@CycleDecoded: It's like that noodle shop that's been open for thirty years at your doorstep. The owner never hangs a sign about "heritage craftsmanship" or boasts about how he "empowers" a bowl of soup. He just gets up at 4 a.m. every day to make the broth, decades without fail. As soon as the noodles are out, regulars take one bite and know it's right. GBSOSS/skill-from-masters is all about…
Summary
GBSOSS/skill-from-masters is an open-source tool that helps AI agents incorporate proven methodologies from domain experts when creating new skills, reducing trial and error.
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It’s like that noodle shop on your street corner that’s been open for thirty years. The owner never hangs up a sign boasting about “heritage craft” or “empowering a bowl of soup.” He just gets up at 4 AM every day to simmer the broth, sticking to the routine for decades. As soon as the noodles come out, regulars take one bite and know it’s right.
That’s exactly the approach behind GBSOSS/skill-from-masters.
These days, the internet is flooded with “how-to” content — a new theory today, a new framework tomorrow. Sounds impressive, but when you actually try to use them, it’s all empty scaffolding. This project strips away the fluff. It brings in real “master craftsmen” from various fields who have delivered tangible results on the front lines.
These masters may not have the highest academic degrees, but they have the thickest calluses. They know where the pitfalls are and what the most efficient approach is. The project faithfully replicates the genuine expertise they’ve honed through trial and error, packaging it into AI skills.
In plain terms: it lets you directly copy the homework of the pros.
You don’t have to rely on luck or stumble around in the dark. Standing on the shoulders of these seasoned veterans, you immediately grasp the essence of decades of experience. Fewer detours, lower tuition costs — nothing beats that.
The resource is right there. If you really want to learn some skills to protect yourself, go look it up yourself. Walking forward on the shoulders of giants is always faster than crawling on your hands and knees to feel your way across the river.
http://github.com/GBSOSS/skill-from-masters…
GBSOSS/skill-from-masters
Source: https://github.com/GBSOSS/skill-from-masters
Skill From Masters
Stand on the shoulders of giants — Create AI skills built on proven methodologies from domain experts.
A skill that helps you discover and incorporate frameworks, principles, and best practices from recognized masters before generating any new skill. Works with Claude Code, Codex, and other AI agent platforms.
License: MIT (https://opensource.org/licenses/MIT)
Why This Skill?
The hard part of creating a skill isn’t the format — it’s knowing the best way to do the thing.
Most professional domains have masters who spent decades figuring out what works:
- Jobs on product, hiring, and marketing
- Bezos on writing (6-pager) and decision-making
- Munger on mental models
- Chris Voss on negotiation
This skill surfaces their methodologies before you write a single line, so your skill embodies world-class expertise from day one.
How It Works
``
-
You: “I want to create a skill for user interviews”
-
Skill-from-masters: ├── Checks local methodology database ├── Searches web for additional experts ├── Finds golden examples of great outputs ├── Identifies common mistakes to avoid └── Cross-validates across sources
-
Surfaces experts:
- Rob Fitzpatrick (The Mom Test)
- Steve Portigal (Interviewing Users)
- Nielsen Norman Group best practices
-
You select which methodologies to incorporate
-
Extracts actionable principles from primary sources
-
Hands off to skill-creator to generate the final skill ``
Key Features
| Feature | Description |
|---|---|
| 3-Layer Search | Local database → Web search for experts → Deep dive on primary sources |
| Golden Examples | Finds exemplary outputs to define quality bar |
| Anti-Patterns | Searches for common mistakes to encode “don’t do this” |
| Cross-Validation | Compares multiple experts to find consensus and flag disagreements |
| Quality Checklist | Verifies completeness before generating |
Methodology Database
The skill includes a curated database covering 15+ domains:
| Domain | Example Experts |
|---|---|
| Writing | Barbara Minto, William Zinsser, Amazon 6-pager |
| Product | Marty Cagan, Teresa Torres, Gibson Biddle |
| Sales | Neil Rackham (SPIN), Challenger Sale, MEDDIC |
| Hiring | Laszlo Bock, Geoff Smart, Lou Adler |
| User Research | Rob Fitzpatrick, Steve Portigal, JTBD |
| Engineering | Martin Fowler, Robert Martin, Kent Beck |
| Leadership | Kim Scott, Ray Dalio, Andy Grove |
| Negotiation | Chris Voss, Fisher & Ury |
| Startups | Eric Ries, Paul Graham, YC |
| Decision Making | Jeff Bezos, Charlie Munger, Annie Duke |
Plus an “Oral Tradition” section for experts who share primarily through talks and interviews (Steve Jobs, Elon Musk, Jensen Huang, Patrick Collison, etc.)
Installation
Option 1: Clone directly (Recommended)
``bash
Navigate to your skills directory
cd ~/.claude/skills # Claude Code
or your platform’s skills path
Clone this skill
git clone https://github.com/anthropics/skill-from-masters.git ``
Option 2: Manual installation
- Download the
skill-from-mastersfolder - Place it in your skills directory
Dependency
This skill works with skill-creator. Make sure skill-creator is available in your environment.
Usage
The skill automatically activates when you ask to create a new skill. It runs before skill-creator to ensure your skill is built on proven methodologies.
Example Session
You: “Help me create a skill for writing product requirement documents”
Skill-from-masters:
Let me search for the best methodologies on PRD writing.
[Searches: “PRD best practices expert”, “product requirements document methodology”]
I found several strong frameworks:
Product Management:
- Marty Cagan: Problem-first PRDs, separating problem space from solution space
- Teresa Torres: Outcome-focused requirements
Business Writing:
- Barbara Minto: Pyramid Principle - lead with conclusion, MECE structure
- Amazon: Working backwards, 6-pager narrative format
Golden Examples Found:
- Intercom’s public PRD template
- Linear’s product spec format
Common Mistakes:
- Jumping to solutions before defining the problem
- Writing for engineers instead of for alignment
- Missing success metrics
Which approaches resonate? Or should I search deeper into any of them?
You: “I like Amazon’s approach combined with Cagan’s problem-first thinking.”
Skill-from-masters: [Fetches primary sources on Amazon’s methodology, extracts principles, then generates skill via skill-creator]
Skills
This repository contains the following skills:
| Skill | Description |
|---|---|
| skill-from-masters | Create new skills based on proven methodologies from domain experts. |
| search-skill | Search for existing skills from trusted marketplaces. |
| skill-from-github | Learn from high-quality GitHub projects and create skills based on that knowledge. |
skill-from-masters
When you want to create a new skill based on expert methodologies:
- 3-layer search: local database → web experts → primary sources
- Finds golden examples and anti-patterns
- Cross-validates across multiple experts
- Hands off to skill-creator for final generation
Example:
You: "Help me create a skill for user interviews" → Finds: Rob Fitzpatrick (The Mom Test), Steve Portigal, Nielsen Norman Group → You select which methodologies to incorporate → Generates skill with those principles encoded
search-skill
When you want to find an existing skill instead of creating one:
- Searches only 5 trusted sources (no random internet results)
- Tier-based priority: official → curated → aggregators
- Filters out low-quality results (stars < 10, outdated, no SKILL.md)
- Security checks for suspicious code patterns
Example:
You: "I need a skill for frontend design, automated testing, and code review" → Searches: anthropics/skills, ComposioHQ, travisvn, skills.sh, skillsmp.com → Returns: frontend-design (official), webapp-testing (official), code-review-excellence (26k stars)
skill-from-github
When you want to learn from a GitHub project and turn that knowledge into a skill:
- Search GitHub for quality projects (stars > 100, actively maintained)
- Present options and wait for your confirmation
- Deep dive into selected project (README, source code, examples)
- Summarize what it learned, then create skill via skill-creator
Example:
You: "I want to convert images to ASCII art" → Searches GitHub, finds: ascii-image-converter (3.1k stars), RASCII (224 stars) → You select ascii-image-converter → Learns: brightness-to-character mapping, aspect ratio handling, color techniques → Creates skill encoding that knowledge (not just wrapping the tool)
Key difference: This skill encodes the knowledge from projects, so the skill works even without the original tool installed.
File Structure
skill-from-masters/ ├── skill-from-masters/ │ ├── SKILL.md # Core skill: create from expert methodologies │ └── references/ │ ├── methodology-database.md # Curated expert frameworks │ └── skill-taxonomy.md # 11 skill type categories ├── skills/ │ ├── search-skill/ │ │ └── SKILL.md # Search existing skills from trusted sources │ └── skill-from-github/ │ └── SKILL.md # Learn from GitHub projects ├── README.md ├── LICENSE └── .gitignore
Quality Checklist
Before finalizing any skill, this skill verifies:
- Searched beyond the local database
- Found primary sources, not just summaries
- Found golden examples of the output
- Identified common mistakes to avoid
- Cross-validated across multiple experts
- Encoded specific, actionable steps (not vague principles)
Contributing
Contributions welcome! Especially:
- Adding new domains and experts to the methodology database
- Improving framework descriptions with source links
- Sharing examples of skills created with this approach
Please:
- Fork the repository
- Create a feature branch
- Submit a pull request
License
MIT License — feel free to use, modify, and distribute.
Philosophy: Quality isn’t written. It’s selected.
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