gaotiexinqu

gaotiexinqu / OneResearchClaw

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Any research. One Claw. 🦞 From any materials to research with fully autonomous & skill-driven researcher.

agentic-systems ai-agents ai-for-science autonomous-research cursor-ai
16
2
100% credibility
Found Apr 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

OneResearchClaw is an AI workflow that converts diverse inputs like meeting recordings, documents, tables, slides, archives, and online links into structured research reports via automated processing, literature search, quality review, and multi-format export.

How It Works

1
🔍 Discover OneResearchClaw

You find this handy tool on GitHub that turns everyday notes, meeting recordings, papers, and links into clear research reports.

2
📦 Set it up easily

Follow simple steps to download and prepare everything so your files can be processed right away.

3
📁 Gather your materials

Pick audio from meetings, documents, spreadsheets, slides, zipped folders, or links to papers and videos.

4
🚀 Start in your AI helper

Open Cursor, load the main guide, add your file and choices like research depth or output style, and hit go.

5
⚡ Watch the transformation

It organizes your stuff, finds supporting papers, checks for quality, and builds everything into a solid report.

6
📤 Choose your formats

Pick how you want results like readable text, printable PDFs, slide decks, or even audio versions.

🎉 Enjoy your reports

You now have professional, well-researched reports ready to share, present, or archive without the hassle.

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Star Growth

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AI-Generated Review

What is OneResearchClaw?

OneResearchClaw is a Python-based autonomous researcher that turns scattered inputs like meeting audio/video, PDFs, tables, PPTs, ZIP archives, or links to arXiv papers, YouTube videos, or any GitHub repo into structured research reports. It handles any research article PDF, any research paper download, or even any GitHub project link by grounding content, searching literature, reviewing drafts, and exporting to MD, DOCX, PDF, PPTX, or audio. Developers get controllable depth (simple/medium/complex) and multi-topic splitting without manual preprocessing.

Why is it gaining traction?

It stands out by automating the full pipeline from raw materials to polished, reviewed reports with query confirmation and multi-model review loops, skipping the tedium of keyword extraction or lit review drudgery. The skill-evolve feature adapts to user feedback over time, and one-click cloud ingestion works for any research topic or GitHub URL. Early adopters hook on the zero-handoff workflow for complex inputs like mixed ZIPs or long meetings.

Who should use this?

Academic researchers synthesizing any research paper or proposal PDF, R&D teams turning group meeting videos into topic-specific reports, or devs prototyping on any GitHub project needing quick lit surveys. Ideal for those drowning in nonhuman subject lab data or diet studies requiring scrutiny.

Verdict

Promising alpha for autonomous claw workflows (16 stars, 1.0% credibility), with solid docs and showcase cases, but low maturity means expect rough edges in edge cases. Try for personal lit reviews if you're Cursor-savvy; skip for production until tests stabilize.

(198 words)

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