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skill-from-notebook

by @gbsossv1.0.0
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Extract methodologies from documents or examples to create executable skills

Jupyter NotebooksAI Model DevelopmentCode GenerationAI Engineering WorkflowData ScienceGitHub
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npx skills add gbsoss/skill-from-masters --skill skill-from-notebook
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name: skill-from-notebook description: Extract methodologies from documents or examples to create executable skills model: sonnet

Skill from Notebook

Extract actionable methodologies from learning materials (documents, articles, videos) or quality examples (blog posts, designs, code) to generate reusable Skills.

Core Philosophy: NotebookLM helps you understand. This skill helps you do.

When to Use

When users want to turn knowledge into executable skills:

  • "I just read this article about code review, help me create a skill from it"
  • "Here's a great technical blog post, extract the writing methodology"
  • "Turn this PDF guide into a skill I can reuse"
  • "Learn from this example and create a skill to produce similar output"

Supported Input Types

| Type | How to Process | |------|----------------| | Local files | PDF, Word, Markdown - Read directly | | Web URL | WebFetch to extract content | | YouTube | Use yt-dlp for subtitles, Whisper if unavailable | | NotebookLM link | Browser automation to extract notes/summaries | | Example/Output | Reverse engineer the methodology |

Step 0: Identify Input Type

Critical first step - Determine which processing path to use:

User Input
    │
    ├─ Has teaching intent? ("how to", "steps", "guide")
    │   └─ YES → Path A: Methodology Document
    │
    ├─ Is a finished work? (article, design, code, proposal)
    │   └─ YES → Path B: Example (Reverse Engineering)
    │
    └─ Neither? → Tell user this content is not suitable

Path A indicators (Methodology Document):

  • Contains words like "how to", "steps", "method", "guide"
  • Has numbered lists or step sequences
  • Written with teaching intent
  • Describes "what to do"

Path B indicators (Example/Output):

  • Is a complete work/artifact
  • No teaching intent
  • Is "the thing itself" rather than "how to make the thing"
  • Examples: a well-written blog post, a polished proposal, a code project

Path A: Extract from Methodology Document

A1: Validate Document Suitability

Check if the document is suitable for skill generation (must meet at least 2):

  • [ ] Has clear goal/outcome
  • [ ] Has repeatable steps/process
  • [ ] Has quality criteria
  • [ ] Has context/scenario description

If not suitable: Tell user honestly and explain why.

A2: Identify Skill Type

| Type | Characteristics | Examples | |------|-----------------|----------| | How-to | Clear step sequence, input→output | Deploy Docker, Configure CI/CD | | Decision | Conditions, trade-offs, choices | Choose database, Select framework | | Framework | Mental model, analysis dimensions | SWOT, 5W1H, First Principles | | Checklist | Verification list, pass/fail criteria | Code review checklist, Launch checklist |

A3: Extract Structure by Type

For How-to:

  • Prerequisites
  • Step sequence (with expected output per step)
  • Final expected result
  • Common errors

For Decision:

  • Decision factors
  • Options with pros/cons
  • Decision tree/flowchart
  • Recommended default

For Framework:

  • Core concepts
  • Analysis dimensions
  • Application method
  • Limitations

For Checklist:

  • Check items with criteria
  • Priority levels
  • Commonly missed items

A4: Generate Skill

Use this template:

## Applicable Scenarios
[When to use this skill]

## Prerequisites
- [What's needed before starting]

## Steps
1. [Step 1] - [Expected outcome]
2. [Step 2] - [Expected outcome]
...

## Quality Checkpoints
- [ ] [Checkpoint 1]
- [ ] [Checkpoint 2]

## Common Pitfalls
- [Pitfall 1]: [How to avoid]

## Source
- Document: [name/URL]
- Extracted: [timestamp]

Path B: Reverse Engineer from Example

When input is a finished work (not a tutorial), reverse engineer the methodology.

B1: Identify Output Type

What kind of artifact is this?

  • Technical blog post
  • Product proposal/PRD
  • Academic paper
  • Code architecture
  • Design document
  • Other: [specify]

B2: Analyze Structure

Break down the example:

Structure Analysis:
├── [Part 1]: [Function] - [Proportion %]
├── [Part 2]: [Function] - [Proportion %]
├── [Part 3]: [Function] - [Proportion %]
└── [Part N]: [Function] - [Proportion %]

Questions to answer:

  • How many parts does it have?
  • What's the function of each part?
  • What's the order and proportion?

B3: Extract Quality Characteristics

What makes this example good?

| Dimension | Questions | |-----------|-----------| | Structure | How is content organized? | | Style | Tone, word choice, expression? | | Technique | What methods make it effective? | | Logic | How does information flow? | | Details | Small but important touches? |

B4: Reverse Engineer the Process

Deduce: To create this output, what steps are needed?

## Deduced Production Steps
1. [Step 1]: [What to do] - [Key point]
2. [Step 2]: [What to do] - [Key point]
...

## Key Decisions
- [Decision 1]: [Options] - [This example chose X because...]

## Reusable Techniques
- [Technique 1]: [How to apply]
- [Technique 2]: [How to apply]

B5: Generate Skill

Use this template for reverse-engineered skills:

## Output Type
[What kind of artifact this produces]

## Applicable Scenarios
[When to create this type of output]

## Structure Template
1. [Part 1]: [Function] - [~X%]
2. [Part 2]: [Function] - [~X%]
...

## Quality Characteristics (Learned from Example)
- [Characteristic 1]: [How it manifests]
- [Characteristic 2]: [How it manifests]

## Production Steps
1. [Step 1]: [What to do] - [Tips]
2. [Step 2]: [What to do] - [Tips]
...

## Checklist
- [ ] [Check item 1]
- [ ] [Check item 2]

## Reference Example
- Source: [name/URL]
- Analyzed: [timestamp]

Example: Path A (Methodology Document)

User: "Extract a skill from this article about writing good commit messages"

Process:

  1. Read the article
  2. Identify: This is a How-to type (has steps, teaching intent)
  3. Extract:
    • Goal: Write clear, useful commit messages
    • Steps: Use conventional format, separate subject/body, etc.
    • Quality criteria: Subject < 50 chars, imperative mood, etc.
  4. Generate skill with steps and checklist

Example: Path B (Reverse Engineering)

User: "Here's a great technical blog post. Learn from it and create a skill for writing similar posts."

Process:

  1. Identify: This is an example (finished work, no teaching intent)
  2. Analyze structure:
    ├── Hook: Real pain point (2-3 sentences)
    ├── Problem: 3 sentences on the core issue
    ├── Solution: Conclusion first, then details
    ├── Code: Each snippet < 20 lines, with comments
    ├── Pitfalls: 3 common errors
    └── Summary: One-line takeaway
    
  3. Extract quality characteristics:
    • Title = specific tech + problem solved
    • One idea per paragraph
    • Code:text ratio ~40:60
    • Personal anecdotes for credibility
  4. Reverse engineer steps:
    • Start with a real problem you solved
    • Write the solution first, then the setup
    • Add code samples progressively
    • etc.
  5. Generate skill: "How to Write a Technical Blog Post"

Advanced: Multi-Example Learning

When user provides multiple examples of the same type:

Example A ──┐
Example B ──┼──> Extract commonalities ──> Core methodology
Example C ──┘           │
                        ▼
                  Analyze differences ──> Style variants / Optional techniques

This produces more robust, generalizable skills.


Important Notes

  1. Always validate first - Not all content is suitable for skill extraction
  2. Identify the path early - Methodology doc vs Example require different approaches
  3. Be specific - Vague skills are useless; include concrete steps and criteria
  4. Preserve the source - Always credit where the knowledge came from
  5. Ask for clarification - If unsure about user intent, ask before proceeding
  6. Quality over speed - Take time to truly understand the content

What This Skill is NOT

  • NOT a summarizer (that's NotebookLM's job)
  • NOT a document converter
  • It's about extracting actionable methodology that can be repeatedly executed

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版本1.0.0
更新日期2026年3月17日
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创建2026年3月17日
最后更新2026年3月17日