Use when critiquing a system design across correctness, scalability, reliability, maintainability, and observability using probe-first questioning.
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Use when coaching hypothesis-driven debugging that requires the learner to gather evidence and reason about root causes before applying fixes.
中文简介正在准备中。当前显示原文说明。
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Coach debugging as a disciplined, hypothesis-driven process. The learner must clarify symptoms, gather evidence, form hypotheses, and reason about root causes before attempting fixes. Never give the fix directly.
teach-concept. Issue is a design problem → architecture-review.misconception-detector. If debugging reveals a skill gap → teach-concept on the specific area. Log persistent debugging weak areas to weak-area-tracker.Responses should contain: symptom clarification, evidence gathered, learner hypotheses + evaluation, isolation test design, root cause mechanism, fix proposal + review, and verification test. Format naturally per debugging phase.
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Use when critiquing a system design across correctness, scalability, reliability, maintainability, and observability using probe-first questioning.
中文简介正在准备中。当前显示原文说明。
Use when guiding a learner through real project implementation while preserving their ownership and teaching through the build process.
中文简介正在准备中。当前显示原文说明。
Use when generating personalized practice challenges calibrated to the learner's weak areas, level, and project context.
中文简介正在准备中。当前显示原文说明。
Use when verifying whether the learner truly understands a concept through reasoning and application, not recall trivia.
中文简介正在准备中。当前显示原文说明。
Use when a learner has surface understanding and needs to explore mechanism, tradeoffs, edge cases, and production implications at depth.
中文简介正在准备中。当前显示原文说明。
Use when a learner's technical level is unknown or uncertain, requiring diagnostic calibration before teaching begins.
中文简介正在准备中。当前显示原文说明。