SK

skill-from-notebook

Extracts methodologies from external content to generate reusable AI agent skills.

Install

mkdir -p .claude/skills/skill-from-notebook && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/2718" && unzip -o skill.zip -d .claude/skills/skill-from-notebook && rm skill.zip

Installs to .claude/skills/skill-from-notebook

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Extract methodologies from documents or examples to create executable skills
76 charsno explicit “when” trigger
Intermediate

Key capabilities

  • Extract methodologies from documents
  • Reverse engineer workflows from finished artifacts
  • Identify teaching patterns in instructional content
  • Generate structured skill templates
  • Perform multi-example analysis for generalizable skills

How it works

The skill identifies the input type as either a methodology document or a finished example, then applies specific extraction paths to deduce actionable steps, quality criteria, and reusable techniques.

Inputs & outputs

You give it
Source document or example artifact
You get back
Structured executable skill template

When to use skill-from-notebook

  • Turn technical blog into a skill
  • Extract workflow from PDF
  • Reverse engineer methodology from example
  • Convert docs to executable steps

About this skill

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

TypeHow to Process
Local filesPDF, Word, Markdown - Read directly
Web URLWebFetch to extract content
YouTubeUse yt-dlp for subtitles, Whisper if unavailable
NotebookLM linkBrowser automation to extract notes/summaries
Example/OutputReverse 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

TypeCharacteristicsExamples
How-toClear step sequence, input→outputDeploy Docker, Configure CI/CD
DecisionConditions, trade-offs, choicesChoose database, Select framework
FrameworkMental model, analysis dimensionsSWOT, 5W1H, First Principles
ChecklistVerification list, pass/fail criteriaCode 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?

DimensionQuestions
StructureHow is content organized?
StyleTone, word choice, expression?
TechniqueWhat methods make it effective?
LogicHow does information flow?
DetailsSmall 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

When not to use it

  • Summarizing documents
  • Converting file formats
  • Generating content without actionable methodology

Prerequisites

Access to source materials like PDFs, articles, or code

Limitations

  • Requires content with clear goal or process indicators
  • Not suitable for unstructured or non-methodological content

How it compares

Unlike a general summarizer, this skill focuses on reverse-engineering the production process to create a repeatable, executable task structure.

Compared to similar skills

skill-from-notebook side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
skill-from-notebook (this skill)26moNo flagsIntermediate
prompt-optimize139moNo flagsAdvanced
ai-cost-optimizer95moCautionIntermediate
self-improving-agent121moReviewIntermediate

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