trapoom555

trapoom555 / claude-paperloom

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Claude Code Plugin for Self-maintaining research knowledge graph for Claude Code + Obsidian

claude-code claude-code-plugin knowledge-graph obsidian research-data-management
17
3
100% credibility
Found Apr 27, 2026 at 17 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
JavaScript
AI Summary

A Claude Code plugin that ingests research papers into an Obsidian vault, generating structured summaries, atomic findings, metadata, quality scores, and typed relationships to build a self-maintaining knowledge graph.

How It Works

1
📚 Discover PaperLoom

You hear about a handy tool that turns scattered research papers into a connected map of ideas, perfect for keeping track of what you read.

2
🤖 Add to your AI helper

You easily add the tool to your AI chat assistant so it can help manage your papers.

3
📂 Set up your research notebook

You create a simple folder on your computer where all your paper notes will live and grow.

4
🔗 Drop in a paper link

You paste a paper's web address, ID, or file into the chat, and tell your AI to add it.

5
✨ Magic happens

Your AI reads the paper, writes a smart summary with critique, pulls out key claims, and links them to your existing notes – all automatically.

6
📱 Open your notes app

You open the folder in your favorite notes app to see the new paper page, findings, and connections.

🌐 Explore your knowledge web

You now have a beautiful, growing map of papers, authors, ideas, and links that helps you see how everything connects – ready for more papers anytime.

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Star Growth

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AI-Generated Review

What is claude-paperloom?

Claude-paperloom is a Claude Code plugin that turns research papers into a self-maintaining knowledge graph inside an Obsidian vault. Feed it a URL, arXiv ID, DOI, or PDF via simple slash commands like `/paperloom:ingest` or `/paperloom:init`, and it fetches the paper, generates a 4-section summary (including a model-powered critique), extracts atomic claims as standalone nodes, scores quality metrics, and wires typed connections like "supports," "contradicts," or "extends" across your library. Built in JavaScript with Python scripts for processing, it leverages Claude models (or local Ollama) for constant-cost linking that scales without exploding token bills.

Why is it gaining traction?

It stands out by delivering Obsidian-native graphs with pre-built Dataview queries for contradictions, high-credibility papers, or by-author views—no custom apps or lock-in. Unlike manual note-taking or basic PDF importers, it auto-matches citations deterministically, surfaces cross-paper conflicts bidirectionally, and keeps ingest to just 4 LLM calls per paper. Developers dig the CLI-like slash commands in Claude Code and free local model support, making claude code install straightforward without pricing surprises.

Who should use this?

ML researchers tracking arXiv dumps for lit reviews, AI engineers building personal wikis of related work, or academics synthesizing fields like NLP. Ideal if you're already in the Claude Code + Obsidian ecosystem and tired of copy-pasting abstracts without connections.

Verdict

Worth a spin for Claude Code users wanting automated paper graphs—solid README and docs make claude code docs easy to follow, with commands like `/paperloom:query` for synthesis. At 17 stars and 1.0% credibility, it's early and unproven; test on a small vault before committing.

(198 words)

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