PigeonDan1

PigeonDan1 / paper_claw

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Paper Claw sends personalized daily research digests from arXiv and beyond straight to your inbox, featuring customizable categories, intelligent classification, and agent-based multilingual summaries powered by your preferred AI via private API. Designed for researchers and AI agents, it makes paper discovery easier, smarter, and more specialized.

agent-skills agentic-framework agentic-workflow
16
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100% credibility
Found Mar 12, 2026 at 13 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

Paper Claw fetches recent arXiv papers from chosen research categories, classifies and summarizes them using AI, and sends personalized daily email digests in multiple languages.

How It Works

1
📖 Discover Paper Claw

You stumble upon this friendly tool that grabs the latest research papers in your favorite topics and turns them into easy daily summaries.

2
🔍 Pick your topics

Choose areas like speech recognition or computer vision so it only brings papers that match what excites you.

3
📧 Set your email

Add your email address (and friends') to get these handy digests delivered right to your inbox.

4
🤖 Add a smart summarizer

Connect a helpful AI brain to make the paper overviews super clear and insightful in your preferred language.

5
🚀 Run your first digest

Press go to fetch today's papers, sort them neatly, summarize, and send a test email.

6
⏰ Schedule daily magic

Set it to run every morning automatically so fresh updates arrive without you lifting a finger.

📨 Inbox full of insights

Every day, open your email to beautifully organized summaries of new papers, saving you hours of hunting.

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Star Growth

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AI-Generated Review

What is paper_claw?

Paper Claw is a Python tool that pulls fresh arXiv papers from your chosen categories, classifies them intelligently, generates multilingual AI summaries using providers like DeepSeek, Kimi, or OpenAI, and emails you a polished daily digest. It solves the hassle of manually scanning recent papers by delivering personalized overviews right to your inbox, complete with readability scores and key insights. Run it locally via CLI with `python main.py --day YYYY-MM-DD`, schedule via GitHub Actions, or integrate as an agent skill.

Why is it gaining traction?

It stands out with dead-simple JSON config for 170+ arXiv categories, auto-fallback across multiple LLMs if one flakes, and seven-language support including Chinese and Japanese—perfect for global researchers. The agent-friendly skill interface lets AI workflows fetch or send digests in one line, and GitHub Actions setup means zero server hassle. Developers dig the private API focus, avoiding public rate limits.

Who should use this?

PhD students or researchers in NLP, CV, speech, or ML tracking daily arXiv drops without RSS overload. Lab leads sending team digests on custom topics like "cs.CL + cs.LG". AI agent builders needing a plug-and-play paper copilot for workflows.

Verdict

Worth forking for niche arXiv monitoring—excellent READMEs with examples and configs make setup fast, despite 13 stars and 1.0% credibility signaling early maturity. Test locally before production; add your tweaks via the paper github link.

(187 words)

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