jiangmuran

jiangmuran / noterx

Public

13岁中学生团队 | 自训练量化预测模型 + 评论画像引擎 + 5 AI Agent 多轮辩论，诊断你的小红书笔记为什么没火 在线体验/研究成果→ noterx.muran.tech

noterx.muran.tech redhackathon
41
3
100% credibility
Found Apr 10, 2026 at 41 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

NoteRx is an AI diagnostic tool for Xiaohongshu notes that uses multiple specialized agents to score content quality, visuals, growth strategies, and predicted user reactions with actionable suggestions.

How It Works

1
🌐 Discover NoteRx

You stumble upon this friendly tool that helps everyday creators make their social media posts shine brighter.

2
📱 Upload your post

Drag in screenshots or a quick video of your note, and everything loads up smoothly.

3
🤖 AI magic fills in details

Watch the smart assistant instantly spot your title, text, tags, and even guess the category to save you time.

4
✏️ Tweak if needed

Glance over the suggestions and make any quick changes to feel just right.

5
🚀 Start the deep check

Tap go, and a team of helpful AI experts dives in to review content, visuals, growth tips, and user vibes.

6
📊 See your personalized report

Get clear scores across key areas, smart suggestions, fake comments, and even improved versions to try.

🎉 Boost your next post

Use the insights to refine your content and post with excitement, knowing it'll connect better with readers.

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Star Growth

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AI-Generated Review

What is noterx?

NoteRx is a Python web app that diagnoses why your Xiaohongshu (Little Red Book) posts flop. Upload title, text, images, or video screenshots—pick a category like food or fashion—and it runs five AI agents through a debate to score content, visuals, growth tactics, and user reactions against baselines from 874 real notes. Get radar charts, fix suggestions, simulated comments, and an optimized rewrite; try it live at noterx.muran.tech.

Why is it gaining traction?

It stands out with data-backed baselines and agent-style LLM orchestration—like agent github copilot but tuned for social virality, handling OCR on screenshots, video analysis via MiMo, and multi-round agent debates for balanced advice. Devs dig the full-stack setup (FastAPI backend, React frontend) as a github agent repo template, blending quantitative models with Claude-compatible prompting. Niche focus on Xiaohongshu gives it edge over generic copilot vscode extensions or agent github action workflows.

Who should use this?

Xiaohongshu creators tweaking food recipes, fashion hauls, or travel itineraries for more likes. Python devs building agent github claude pipelines or agent github copilot cli alternatives for content tools. Marketers reverse-engineering viral posts without manual A/B testing.

Verdict

Grab it for Xiaohongshu optimization experiments—impressive student-built agent at 41 stars, though 1.0% credibility signals early maturity with thin tests. Fork the github agent repo for your LLM agent projects; production needs more polish.

(187 words)

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