EESJGong

EESJGong / scholar-skill

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An OpenClaw skill for academic reading, knowledge linking, reflection, and knowledge evolution in Obsidian.

academic-reading agent-workflow knowledge-management obsidian openclaw-skill
16
4
100% credibility
Found Mar 21, 2026 at 16 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

ScholarSkill is an OpenClaw skill designed to create structured, interconnected academic knowledge workflows within Obsidian vaults, supporting paper reading, knowledge extraction, cognitive updates, and critical thinking in English or Chinese.

How It Works

1
📚 Discover ScholarSkill

You stumble upon ScholarSkill, a helpful companion for turning academic papers into a smart, growing knowledge system inside your Obsidian notes app.

2
Pick Your Language
🇺🇸
English

Go with English templates and guides for your notes.

🇨🇳
Chinese

Select Chinese templates and guides for your notes.

3
🧠 Ask Your AI Helper to Set It Up

Simply tell your AI assistant to install it and connect to your Obsidian notes folder, and it handles the rest.

4
✨ Your Notes App Transforms

New organized folders and ready-to-use note templates appear in your Obsidian vault, making everything feel structured and inviting.

5
🔗 Grab Extra Helpers

Your AI adds a few companion tools for fetching papers, reading files, and keeping things smooth.

6
📖 Feed It a Paper

Share a paper link or file, pick your reading depth, and let it create structured notes, insights, and connections.

🌟 Your Knowledge Evolves

Papers turn into linked ideas, old notes update with new insights, and your Obsidian vault becomes a living web of deep understanding.

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Star Growth

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AI-Generated Review

What is scholar-skill?

Scholar-skill is a Python OpenClaw skill that transforms academic paper reading into an evolving knowledge system inside Obsidian. Drop in a paper or arXiv link, and it generates structured notes at levels L1 (quick scan), L2 (deep read), or L3 (critical analysis), extracting semantic/episodic/procedural memories while linking to your existing vault concepts, MOCs, and insights. It solves the dump-of-summaries problem by enabling knowledge updates, reflections, and verifications that keep your research base sharp over time.

Why is it gaining traction?

Unlike basic summarizers, it builds a networked Obsidian vault with auto-consolidation, human-confirmation triggers for conflicts, and scheduled reflections—turning isolated reads into a durable workflow. Bilingual English/Chinese support, one-command ClawHub installs for deps like obsidian-direct and arxiv-watcher, and agent-friendly setup via "openclaw skills list" make it dead simple for OpenClaw users eyeing the openclaw github repo. Early openclaw github stars hint at niche appeal among PKM tinkerers.

Who should use this?

PhD students or researchers drowning in papers, especially those already on Obsidian for Zettelkasten-style vaults. AI-assisted academics wanting to batch-process queues, revise old notes with new evidence, or track evolving topics like LLMs or world models. Obsidian power-users integrating OpenClaw for hands-off literature reviews.

Verdict

Worth starring and testing if you're in OpenClaw+Obsidian—solid docs and setup scripts lower the barrier despite 16 stars and 1.0% credibility signaling early-stage testing. Polish deps installs and L3 depth before production workflows.

(198 words)

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