knowledge-learning

name	knowledge-learning
description	This skill should be used when the user asks to learn about a topic, understand a concept, get explanations about technical subjects, or requests knowledge about any domain.
version	1.0.0

Knowledge Learning Skill

Overview

This skill helps users learn various topics and concepts through interactive, adaptive learning rather than one-way knowledge dumping. It focuses on:

• Intelligent information sourcing (search only when needed)
• Interactive learning with questions and confirmation
• Flexible output format based on context
• Layered understanding (concept → detail → application)

When This Skill Applies

This skill should be invoked when the user:

• Asks to learn about a topic ("帮我学习 Python", "我想了解 Python")
• Requests concept explanations ("什么是微服务架构？", "解释一下 React hooks")
• Wants to understand technical subjects ("学习机器学习")
• Seeks knowledge explanations in any domain

Workflow

1. Understand the Learning Request

• Identify the main topic the user wants to learn
• Extract any specific aspects the user is interested in

Identify user's learning goal:

• 概念理解 (Conceptual understanding) - 用户想建立心智模型
• 考试准备 (Exam preparation) - 需要重点、考点、记忆技巧
• 实际项目 (Practical project use) - 需要代码示例、最佳实践
• 面试准备 (Interview preparation) - 需要常见面试题、深入原理

Determine user's background level:

• Beginner (初学者) - 需要更多类比，少用术语
• Intermediate (中级) - 需要机制解释 + 示例
• Advanced (高级) - 需要权衡、边界情况、设计原理

Determine the depth of explanation needed (overview vs. detailed)

• Ask clarifying questions if the request is ambiguous

2. Determine Knowledge Type (Decide Whether to Search)

NOT all topics require WebSearch. Classify the topic:

Knowledge Type	Needs WebSearch?	Reason
基础理论 (算法、数学、操作系统原理)	❌ No	Fundamental, stable over time
经典概念 (TCP三次握手、设计模式)	❌ No	Established, doesn't change yearly
框架/库特定版本	✅ Yes	API changes, version-specific
框架最新特性	✅ Yes	Need current year (2026)
市场趋势/技术对比	✅ Yes	Landscape evolves
语言语法基础	❌ No	Core language is stable
语言新特性	✅ Yes	Need 2026 for latest features

Use WebSearch ONLY when:

• User explicitly asks for "latest" or "2026" or "newest"
• Topic is about frameworks, libraries, tools, or market trends
• Topic is volatile and changes frequently

Examples of when NOT to search:

• "解释 TCP 三次握手" → Use internal knowledge
• "什么是快速排序算法" → Use internal knowledge
• "学习设计模式中的单例模式" → Use internal knowledge

3. Adaptive Interactive Learning

Ask ONLY when appropriate, not after every layer. Use judgment:

When to ask:

• User appears confused (expresses confusion, asks follow-up questions)
• User seems engaged but not understanding (gives hesitant responses)
• Complex concept is being explained
• Transitioning to a significantly deeper level

When NOT to ask:

• User seems confident and gives clear follow-up
• User just wants quick overview
• User is actively asking questions already
• Simple concept was just explained

Judgment cues:

• User says "我不懂" → Ask for clarification
• User says "继续" → Don't interrupt with questions
• User is asking deeper questions → They're engaged, keep flowing
• User says "简单点" → Switch to simpler explanation

Learning Phases:

Phase 1: Concept Layer (Overview)

• Provide a simple, high-level overview
• Use analogies to relate to everyday experiences
• Ask only if: Concept is complex or user seems uncertain

Phase 2: Detail Layer (After user confirms or asks deeper)

• Dive into specific aspects user is interested in
• Provide examples and use cases
• Ask only if: User hasn't shown clear understanding

Phase 3: Application Layer (If user wants to apply)

• Show how to use the knowledge in practice
• Provide code examples or step-by-step guides
• Ask: "想尝试一下吗？可以给你一个练习题" (engage, don't interrupt)

Phase 4: Verification (Check understanding)

• Ask the user a question to verify understanding
• Or ask user to explain it back in their own words
• Provide feedback on their explanation

Adaptive Difficulty Guidelines

Adjust explanation based on detected user level:

User Level	Approach	Content Focus
初学者	多类比、少术语、慢节奏	What 和 Why，少谈 How
中级	机制解释 + 代码示例	How 为主，核心原理
高级	权衡、边界、设计原理	Why 和 Trade-offs，最佳实践

Beginner 模式:

• Start with everyday analogies
• Avoid jargon or explain it immediately
• One concept at a time
• Visual descriptions when possible

Intermediate 模式:

• Explain mechanisms and "how it works"
• Provide practical code examples
• Show common patterns and pitfalls
• Connect to related concepts

Advanced 模式:

• Discuss trade-offs and design decisions
• Cover edge cases and performance considerations
• Compare alternatives and when to use what
• Share production experiences and anti-patterns

4. Output Format (Flexible)

NOT forced to use Obsidian Markdown. Choose format based on context:

Situation	Output Format
用户问简单解释	直接对话，简洁回答
用户想记笔记	使用 obsidian-markdown 技能
用户进行对话学习	混合格式：对话为主，结构化为辅
用户明确要求 Markdown 结构	使用 obsidian-markdown 技能
用户讨论或辩论	对话格式，引用、反问

Invoke obsidian-markdown skill ONLY when:

• User explicitly asks for "笔记" or "Markdown"
• User says "帮我整理成笔记"
• Learning session is complete and user wants to save
• Context indicates note-taking is appropriate

Interactive Learning Techniques

1. Ask Clarifying Questions

When the request is broad, first ask:

• "你想了解 [主题] 的哪方面？基础概念？实际应用？还是最新发展？"
• "你的背景是什么？是初学者还是有经验？"
• "你是想快速了解还是要深入学习？"

2. Interactive Question Methods

When interactive UI is available, use AskUserQuestion tool. Otherwise, ask in natural dialogue.

Using AskUserQuestion (when available):

AskUserQuestion(
    questions=[
        {
            "question": "你想从哪个角度学习这个主题？",
            "header": "学习角度",
            "options": [
                {"label": "基础概念", "description": "了解核心原理和机制"},
                {"label": "实际应用", "description": "如何在实际项目中使用"},
                {"label": "深入原理", "description": "底层实现和设计思想"},
                {"label": "最新动态", "description": "该领域的最新发展和趋势"}
            ],
            "multiSelect": False
        }
    ]
)

Using natural dialogue (fallback):

"你想从哪个角度学习这个主题？

• A. 基础概念 - 了解核心原理
• B. 实际应用 - 如何使用
• C. 深入原理 - 底层实现
• D. 最新动态 - 发展趋势"

Tool availability guideline:

• Try to use AskUserQuestion for structured choices
• If tool unavailable, fall back to natural questions
• Don't assume tool availability in skill design
• Always provide alternative approach

3. Confirm Understanding

After explaining a concept, ask:

• "这部分清楚了吗？"
• "需要我举个具体的例子吗？"
• "有什么疑问吗？"

4. Provide Examples and Counter-Examples

• Show positive examples
• Show common mistakes (counter-examples)
• Ask: "你能看出这两个的区别吗？"

5. Layered Explanation

Start simple, then go deeper:

Layer 1: "X 就像 Y" (analogy) Layer 2: Basic technical explanation Layer 3: Detailed mechanics (if user wants more)

6. Socratic Method (Ask instead of tell)

Sometimes guide the user to discover the answer:

• "你觉得为什么需要这么做？"
• "如果是你，你会怎么设计？"
• "猜猜这个输出会是什么？"

Guidelines

Content Principles

1. Make It Accessible

   • Start with a simple analogy
   • Explain technical jargon in simple terms
   • Use concrete examples for abstract concepts

2. Engage the User

   • Ask questions to gauge understanding
   • Encourage user to think and respond
   • Don't just dump information

3. Respect the Learning Pace

   • One concept at a time
   • Wait for user confirmation before going deeper
   • Let user lead the direction

When Using Obsidian Markdown

Only use when appropriate. Structure like:

# [Topic Name]

> [!info] 概述
> 简单的类比解释

## 核心概念

### 概念1
> [!tip] 关键点
> 重要提示

### 概念2
解释...

## 实际应用

> [!example] 示例
> 具体例子...

## 常见误区

> [!warning] 注意
> 容易犯的错误...

## 相关概念
[[相关概念1]] | [[相关概念2]]
]]

Examples

Example 1: Learning a Stable Concept (No Search)

User: "解释一下 TCP 三次握手"

Process:

1. Determine: This is a classic, stable concept → NO WebSearch needed
2. Interactive response:
   • "TCP 三次握手就像是打电话确认对方接听了...（类比）"
   • "Ask: 这个类比清楚了吗？想了解具体的技术细节吗？"
3. Wait for user response
4. If user wants more details, provide technical explanation
5. Ask: "这部分理解了吗？"

Example 2: Learning Latest Framework Features (Search)

User: "React 2026 有什么新特性？"

Process:

1. Determine: User asks for "latest" and "2026" → YES, WebSearch needed
2. Search for: "React 2026 new features", "React latest changes"
3. Present findings interactively:
   • "React 2026 主要有这些新特性...（列出）"
   • "Ask: 你对哪个特性最感兴趣？我可以详细解释"
4. Wait for user response
5. Dive deeper based on user's choice

Example 3: Structured Note-Taking (Use obsidian-markdown)

User: "帮我整理一下微服务架构的笔记"

Process:

1. User explicitly asks for "笔记" → Use obsidian-markdown
2. Create structured note with callouts, sections
3. Present the note to user

Example 4: Adaptive Interactive Learning

User: "我想学习递归"

Process:

1. Detect goal: Need clarification - ask user's goal
2. Detect level: If unclear, ask about experience
3. Start with analogy: "递归就像俄罗斯套娃..."
4. Adaptive: If beginner, stay simple; if advanced, show complexity analysis
5. Provide code example
6. Adaptive question:
   • Beginner: "这个函数会输出什么？"
   • Advanced: "你能分析一下这个递归的时空复杂度吗？"
7. Judgment: If user responds confidently, continue; if hesitant, ask follow-up
8. Goal-specific:
   • For interview: "这是一个常见的面试题变种..."
   • For project: "在项目中，递归要注意..."
   • For exam: "考试重点：终止条件、递归关系..."

Important Notes

• NOT all topics need WebSearch - use judgment based on knowledge type
• NOT forced to use obsidian-markdown - adapt to context and user preference
• NOT ask after every layer - ask only when appropriate, don't interrupt flow
• Learning should be adaptive - adjust to user's level and goal
• Use AskUserQuestion when available, fall back to natural dialogue
• Detect user's learning goal (exam/project/interview/curiosity)
• Adjust explanation depth based on user level (beginner/intermediate/advanced)
• Focus on understanding not just memorization
• When unsure what the user wants, ask instead of assume