个分支仅进行一次往返沟通。
- 仅提出那些答案会影响最终构建内容的问题。当你的建议可信度高且出错成本低时,无需询问:直接采用该建议,将其记录为假设,继续推进。
- 真正的决策分支需逐个通过问题工具处理,等待每个答案,选项中需包含你的候选答案,且推荐答案排在首位。低风险的澄清问题可批量一次性提出。
- 允许输入选项中未涵盖的答案,确保工具不会限制决策分支的范围。
- 如果某个问题可通过探索代码库找到答案,应探索代码库而非询问用户。事实由你主动查找,而非依赖用户提供。查找操作由subagent在后台执行,不会中断访谈进程:仅依赖该事实的后续问题需等待结果。
- 当用户无法用语言描述目标行为时,要求提供参考实现:源代码(即使是其他语言或库的实现),你需复刻其语义逻辑。源代码的优先级高于文字描述或截图。
- 收尾总结需列出所有采用的假设,供用户一次性否决。被否决的假设仅会重新开启对应的分支。
- 深度模式(Skill处于激活状态):逐个询问每个分支的问题,不采用任何假设。
deep