Does it support active recall learning?

Yes, it generates at least 8 practice problems per topic and uses collapsed markdown tags to hide answers, forcing you to recall information before checking.

How does it handle large files?

For large PDFs (over 100MB), the skill uses CLI tools to extract text efficiently in chunks, ensuring it can handle comprehensive technical manuals without performance issues.

How does this differ from the standard 'study' skill?

While the standard study skill is designed for interactive, deep-dive conversations, Study Vault is optimized for speed and bird's-eye views, generating a complete set of notes and practice problems first.

Can I generate notes for specific chapters only?

Yes, you can provide an argument hint such as '[book-name] Ch3-Ch5' to limit the vault generation to specific sections of a source.

What sources can Study Vault analyze?

Study Vault can process local book PDFs, web URLs (such as technical articles or documentation), and GitHub repository links to extract and structure information.

Study Vault - Technical Learning Assistant

Name: Study Vault - Technical Learning Assistant
Author: lsh1215

bylsh1215

•

Learning & Documentation

Generates structured, first-principles-based study notes and interactive practice vaults from books, documentation, or GitHub repositories.

Study Vault is a specialized learning tool for Claude Code that transforms dense technical material into organized, searchable knowledge bases. It analyzes sources like PDFs, web pages, and code repositories to create a comprehensive 'Study Vault' featuring hierarchical topic maps, concept comparisons, and active recall practice problems. By focusing on the structural 'why' behind concepts rather than just definitions, it helps developers and students gain a high-level architectural understanding of complex systems before diving into deep-dive study sessions.

Key Features

01Concept Comparison: Creates detailed matrices to distinguish between easily confused technical terms and patterns.

028 GitHub stars

03First Principles Analysis: Explains concepts by focusing on the core problems they solve and their design trade-offs.

04Cross-Linked Knowledge: Automatically connects related concepts with bidirectional links for non-linear browsing.

05Automated Topic Hierarchy: Extracts structure from PDFs, URLs, or repos to build a logical learning map.

06Active Recall Practice: Generates categorized practice problems with hidden answers to strengthen memory retention.

Use Cases

01Summarizing long technical documentation URLs into a categorized reference dashboard with quick-lookup tables.

02Onboarding to a complex GitHub repository by generating an architectural overview and internal study guide.

03Converting technical book PDFs into a structured digital vault for exam preparation or certification review.

Key Features

01Concept Comparison: Creates detailed matrices to distinguish between easily confused technical terms and patterns.

028 GitHub stars

03First Principles Analysis: Explains concepts by focusing on the core problems they solve and their design trade-offs.

04Cross-Linked Knowledge: Automatically connects related concepts with bidirectional links for non-linear browsing.

05Automated Topic Hierarchy: Extracts structure from PDFs, URLs, or repos to build a logical learning map.

06Active Recall Practice: Generates categorized practice problems with hidden answers to strengthen memory retention.

Use Cases

01Summarizing long technical documentation URLs into a categorized reference dashboard with quick-lookup tables.

02Onboarding to a complex GitHub repository by generating an architectural overview and internal study guide.

03Converting technical book PDFs into a structured digital vault for exam preparation or certification review.