atomercore/exam2knowledge-skill

🎓 考试2知识 v1.0.0

中文 |英语

“见问题→识别模式→应用方法→获得答案”

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✨ 它的作用

将考试题目转化为结构化、以考试为中心的知识系统。这不是系统性的学习——这培养了即时解决问题的模式识别反射。

适合： 历年试卷、练习题、课程资料→高频考试点→战略学习计划

📁 结构

⚙️ 工作原理

1. 模式识别 — 识别问题类型和认知水平（布鲁姆分类法）
2. 逆向工程 — 提取及分级知识点（[**] 必须掌握到[] 可选）
3. 解决方案模板 — 构建通用步骤+决策规则
4. 错误模式库 — 按类别分类的目录错误（诊断评分标准）
5. 跨问题智能 — 频率排序 + 群组 + 趋势（批处理模式;量化评分标准中的自我检查标准）
6. 考试准备输出 — 优先行动框架（输出模板）

🎯 决策规则

🎓 Exam2Knowledge v1.0.0

中文 | English

“See question → Recognize pattern → Apply method → Get answer”

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✨ What It Does

Transforms exam questions into structured, exam-focused knowledge systems. Not systematic learning — this builds a pattern-recognition reflex for instant problem-solving.

Perfect for: Past exam papers, practice questions, course materials → High-frequency test points → Strategic study plan

📁 Structure

.agents/skills/Exam2Knowledge/
├── SKILL.md                  # Core definition + processing pipeline
├── assets/
│   └── output-template.md    # Standardized output structure
└── references/
    ├── blooms-taxonomy.md    # 6-level cognitive hierarchy
    ├── diagnostic-rubric.md  # 5-category error classification
    └── quantified-rubric.md  # Quantified self-check standards

⚙️ How It Works

1. Pattern Recognition — Identify question type & cognitive level (Bloom’s Taxonomy)
2. Reverse Engineering — Extract & tier knowledge points ([**] Must-Master to [] Optional)
3. Solution Template — Build universal steps + decision rules
4. Error Pattern Library — Catalog mistakes by category (Diagnostic Rubric)
5. Cross-Question Intelligence — Frequency ranking + clusters + trends (batch mode; self-check standards in Quantified Rubric)
6. Exam-Ready Output — Prioritized action framework (Output Template)

🎯 Decision Rules

✨ Key Features

• 🎯 5-step processing pipeline with strict execution order
• 🔀 Conditional logic — output adapts to input type & time constraint
• ✅ Built-in self-check — format, content, consistency, boundary verification
• 📚 Tiered knowledge — [] / [] / [] frequency-based ranking
• 🛡️ Capability boundaries — explicit “can do / cannot do” declaration

📥 Supported Input

• ✅ Single/multiple questions or full exam papers (text format)
• ✅ OCR results from handwritten exams