"[具体任务] top performer"
"[具体任务] how the best do it"
"[具体任务] real example from [top company]"
"[角色] who is the best at [任务]"
"[具体任务] interview with [practitioner]"
"[具体任务] behind the scenes"
目标:找到3-5个实践中公认做得好的真实案例。
识别实践专家的信号:
有具体的成果/数据("成交率提升X%"、"客户满意度最高")
被同行认可("团队里大家都学他")
有真实的案例细节,不是泛泛的原则
对于每个黄金案例,记录:
这个人具体是怎么做的?
和普通人做法有什么不同?
有什么具体的细节让他做得更好?
2.2 找失败案例(什么是做得差的)⚠️ 同样重要
搜索策略:
"[具体任务] common mistakes"
"[具体任务] what not to do"
"[具体任务] fails"
"[具体任务] I learned the hard way"
"[具体任务] before after comparison"
"why [具体任务] doesn't work"
目标:找到常见的失败模式和踩过的坑。
对于每个失败案例,记录:
具体做错了什么?
为什么这样做是无效的?
应该怎么做才对?
2.3 找对比(有效 vs 无效)
搜索策略:
"[具体任务] good vs bad example"
"[具体任务] before after"
"[具体任务] do this not that"
"[具体任务] comparison"
"[task] real example"
"[task] case study"
"[task] common mistakes"
"[task] what not to do"
"[task] before after"
"[task] I learned the hard way"
"how [company] does [task]"
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.
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
Download the skill-from-masters folder
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]
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.