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Skill From Notebook

This extracts actionable methodologies from documents or examples and turns them into reusable skills. Feed it a tutorial on code reviews or a guide on technical writing, and it'll pull out the steps and criteria. Feed it a polished blog post or proposal, and it'll reverse engineer what made it good and give you a template to create similar work. The two-path approach is smart: it treats "how to" content differently from finished examples. Think of it as the bridge between NotebookLM-style understanding and actually doing the thing repeatedly. Works with PDFs, URLs, YouTube videos, even NotebookLM links. Honestly most useful when you find yourself wanting to replicate a process but the original source is scattered or implicit.

skills.sh installs
372
GitHub stars
1.6K
last updated
Aug 21, 2026

Install

$ npx -y skills add gbsoss/skill-from-masters --skill skill-from-notebook --agent claude-code

Installs into .claude/skills of the current project.

Files

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:

Sponsors

Details

Repository
github.com/gbsoss/skill-from-masters
Category
Data Science & ML
First seen
Jun 3, 2026

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