ScholarSkill

Parse scholarly papers into interlinked Obsidian knowledge with extracted memories.

216|19|Updated Mar 19, 2026
One-click install
npx skills add https://github.com/EESJGong/scholar-skill --skill scholarskill
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ScholarSkill
Source: https://github.com/EESJGong/scholar-skill/tree/main/zh-CN
Command: npx skills add https://github.com/EESJGong/scholar-skill --skill scholarskill

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires arxiv-watcher, academic-research-hub, obsidian-direct, obsidian-cli, tavily, pdf, durable-task-runner, and includes scripts (resource) components.

What problem does it solve?

Bridges the gap between reading scholarly papers and building a durable, navigable knowledge base inside Obsidian, turning scattered notes into a structured, searchable memory system.

Core Features & Use Cases

  • L3 reading & memory extraction within Obsidian to produce deep notes and reusable insights.
  • Knowledge maps and bidirectional links to connect new papers with existing notes and MOCs.
  • Memory consolidation & reflection workflows to maintain an evolving, auditable understanding over time.

Quick Start

Install ScholarSkill, point it at your Obsidian vault, and run auto-configuration to initialize your workspace.

Frequently Asked Questions about ScholarSkill

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I convert scholarly papers into interlinked Obsidian knowledge?

To convert scholarly papers into interlinked Obsidian knowledge, ScholarSkill parses PDFs and extracts semantic, episodic, and procedural memories to build structured notes and MOCs. It bridges reading and durable knowledge consolidation by creating bidirectional links across your vault.

What is the best way to track arxiv papers and build a knowledge map in Obsidian?

Tracking arxiv papers and building a knowledge map in Obsidian is achieved by using the arxiv-watcher dependency alongside memory extraction. ScholarSkill monitors new papers, parses the content, and automatically generates bidirectional links and MOCs to connect new findings with existing notes.

Can I use this Skill to extract memories from academic PDFs for long-term research?

Yes, you can extract memories from academic PDFs for long-term research. ScholarSkill performs L1/L2/L3 reading to extract deep semantic, episodic, and procedural memories, supporting ongoing knowledge consolidation and reflection workflows for auditable understanding.

Does ScholarSkill require a specific Obsidian setup to create MOCs?

ScholarSkill requires an Obsidian vault initialized through its auto-configuration process to create MOCs. It relies on obsidian-direct and obsidian-cli dependencies to manage the workspace, write durable notes, and establish bidirectional links directly within your existing environment.

How do I handle long-running PDF parsing tasks for academic reading?

To handle long-running PDF parsing tasks for academic reading, ScholarSkill optionally utilizes the durable-task-runner dependency. This component manages extended background workflows, ensuring deep L3 reading and memory extraction processes complete without timing out.

Why use ScholarSkill instead of standard Obsidian plugins for knowledge management?

ScholarSkill offers specialized memory extraction and cross-paper connection workflows that standard Obsidian knowledge management plugins lack. It integrates arxiv monitoring, structured L1/L2/L3 reading, and automated MOC creation to maintain an evolving, auditable research knowledge base.