lecture-notes-master

Obsidian lecture notes with recursive atomic decomposition. Generates main note (hub), atomic notes (3+ layers deep, rich structure each), and unlimited glossary entries. Inputs: lectures, articles, videos, URLs, transcripts, PDFs. Outputs: Obsidian markdown with Mermaid diagrams, comparison tables, bilingual terms, wikilinks.

SchaeferAnjon@schaeferanjon

Install

openclaw skills install @schaeferanjon/lecture-notes-master

Lecture Notes Master

Generate structured Obsidian lecture notes with recursive atomic decomposition:

主笔记 (Main Note): Hub note with overview, core sections, summary, review questions
原子笔记 (Atomic Notes): Deep concept notes in ≥3 layers, each layer with rich structure
原子概念 (Glossary): Unlimited bilingual term definitions

When to Apply

Triggers:

User provides: URL, video link, PDF, transcript, PPT, slides, article
User says: "总结", "summarize", "create notes", "lecture notes", "笔记", "做笔记"
User mentions: Obsidian, atomic notes, wikilinks, PARA, MOC
User provides content for note-taking or analysis
Exam prep / study materials

Example prompts:

"总结一下这个视频 https://youtu.be/xxx"
"Create lecture notes for this article"
"帮我做笔记 https://www.example.com/article"
"Summarize this into Obsidian notes"

User Profile

Configured in config.json:

Name: Schaefer (Zonghan Jia)
University: Heidelberg University (ZITI), Computer Engineering
Obsidian Vault: See config.json → obsidian.vault_path
Output Directory: 00-Inbox/{Topic}/ (main note + glossary + numbered L1 subdirectories)
Language: Bilingual — English primary, Chinese secondary
Term format: English Term（中文术语）

Core Principles

Recursive Atomic Decomposition

Every source material is decomposed into a tree of notes, organized into numbered subdirectories by L1 topic:

text

{Topic}/
├── 主笔记: {Topic}-Notes.md
│   Hub note linking to all L1 atomic notes
│
├── 01-{L1-Concept-A}/
│   ├── {L1-Concept-A}.md              (L1 顶层概念)
│   ├── {L2-Sub-Concept-A1}.md         (L2 子概念)
│   ├── {L2-Sub-Concept-A2}.md         (L2 子概念)
│   ├── {L3-Detail-A1a}.md             (L3 细分解)
│   └── {L3-Detail-A1b}.md             (L3 细分解)
│
├── 02-{L1-Concept-B}/
│   ├── {L1-Concept-B}.md              (L1 顶层概念)
│   ├── {L2-Sub-Concept-B1}.md         (L2 子概念)
│   └── {L3-Detail-B1a}.md             (L3 细分解)
│
├── 03-{L1-Concept-C}/
│   └── {L1-Concept-C}.md              (L1 顶层概念)
│
├── glossary/（原子概念 — 术语定义，不限量）
│   ├── English Term（中文术语）.md
│   └── ... 每个术语一个文件
│
└── assets/（图表资源）
    └── *.png

Directory Organization Rules

Location	Contains	Example
`{Topic}/` root	Main note only	`Lazygit-Notes.md`
`NN-{L1-Concept}/`	L1 note + its L2 children + their L3 children	`01-Installation-and-Setup/`
`glossary/`	All glossary entries	`glossary/TUI（终端用户界面）.md`
`assets/`	Generated charts/images	`assets/performance-chart.png`

Numbering Rules:

L1 subdirectories use two-digit prefix: 01-, 02-, 03-, ...
No atomic notes in the topic root — only the main hub note lives there
Within each L1 folder, all notes are flat (L1 + L2 + L3 together, no further nesting)
Numbering follows the order of L1 concepts as they appear in the main note
Wiki-links use filename only (no path prefix) — Obsidian resolves them automatically

Decomposition Rules

Layer 1 (顶层概念):

Source material's major themes, sections, or arguments
Each L1 note covers ONE major concept branch
Number: determined by content (typically 3-7, NOT fixed)

Layer 2 (子概念):

Sub-concepts, mechanisms, or components within each L1 concept
Each L2 explains a specific aspect of its parent L1
Number: typically 2-4 per L1 parent

Layer 3+ (细分解):

Specific mechanisms, case studies, comparisons, or evidence
Finest granularity of analysis
Number: as many as the content demands

Stop Decomposing When:

A concept can be fully explained in ≤500 words with one diagram
Further splitting would break logical coherence
The concept is better served as a glossary entry (pure definition)

Glossary vs Atomic Note:

Use Glossary	Use Atomic Note
Term needing a bilingual definition (1-3 sentences)	Concept requiring explanation, examples, diagrams
No deep analysis needed	Has sub-components worth exploring
Pure noun/term	Has "why", "how", comparison dimensions

Minimum Requirement

Every set of notes MUST produce:

1 main note (主笔记)
≥3 layers of atomic notes (L1 → L2 → L3 minimum)
Glossary entries for ALL technical terms mentioned

Every Atomic Note Must Be Rich

ALL atomic notes (L1, L2, L3) use the same rich template structure:

定义 — One-paragraph definition with inline wikilinks
Why Do We Need This? — Motivation with concrete scenario
Core Concept — Idea + example + Mermaid diagram + step-by-step breakdown
Comparison — Table comparing with/without, or vs alternatives
Common Pitfalls — 2-3 mistakes and fixes (omit only if truly not applicable)
Key Takeaway — One flashcard-worthy sentence
Review Questions — 3 levels: recall, understanding, application
Related Notes — Parent (UP), children (DOWN), siblings (ACROSS)

See templates/atomic-note.md for the full template.

Writing Style: Runoob Tutorial（菜鸟教程风格）

Rule	Description
Step-by-step	"Why do we need this?" → "What is it?" → "How does it work?" → "Watch out for..."
Example-driven	Example FIRST, then explain the principle. Never start with pure theory
Visual-rich	Every concept gets at least one Mermaid diagram OR table
Table comparison	Similar concepts → comparison table
Bilingual terms	`English Term（中文）`, English is primary
Atomic	Each note covers exactly ONE concept
Review questions	3 per note: recall, understanding, application

Prerequisites

bash

python3 --version || python --version
pip3 install matplotlib numpy  # For visualization scripts (optional)

Optional: summarize CLI for URL/video content extraction.

Workflow

Step 1: Analyze User Input

Identify: input type (URL, video, PDF, transcript, raw text), topic name, key themes.

URL & Video Content Extraction

When user provides a URL or video link, use summarize CLI:

bash

# Extract text from URL
summarize "<URL>" --extract-only --model google/gemini-3-flash-preview

# Extract YouTube transcript
summarize "<YouTube-URL>" --youtube auto --extract-only

# Pre-summary for screening
summarize "<URL>" --length medium --model google/gemini-3-flash-preview

Useful flags: --extract-only (raw text), --youtube auto, --firecrawl auto (JS-heavy sites), --json

If summarize is not available: Use the agent's built-in web fetching tools as fallback.

Step 2: Plan Decomposition Tree

⚠️ MANDATORY: You MUST complete this step BEFORE writing ANY content. ⚠️ MANDATORY: You MUST create ALL directories with mkdir -p BEFORE writing ANY files. ⚠️ ZERO TOLERANCE: No atomic notes are allowed in the topic root directory. ONLY the main hub note lives there.

Plan the COMPLETE file tree with numbered directories, then create them immediately.

2a. Plan the tree (output to user for confirmation)

text

Topic: 2028 Global Intelligence Crisis

主笔记: 2028-Global-Intelligence-Crisis-Notes.md  (in topic root)

01-Intelligence-Displacement-Spiral/
  L1: Intelligence-Displacement-Spiral.md
  L2: OpEx-Substitution-Mechanism.md
  L2: Ghost-GDP-Phenomenon.md
  L3: OpEx-vs-CapEx-AI-Spending.md               ← parent: OpEx-Substitution
  L3: Why-No-Natural-Brake.md                     ← parent: OpEx-Substitution

02-SaaS-Collapse-and-Intermediation-Death/
  L1: SaaS-Collapse-and-Intermediation-Death.md
  L2: Agentic-Coding-Disruption.md
  L2: Habitual-Intermediation-Collapse.md
  L3: Friction-Zero-Disruption.md                 ← parent: Habitual-Intermediation

03-White-Collar-Displacement-Asymmetry/
  L1: White-Collar-Displacement-Asymmetry.md
  L2: Downshifting-Effect.md
  L2: Labor-Share-Decline.md

04-Financial-Contagion-Chain/
  L1: Financial-Contagion-Chain.md
  L2: Private-Credit-SaaS-Crisis.md
  L2: Permanent-Capital-Trap.md
  L2: Mortgage-Market-Structural-Threat.md
  L3: Zendesk-Case-Study.md                       ← parent: Private-Credit
  L3: Insurance-Asset-Impairment.md               ← parent: Permanent-Capital

glossary/ (42 entries):
  glossary/Ghost GDP（幽灵GDP）.md
  glossary/Intelligence Displacement Spiral（智能替代螺旋）.md
  glossary/Private Credit（私募信贷）.md
  ... (one file per term)

2b. Create ALL directories FIRST (before writing any files)

bash

# MANDATORY: Run this BEFORE writing any notes
TOPIC_DIR="<vault>/00-Inbox/{Topic}"
mkdir -p "$TOPIC_DIR"
mkdir -p "$TOPIC_DIR/01-{L1-Concept-A}"
mkdir -p "$TOPIC_DIR/02-{L1-Concept-B}"
mkdir -p "$TOPIC_DIR/03-{L1-Concept-C}"
# ... one mkdir per L1 concept
mkdir -p "$TOPIC_DIR/glossary"
mkdir -p "$TOPIC_DIR/assets"

2c. Verify directory structure before proceeding

bash

# Verify: must show numbered subdirectories + glossary + assets
find "$TOPIC_DIR" -type d | sort

Only proceed to Step 3 after directories exist.

Step 3: Search Existing Resources

bash

# Search glossary for existing bilingual terms
python3 <SKILL_DIR>/scripts/search.py "<topic keywords>" --domain glossary

# Search Mermaid templates for diagram ideas
python3 <SKILL_DIR>/scripts/search.py "<concept type>" --domain mermaid

# Search writing rules for style guidance
python3 <SKILL_DIR>/scripts/search.py "<content type>" --domain writing

Step 4: Generate Notes (in order)

⚠️ CRITICAL: Every file MUST be written to its correct subdirectory. Double-check the output path before every Write/Edit call.

Order	Note Type	Write To	Example Path
1	Main note (hub)	`{Topic}/` root — ONLY file here	`Lazygit/Lazygit-Notes.md`
2	L1 atomic notes	`{Topic}/NN-{L1-Concept}/`	`Lazygit/01-Installation-and-Setup/Installation-and-Setup.md`
3	L2 atomic notes	Same dir as parent L1	`Lazygit/03-Basic-Git-Operations/Staging-and-Committing.md`
4	L3 atomic notes	Same dir as parent L1	`Lazygit/03-Basic-Git-Operations/Staging-Modes.md`
5	Glossary entries	`{Topic}/glossary/`	`Lazygit/glossary/Stage（暂存）.md`
6	Visualizations	`{Topic}/assets/`	`Lazygit/assets/workflow-chart.png`

Self-check before each file write:

Is this the main hub note? → Write to {Topic}/ root
Is this an atomic note (L1/L2/L3)? → Write to {Topic}/NN-{L1-Parent}/
Is this a glossary entry? → Write to {Topic}/glossary/
NEVER write atomic notes directly to {Topic}/ root

Script Usage

bash

# Main note (in topic root)
python3 <SKILL_DIR>/scripts/generate.py \
  --type lecture --title "<title>" \
  --concepts "C1,C2,C3,C4" \
  --output "<vault>/00-Inbox/{Topic}/"

# Atomic note (any layer — output to its L1 parent subdirectory)
python3 <SKILL_DIR>/scripts/generate.py \
  --type atomic --concept "<name>" \
  --parent "<parent-note-stem>" \
  --children "Child1,Child2" \
  --siblings "Sibling1,Sibling2" \
  --output "<vault>/00-Inbox/{Topic}/NN-{L1-Concept}/"

# Glossary entry
python3 <SKILL_DIR>/scripts/generate.py \
  --type glossary --term-en "<English Term>" --term-cn "<中文术语>" \
  --definition "<one-line definition>" \
  --output "<vault>/00-Inbox/{Topic}/glossary/"

# Course MOC
python3 <SKILL_DIR>/scripts/generate.py \
  --type moc --course "<course>" --semester "<semester>"

Note: <SKILL_DIR> = the directory where this skill is installed. NN = two-digit L1 index (01, 02, ...).

Step 5: Generate Visualizations (as needed)

For data-driven charts that Mermaid cannot handle:

bash

python3 <SKILL_DIR>/scripts/visualize.py \
  --type "<chart_type>" \
  --data "<data_json>" \
  --output "<output_path>" \
  --title "<chart title>"

Available chart types: bar, line, scatter, timeline, heatmap, comparison, pie, radar

Output Format Templates

All templates are in the templates/ directory:

Type	Template File	Description
Main Note (主笔记)	`templates/lecture-note.md`	Hub note with overview, N sections, summary, review questions
Atomic Note (原子笔记)	`templates/atomic-note.md`	Rich concept note — used for ALL layers (L1, L2, L3)
Glossary Entry (原子概念)	`templates/glossary-entry.md`	Short bilingual term definition
Course MOC	`templates/course-moc.md`	Map of Content with lecture index, concept clusters

Main Note (主笔记) Key Requirements

YAML frontmatter: title, date, course/topic, tags, source_files, status, aliases
Core Idea（核心思想）blockquote with inline [[glossary-wikilinks]]
Source links
Overview section (with image embed if available)
N numbered sections (one per L1 concept, NOT limited to 3), each with:
- → 详见 [[L1-Atomic-Note]] link
- Sub-sections: Why → What → How
- Mermaid diagrams, comparison tables, key insight blockquotes
Summary section: concept map (Mermaid) + data summary table + key quote
Review Questions: recall + understanding + application + critical thinking
Related Notes linking to all L1 atomic notes

Atomic Note (原子笔记) Key Requirements

Same rich structure for ALL layers (L1, L2, L3):

YAML frontmatter: title (bilingual), date, tags, aliases
One-paragraph 定义 with inline wikilinks
Why Do We Need This? — motivation + concrete example
Core Concept — idea + example/code + Mermaid diagram + step-by-step
Comparison — table comparing alternatives or with/without
Common Pitfalls — mistakes and how to avoid
Key Takeaway — one flashcard-worthy sentence
Review Questions — recall, understanding, application
Related Notes — parent (UP) + children (DOWN) + siblings (ACROSS)

Glossary Entry (原子概念) Key Requirements

YAML frontmatter: title (bilingual), date, tags: [glossary, {topic-tag}], aliases
One blockquote 定义 (1-3 sentences, bilingual)
Related Notes linking to relevant atomic notes + main note

Cross-Reference Rules (CRITICAL)

All notes link in THREE directions:

Note Type	Links UP to	Links DOWN to	Links ACROSS to
Main Note	—	All L1 notes	—
L1 Atomic	Main Note	Its L2 children	Sibling L1 notes
L2 Atomic	Parent L1	Its L3 children	Sibling L2 notes
L3 Atomic	Parent L2	—	Sibling L3 notes
Glossary	Related atomic notes	—	Related glossary terms

Inline wikilinks: All glossary terms MUST be linked inline on first mention in every note using [[Term（术语）]] syntax.

Wiki-Link Naming Convention (CRITICAL)

Wiki-link targets MUST match filenames (without .md). Spaces → hyphens in atomic notes, but glossary keeps parenthetical Chinese.

Note Type	File Name Pattern	Wiki-Link
Main Note	`{Topic}-Notes.md`	`[[{Topic}-Notes]]`
Atomic Note	`{Concept-Name}.md`	`[[{Concept-Name}]]`
Glossary Entry	`{English Term（中文术语）}.md`	`[[{English Term（中文术语）}]]`

Rules:

Before generating any notes, list ALL file names AND their target directories
NEVER leave wiki-links empty ([[]]) or with placeholder text ([[TODO]])
If a target note doesn't exist yet, use the correct future filename — Obsidian creates it on click
Glossary filenames include both English and Chinese: English Term（中文术语）.md
Wiki-links use filename only (no path) — Obsidian resolves across subdirectories automatically

Mermaid Diagram Guidelines

Diagram Type	Use For	Example
`graph TB/LR`	Hierarchies, flows, architectures	Concept trees, process chains
`sequenceDiagram`	Time-ordered interactions	Data transfers, API calls
`stateDiagram-v2`	State transitions	Lifecycle, mode changes
`classDiagram`	Object relationships	Class hierarchy
`gantt`	Timelines, parallel tasks	Project phases, pipeline
`pie`	Proportions	Distribution breakdown
`xychart-beta`	Data trends	Performance scaling
`mindmap`	Topic overview	Concept clustering

Rules:

NEVER use ASCII art — always Mermaid
Every diagram must have a title and labeled edges
Max 15-20 nodes per diagram
Use classDef for consistent colors
Use subgraphs for grouping

Color theme:

Rendering diagram...

Matplotlib Visualization

Use when Mermaid cannot express the data: performance bars, scaling curves, heatmaps, radar charts.

Rules: PNG at dpi=150, consistent colors (#4CAF50, #FF9800, #2196F3, #F44336), always include axis labels and title, reference as ![[filename.png]].

Search Reference

Domain	Use For	Example Keywords
`glossary`	Find existing bilingual terms	cuda, memory, 内存, 术语
`mermaid`	Find diagram templates	flow, sequence, hierarchy, 图表
`writing`	Get writing style rules	introduction, comparison, 规则
`questions`	Get review question templates	recall, application, 考试

Quality Checklist

Content

WHY → WHAT → HOW structure for every concept (all layers)
Example appears BEFORE theory in every concept note
All terms bilingual: English（中文）
Each atomic note covers exactly ONE concept

Decomposition

Decomposition tree planned BEFORE writing
ALL file names AND target directories listed before generation
≥3 layers of atomic notes produced (L1 → L2 → L3 minimum)
L1 covers major themes, L2 breaks down sub-concepts, L3 provides finest analysis
Glossary entries for ALL technical terms mentioned

Visualization

NO ASCII art — use Mermaid
Every concept has at least one diagram or table
Similar concepts have comparison tables
Diagrams have titles and labeled edges

Structure

YAML frontmatter complete (title, date, tags, aliases)
[[wiki-links]] for all cross-references (inline + Related Notes)
3 review questions per atomic note: recall, understanding, application
Related Notes with UP / DOWN / ACROSS links
File naming: Concept-Name.md (hyphens for atomic notes)

Directory Organization

Main note in topic root (00-Inbox/{Topic}/)
Atomic notes organized into numbered L1 subdirectories (01-xxx/, 02-xxx/)
L2 and L3 notes placed inside their parent L1 subdirectory (flat, no further nesting)
Glossary entries in glossary/ subdirectory
No atomic notes left loose in topic root

Obsidian Compatibility

[[wiki-links]] syntax (not markdown links)
Standard ```mermaid fencing
Images: ![[image.png]]
Tags: lowercase with hyphens

Tips

Provide source material: URL, video link, PDF, transcript → better notes
Video links: Paste YouTube/Bilibili URLs directly; transcript auto-extracted
Be specific about topic: "这个视频的AI经济分析" > "总结一下"
Search glossary first: Reuse existing terms for cross-course consistency
Iterate: Generate base notes, then ask for deeper decomposition on specific branches
Cross-reference: Link related concepts across different note sets