A Feynman-based learning coach that builds systematic multi-day learning plans and provides rapid article or book breakdowns.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install quick-learn
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install quick-learn using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Quick Learn: Feynman-Based Smart Learning Coach?
Quick Learn is a sophisticated learning agent designed to facilitate deep understanding through the Feynman Technique. By acting as a proactive coach, it researches authoritative sources, designs custom curricula, and manages interactive study sessions. It is part of the Openclaw Skills collection, enabling developers and researchers to move beyond passive consumption into active mastery. The skill supports both systematic long-term learning paths and rapid breakdown modes for articles and books, ensuring that technical concepts are simplified and reinforced through active recall. Its core philosophy revolves around the four steps of study, explanation, gap identification, and simplification, transforming learning from a one-way delivery into a conversational experience.
Quick Learn: Feynman-Based Smart Learning Coach Use Cases
- Rapidly mastering new technologies or frameworks like React, Docker, or Kubernetes through structured daily curricula.
- Breaking down complex research papers, long-form articles, and technical books into actionable summaries.
- Maintaining long-term study habits using automated daily push notifications and scheduled learning reminders.
- Identifying conceptual blind spots by explaining topics in plain language to an agent that provides immediate feedback.
How Quick Learn: Feynman-Based Smart Learning Coach Works
- Multi-Source Discovery: The agent searches across five dimensions including official documentation, best practices, and curated roadmaps to find high-quality references.
- Intelligent Planning: It estimates the required duration based on concept density and user experience, generating a persistent path.json configuration.
- Automated Interaction: Utilizing cron jobs, the agent pushes structured daily lessons containing core concepts, examples, and Mermaid diagrams.
- Feynman Feedback Loop: Users are prompted to explain concepts in their own words; the agent then identifies gaps and provides simplified analogies to bridge them.
- Progressive Tracking: The system logs every session in structured markdown and JSON to monitor study duration, mood trends, and concept mastery levels.
- Forgetting Curve Review: Automated review triggers ensure long-term retention through spaced repetition at 1, 3, and 7-day intervals.
Quick Learn: Feynman-Based Smart Learning Coach Setup
To begin a systematic plan, simply provide a prompt such as "help me learn React Hooks". For rapid summaries, provide a URL or content and say "explain this article". Advanced users can manually generate or customize paths using the integrated Python helper script:
python3 skills/quick-learn/scripts/learner.py path "{topic}" {days} --output learning-data/{slug}/path.json
Quick Learn: Feynman-Based Smart Learning Coach Data Schema & Taxonomy
The skill organizes its data within the learning-data/ directory using slug-based subfolders for each unique topic:
| File | Purpose |
|---|---|
path.json |
Main state file tracking progress, schedule, and daily curriculum keywords. |
sources.md |
Documented list of verified authority links and documentation sources curated via search. |
daily-log.md |
Chronological record of study sessions, Feynman responses, and simplification quality scores. |
breakdown.md |
Generated summaries for Mode B article or book breakdowns for quick reference. |
Quick Learn: Feynman-Based Smart Learning Coach Advanced Features
- Multi-plan Orchestration: Seamlessly manage and track multiple active learning tracks simultaneously without schedule interference.
- Dynamic Difficulty Scaling: Automatically adjusts content complexity and analogy types based on user performance ratios and engagement levels.
- Visual Knowledge Mapping: Periodically generates Mermaid-based maps to visualize mastered concepts versus pending dependencies.
- Bilingual Term Preservation: Intelligent logic that keeps technical terms, APIs, and UI names in their original language while providing explanatory prose in the user's primary tongue.
- Automated Weekly Reports: Generates a comprehensive summary of study time, completion rates, and mood trends via Sunday evening push notifications.
SKILL.md
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