What makes Master Teacher notable?

988 downloads. Trust evidence available

How should Master Teacher be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

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agentCLAWHUBUnverified

Master Teacher

Systematic teaching skill for AI agents. Transforms the agent into a master-level instructor using mastery learning, Socratic questioning, and structured les... Skill: Master Teacher Owner: jacky-wzj Summary: Systematic teaching skill for AI agents. Transforms the agent into a master-level instructor using mastery learning, Socratic questioning, and structured les... Tags: latest:2.8.0 Version history: v2.8.0 | 2026-04-21T03:19:20.362Z | user v2.8: Add teaching principles #11 (state facts before comparing) and #12 (state facts before questioning) v2.7.0 | 2026-04-20T22:44:45

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

988

Updated

Oct 11, 2026

Version

2.8.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 988 downloads reported by the source. Last updated 10/11/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 11, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 11, 2026
Adoption signal: 988 downloadsadoption · observed Oct 11, 2026
Latest release: 2.8.0release · observed Apr 21, 2026
Handshake status: UNKNOWNsecurity

What changed

Newest first. Only changes that point at a source are listed.

Release 2.8.0release
v2.8: Add teaching principles #11 (state facts before comparing) and #12 (state facts before questioning)
Observed Apr 21, 2026 · source

Install and run

Setup complexity: low.

clawhub skill install s1736s06248q8gm2sshtab5kgx853tmt:master-teacher

Setup complexity is classified as HIGH. You must provision dedicated cloud infrastructure or an isolated VM. Do not run this directly on your local workstation.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-jacky-wzj-master-teacher/snapshot"

Run-check

$0.02 USD

1 measured facts are behind this paywall: success rate and latency, uptime and estimated cost, when not to use it, how to call it, benchmark scores.

Agents pay $0.02 in USDC. A card payment is $0.50, the smallest a card allows.

Documentation

CLAWHUB

136,472 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: master-teacher
description: "Systematic teaching skill for AI agents. Transforms the agent into a master-level instructor using mastery learning, Socratic questioning, and structured lesson delivery. Use when: (1) user asks to 'learn', 'study', or 'systematically understand' a topic, (2) multi-lesson curriculum is needed (≥3 lessons), (3) user wants progress tracking across fragmented learning sessions. Triggers on: 'teach me', 'create a course', 'I want to learn', 'systematic study'. NOT for: single Q&A, one-off tasks, casual chat."
---

# Master Teacher

Systematic teaching skill: prep → profile → outline → content authoring → teach → verify → track.

## Scripts

Deterministic operations use Python scripts. The model handles teaching and judgment; scripts handle state.

| Script | Purpose | When to call |
|--------|---------|-------------|
| `scripts/init_course.py` | Create course directory and state files | Phase 2: after student confirms outline |
| `scripts/track_progress.py start` | Mark a lesson as in-progress | Phase 3: when starting a lesson |
| `scripts/track_progress.py step` | Record a completed step within a lesson | Phase 3: after each step (position/concepts/code/practice) |
| `scripts/track_progress.py complete` | Mark a lesson as completed with score | Phase 3: after student passes verification |
| `scripts/show_progress.py` | Display visual progress overview | Phase 4: after every lesson completion |
| `scripts/lesson_report.py` | Generate and save lesson report | Phase 4: after every lesson completion (before show_progress) |
| `scripts/resume.py` | Load resume state and suggest review | Phase 5: when student returns after a break |

State lives in `progress/state.json` (single source of truth). `tracking.md` is auto-rebuilt by scripts. **Never manually write or edit tracking.md or state.json.**

## Execution Flow

### Phase 0: Prep

**Prep is a research-heavy phase. It may span multiple sessions.**

**Step 1: Collect materials**
- Search for courses, tutorials, blogs, books, videos, and source code analysis on the topic
- Save to course directory:
  ```
  <course>/prep/
  ├── sources.md       ← All reference links + one-line evaluation
  ├── repos/           ← Cloned repositories
  ├── articles/        ← Saved articles/PDFs
  └── notes.md         ← Research notes per source
  ```
- Search iteratively, cross-validate across sources

**Step 2: Study materials**
- Read each source, write findings into notes.md
- Compare viewpoints (who is right? whose angle is unique?)
- Identify consensus and disagreements
- Do not rush this step

**Step 3: Synthesize**
- Design your knowledge tree (concepts, sequence, dependencies)
- Borrow proven structures from existing materials
- Fill gaps (what others missed or explained poorly)
- Generate prep/synthesis.md: draft teaching plan

When prep is complete, tell the student: "Prep done. Studied X sources. Ready to outline."

### Phase 1: Profile the Student

Check USER.md / MEMORY.md

README.md

# Master Teacher 🎓

Systematic teaching skill for AI agents — mastery learning, Socratic questioning, and progress tracking.

Transforms your AI agent into a master-level instructor for teaching complex technical topics (architecture, source code analysis, system design).

## Features

- **Prep before teaching** — agent researches the topic before lecturing
- **Mastery learning** — students must pass verification (≥2/3) before advancing
- **Socratic questioning** — guide with questions, don't give conclusions
- **Structured lessons** — position → theory → code → relate to practice → verify
- **Progress tracking** — persistent across fragmented learning sessions
- **Adaptive pacing** — handles "too easy", "don't understand", off-topic, silence
- **Mid-course review** — revisit weak points at halfway mark
- **Final report** — summary of mastery, weak points, and next steps

## Install

### Claude Code

```bash
# Option 1: Clone to personal skills
git clone https://github.com/jacky-wzj/master-teacher.git ~/.claude/skills/master-teacher

# Option 2: Clone to project skills
git clone https://github.com/jacky-wzj/master-teacher.git .claude/skills/master-teacher
```

Then in Claude Code, the skill activates when you say things like:
- "教我 X"
- "teach me about X"
- "我要系统学习 X"
- "create a course on X"

Or invoke directly: `/master-teacher`

### OpenClaw

```bash
# From ClawHub
clawhub install master-teacher

# Or clone manually
git clone https://github.com/jacky-wzj/master-teacher.git ~/.openclaw/skills/master-teacher
```

The skill triggers when the user asks to systematically learn a topic.

## Usage

Once installed, just ask the agent to teach you something:

```
我想系统学习 Claude Code 的架构设计
```

The agent will:
1. **Prep** — research the topic first
2. **Profile** — check what it already knows about you, ask only what's missing
3. **Outline** — propose a curriculum, wait for your confirmation
4. **Teach** — deliver lessons one at a time with verification
5. **Track** — save progress so you can resume anytime

## Course files

Each course is stored in the workspace:

```
<workspace>/<course-name>/
├── README.md              # Course outline
├── lessons/
│   ├── lesson-01-xxx.md   # Lesson content
│   └── lesson-02-xxx.md
└── progress/
    └── tracking.md        # Learning progress
```

## License

MIT

_meta.json

{
  "ownerId": "kn72fx843ww9pnr3vaq4extfgs8524z6",
  "slug": "master-teacher",
  "version": "2.8.0",
  "publishedAt": 1776741560362
}

skill-card.md

## Description:

Master Teacher transforms an AI agent into a structured instructor for multi-lesson courses using mastery learning, Socratic questioning, lesson authoring, and progress tracking.

This skill is ready for commercial/non-commercial use.

## Publisher:

[jacky-wzj](https://clawhub.ai/user/jacky-wzj)

### License/Terms of Use:

MIT-0

## Use Case:

Developers, technical learners, and external users use this skill to have an agent research a topic, build a structured curriculum, deliver lessons one topic at a time, verify mastery, and preserve progress across sessions.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: The skill may read USER.md or MEMORY.md during student profiling, which can expose personal, project, or company context.

Mitigation: Review memory/profile files before use and avoid using the skill in workspaces that contain secrets or sensitive personal or company information.

Risk: The skill persists course data, progress state, student responses, reports, and weak points in local files.

Mitigation: Use a dedicated course directory, keep sensitive prompts and answers out of the course, and remove or sanitize generated files when they are no longer needed.

## Reference(s):

- [Master Teacher on ClawHub](https://clawhub.ai/jacky-wzj/skills/master-teacher)

## Skill Output:

**Output Type(s):** [Text, Markdown, Code, Shell commands, Configuration, Guidance, Files]

**Output Format:** [Markdown lessons, reports, progress summaries, inline shell commands, JSON state files, and course directory files.]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [May persist local course materials, progress state, reports, student responses, and weak points in the workspace.]

## Skill Version(s):

2.8.0 (source: server release metadata)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

templates/lesson.md

---
## Lesson template — copy and fill for each lesson

# Lesson X: [Title]

> One-line summary

## Position
Where this sits in the course. What it depends on. What it unlocks.

## Core Concepts

### Design intent (why)

### Comparison (why A not B)

### Key ideas

## Code / Examples

```
# annotated snippet
```

## How This Applies to Our Work

## Verification

| # | Question | Type | Answer key |
|---|----------|------|-----------|
| 1 | | Comprehension | |
| 2 | | Application | |
| 3 | | Analysis | |

### Student answers & grading
(filled during teaching)

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