Agent skill

Lecture Notes Master

by LeoYeAI in LeoYeAI/openclaw-master-skills

Obsidian lecture notes with recursive atomic decomposition. An agent skill from LeoYeAI/openclaw-master-skills.

MITAuto-check passedDocuments & Office

Install Lecture Notes Master

skills CLI
$ npx skills add LeoYeAI/openclaw-master-skills --skill lecture-notes-master -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install LeoYeAI/openclaw-master-skills lecture-notes-master --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/lecture-notes-master .claude/skills/lecture-notes-master && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
lecture-notes-master
GitHub stars
2.2k
Token cost
~4.9k tokens
SKILL.md length
1,775 words
Files
15 (incl. scripts)
Skills in repo
972
Repo updated
First seen
Licence
MIT

At a glance

Obsidian lecture notes with recursive atomic decomposition. An agent skill from LeoYeAI/openclaw-master-skills.

  • Works in 5 steps: Analyze User Input → Plan Decomposition Tree → Search Existing Resources → …
  • Tasks that involve Note-taking
  • SKILL.md covers When to Apply, User Profile, Core Principles and Prerequisites, plus 7 more sections
  • Runs Python scripts from its folder; calls python3, python and pip3

What it does

Lecture Notes Master is an agent skill from LeoYeAI/openclaw-master-skills. 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.

Its SKILL.md is about 4.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 17 other files, including scripts (for example `EXAMPLES.md`, `_meta.json` and `config.json`).

It sits in Documents & Office, covering Note-taking and Translation. It works with Obsidian. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.

When your agent uses it

  • Tasks that involve Note-taking
  • Tasks that involve Translation

Example prompts

  • “/lecture-notes-master”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Analyze User Input
  2. Plan Decomposition Tree
  3. Search Existing Resources
  4. Generate Notes (in order)
  5. Generate Visualizations (as needed)

What it can do on your machine

Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3
    • python
    • pip3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • youtu.be

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Lecture Notes Master loads about 4.9k tokens when it runs. Until then it costs about 87 tokens; SKILL.md has 1,775 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~87
When it runs · the whole SKILL.md, loaded when a task matches
~4.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 1,775 words, ~4,943 tokens.

Download SKILL.mdSave it as .claude/skills/lecture-notes-master/SKILL.md (or your agent's skills folder). This skill also uses 14 other files; get the full folder from GitHub.
name
lecture-notes-master
description
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.

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:


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:

{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
LocationContainsExample
{Topic}/ rootMain note onlyLazygit-Notes.md
NN-{L1-Concept}/L1 note + its L2 children + their L3 children01-Installation-and-Setup/
glossary/All glossary entriesglossary/TUI(终端用户界面).md
assets/Generated charts/imagesassets/performance-chart.png

Numbering Rules:

  1. L1 subdirectories use two-digit prefix: 01-, 02-, 03-, ...
  2. No atomic notes in the topic root — only the main hub note lives there
  3. Within each L1 folder, all notes are flat (L1 + L2 + L3 together, no further nesting)
  4. Numbering follows the order of L1 concepts as they appear in the main note
  5. 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 GlossaryUse Atomic Note
Term needing a bilingual definition (1-3 sentences)Concept requiring explanation, examples, diagrams
No deep analysis neededHas sub-components worth exploring
Pure noun/termHas "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:

  1. 定义 — One-paragraph definition with inline wikilinks
  2. Why Do We Need This? — Motivation with concrete scenario
  3. Core Concept — Idea + example + Mermaid diagram + step-by-step breakdown
  4. Comparison — Table comparing with/without, or vs alternatives
  5. Common Pitfalls — 2-3 mistakes and fixes (omit only if truly not applicable)
  6. Key Takeaway — One flashcard-worthy sentence
  7. Review Questions — 3 levels: recall, understanding, application
  8. 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)
RuleDescription
Step-by-step"Why do we need this?" → "What is it?" → "How does it work?" → "Watch out for..."
Example-drivenExample FIRST, then explain the principle. Never start with pure theory
Visual-richEvery concept gets at least one Mermaid diagram OR table
Table comparisonSimilar concepts → comparison table
Bilingual termsEnglish Term(中文), English is primary
AtomicEach note covers exactly ONE concept
Review questions3 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)
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.

OrderNote TypeWrite ToExample Path
1Main note (hub){Topic}/ root — ONLY file hereLazygit/Lazygit-Notes.md
2L1 atomic notes{Topic}/NN-{L1-Concept}/Lazygit/01-Installation-and-Setup/Installation-and-Setup.md
3L2 atomic notesSame dir as parent L1Lazygit/03-Basic-Git-Operations/Staging-and-Committing.md
4L3 atomic notesSame dir as parent L1Lazygit/03-Basic-Git-Operations/Staging-Modes.md
5Glossary entries{Topic}/glossary/Lazygit/glossary/Stage(暂存).md
6Visualizations{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:

TypeTemplate FileDescription
Main Note (主笔记)templates/lecture-note.mdHub note with overview, N sections, summary, review questions
Atomic Note (原子笔记)templates/atomic-note.mdRich concept note — used for ALL layers (L1, L2, L3)
Glossary Entry (原子概念)templates/glossary-entry.mdShort bilingual term definition
Course MOCtemplates/course-moc.mdMap 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
Show full SKILL.md (710 more words)Show less
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 TypeLinks UP toLinks DOWN toLinks ACROSS to
Main Note—All L1 notes—
L1 AtomicMain NoteIts L2 childrenSibling L1 notes
L2 AtomicParent L1Its L3 childrenSibling L2 notes
L3 AtomicParent L2—Sibling L3 notes
GlossaryRelated 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 targets MUST match filenames (without .md). Spaces → hyphens in atomic notes, but glossary keeps parenthetical Chinese.

Note TypeFile Name PatternWiki-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:

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

Mermaid Diagram Guidelines

Diagram TypeUse ForExample
graph TB/LRHierarchies, flows, architecturesConcept trees, process chains
sequenceDiagramTime-ordered interactionsData transfers, API calls
stateDiagram-v2State transitionsLifecycle, mode changes
classDiagramObject relationshipsClass hierarchy
ganttTimelines, parallel tasksProject phases, pipeline
pieProportionsDistribution breakdown
xychart-betaData trendsPerformance scaling
mindmapTopic overviewConcept clustering

Rules:

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

Color theme:

mermaid
%%{init: {'theme': 'base', 'themeVariables': {'primaryColor': '#4CAF50', 'primaryTextColor': '#fff', 'primaryBorderColor': '#388E3C', 'lineColor': '#666', 'secondaryColor': '#FF9800', 'tertiaryColor': '#2196F3'}}}%%

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

DomainUse ForExample Keywords
glossaryFind existing bilingual termscuda, memory, 内存, 术语
mermaidFind diagram templatesflow, sequence, hierarchy, 图表
writingGet writing style rulesintroduction, comparison, 规则
questionsGet review question templatesrecall, 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

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

© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 14 other files (scripts) in skills/lecture-notes-master of LeoYeAI/openclaw-master-skills.

  • SKILL.md
  • EXAMPLES.md
  • _meta.json
  • config.json
  • data/glossary.csv
  • data/mermaid-templates.csv
  • data/review-questions.csv
  • data/writing-rules.csv
  • scripts/generate.py
  • scripts/search.py
  • scripts/visualize.py
  • templates/atomic-note.md
  • templates/course-moc.md
  • templates/glossary-entry.md
  • templates/lecture-note.md

Open the folder on GitHubat commit e5199b5

Compare with similar skills

Lecture Notes Master next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Lecture Notes Master compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Lecture Notes Master this skillLeoYeAI/openclaw-master-skills2.2k—~4.9kAutomated safety check: PassMIT
Obsidian MarkdownKevRojo/Dulus141—~1.4kAutomated safety check: PassGPL-3.0
FIRE Card to EPUBtwhsi/skills259—~1kAutomated safety check: PassNone
Knap Markdown Templateskepano/obsidian-skills49k2 repos~986Automated safety check: PassMIT
Obsidian MarkdownAtmosphere/atmosphere3.8k20 repos~1.3kAutomated safety check: PassApache-2.0
Luhmann Note Numberertwhsi/skills259—~1.5kAutomated safety check: PassNone

Similar skills

  • Obsidian Markdown

    KevRojo/Dulus

    Create and edit Obsidian Flavored Markdown with wikilinks, embeds, callouts, properties, and other Obsidian-specific syntax.

    141 GitHub stars~1.4k tokensUpdated 5 days ago
    Documents & OfficeAuto-check passed
  • FIRE Card to EPUB

    twhsi/skills

    Converts FIRE analysis cards or project-note JSON into a validated EPUB book with directory, chapter and keyword index cards and backlinks.

    259 GitHub stars~1k tokensUpdated 2 mo ago
    Documents & OfficeAuto-check passed
  • Knap Markdown Templates

    kepano/obsidian-skills

    Renders Markdown notes from Knap templates and JSON data on the command line, including notes built from Defuddle web page output.

    49k GitHub starsUsed in 2 repos~986 tokens
    Documents & OfficeAuto-check passed
  • Obsidian Markdown

    Atmosphere/atmosphere

    Create and edit Obsidian Flavored Markdown with wikilinks, embeds, callouts, properties, and other Obsidian-specific syntax.

    3.8k GitHub starsUsed in 20 repos~1.3k tokens
    Documents & OfficeAuto-check passed
  • Assigns and checks Luhmann-style codes for book manuscript notes and Obsidian card folders without renumbering existing notes.

    259 GitHub stars~1.5k tokensUpdated 2 mo ago
    Knowledge ManagementAuto-check passed
  • Summarize

    reysu/ai-life-skills

    Summarize any content (YouTube video, article, whitepaper/PDF, podcast episode, book chapter, etc.) into a rich Obsidian note with section-by-section breakdowns, wikilinks to all technical concepts…

    270 GitHub stars~7.7k tokensUpdated 1 mo ago
    Documents & OfficeAuto-check passed

More from LeoYeAI/openclaw-master-skills

All 972 skills in this repo
  • DevOps Pipeline Management

    LeoYeAI/openclaw-master-skills

    Manages pipelines on a DevOps quality and efficiency platform through its OpenAPI: list workspaces and templates, create, update, run and cancel pipelines, and read run records.

    2.2k GitHub stars~4.2k tokensUpdated 2 mo ago
    Auto-check: notes
  • Feishu Document Collaboration

    LeoYeAI/openclaw-master-skills

    Patches OpenClaw's Feishu extension so an edited document triggers an isolated agent session that reads the doc and replies inline, turning it into a live chat space.

    2.2k GitHub stars~2k tokensUpdated 2 mo ago
    Auto-check passed
  • Files Memory System

    LeoYeAI/openclaw-master-skills

    Multi-context memory management system for OpenClaw agents with group-isolated storage, global shared memory, workspace organization, and group-specific skills isolation.

    2.2k GitHub stars~3.8k tokensUpdated 2 mo ago
    Auto-check passed
  • GEO-Claw AI Visibility Agent

    LeoYeAI/openclaw-master-skills

    Runs a brand's AI-search visibility work end to end: diagnosing how AI platforms represent it, repositioning it, producing AI-optimized content and monitoring ongoing mentions.

    2.2k GitHub stars~4.7k tokensUpdated 2 mo ago
    Auto-check passed
  • Google Workspace CLI

    LeoYeAI/openclaw-master-skills

    Installs and authenticates the gws CLI, then automates Gmail, Drive, Sheets, Calendar, Docs, Chat and Tasks with ready-made recipes, persona bundles and security audits.

    2.2k GitHub stars~2.6k tokensUpdated 2 mo ago
    Auto-check: notes
  • HealthFit Health Advisors

    LeoYeAI/openclaw-master-skills

    Runs four advisor roles, a fitness coach, nutritionist, data analyst and TCM practitioner, to build a health profile and track workouts, diet and wellness over time.

    2.2k GitHub stars~4.4k tokensUpdated 2 mo ago
    Auto-check passed

Works with

Questions about Lecture Notes Master

What does Lecture Notes Master do?

Obsidian lecture notes with recursive atomic decomposition. An agent skill from LeoYeAI/openclaw-master-skills. Lecture Notes Master is an agent skill from LeoYeAI/openclaw-master-skills. Obsidian lecture notes with recursive atomic decomposition.

When should I use Lecture Notes Master?

Lecture Notes Master fits situations like: tasks that involve Note-taking; tasks that involve Translation.

How do I install Lecture Notes Master in Claude Code?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill lecture-notes-master -a claude-code`. Or copy the skill folder (skills/lecture-notes-master in LeoYeAI/openclaw-master-skills) into .claude/skills/lecture-notes-master in your project. Claude Code loads it when a task matches its description.

How do I install Lecture Notes Master in Codex?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill lecture-notes-master -a codex`. Or copy the skill folder (skills/lecture-notes-master in LeoYeAI/openclaw-master-skills) into .agents/skills/lecture-notes-master in your project. Codex loads it when a task matches its description.

Can I use Lecture Notes Master in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeoYeAI/openclaw-master-skills --skill lecture-notes-master -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/lecture-notes-master, .gemini/skills/lecture-notes-master, .github/skills/lecture-notes-master and .opencode/skills/lecture-notes-master in your project.

What does Lecture Notes Master need to run?

Going by SKILL.md and its folder, Lecture Notes Master needs Python for the scripts in its folder and the command-line tools its instructions call (python3, python and pip3). Our summary lists: Python 3.

Does Lecture Notes Master access the network?

SKILL.md names 1 domain. As links in the text: youtu.be. This is read from the text; nothing was executed.

Is Lecture Notes Master safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Lecture Notes Master use?

Lecture Notes Master is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Lecture Notes Master use?

About 4.9k tokens (SKILL.md is roughly 20k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Lecture Notes Master?

Skills that share tags, products or a category with Lecture Notes Master: Obsidian Markdown (KevRojo/Dulus, 141 stars), FIRE Card to EPUB (twhsi/skills, 259 stars), Knap Markdown Templates (kepano/obsidian-skills, 49k stars) and Obsidian Markdown (Atmosphere/atmosphere, 3.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Lecture Notes Master?

LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,159 GitHub stars. The repository holds 972 skills in this directory. The repository was last updated on July 20, 2026.

Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.