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.

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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

1. You: "I want to create a skill for user interviews"

2. 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

3. Surfaces experts:
   - Rob Fitzpatrick (The Mom Test)
   - Steve Portigal (Interviewing Users)
   - Nielsen Norman Group best practices

4. You select which methodologies to incorporate

5. Extracts actionable principles from primary sources

6. 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)

# 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

1. Download the skill-from-masters folder
2. 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:

1. Fork the repository
2. Create a feature branch
3. Submit a pull request

License

MIT License — feel free to use, modify, and distribute.

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Philosophy: Quality isn't written. It's selected.