✨Data Intelligence Lab@HKU✨
@hkuds • Open source projects from hkuds. Use this route to separate flagship concentration from portfolio breadth before you treat a publisher as broadly strong.
Portfolio concentration
50%
Top three share
Shows whether the organization is driven by one breakout repo or several visible projects.
Breadth
30 repos
Visible snapshot
20 repositories updated in the last 90 days.
Leading language
Python
Portfolio mix
Python (25), TypeScript (3), Shell (1)
Average size
8.2K
Stars per repository
Useful for distinguishing one flagship-heavy publisher from a repeatable portfolio.
Updated: 2026-07-03(26d ago)GitHub API fallback30 repositories
50%
of the visible star count comes from this organization's top three repositories.
8.2K
stars per repository in this same snapshot.
Python
is the most common language here, with 20 repositories updated in the last 90 days.
Why this rank
This organization stands out because its public portfolio is relatively balanced across 30 repositories.
Balanced portfolio across 30 reposTop 3 share 50%
Organization pages work best when you separate portfolio breadth from flagship concentration. In ✨Data Intelligence Lab@HKU✨'s case, the visible top three repositories account for about 50% of total stars in this snapshot, which helps explain whether the organization is known for one breakout project or for a broader repeatable portfolio.
The dominant language mix here is Python (25), TypeScript (3), Shell (1). That makes this page useful not just for popularity checks, but also for seeing what technical shape an organization's public ecosystem actually has.
Top Repositories
| # | Repository | Language | Stars | 🍴 Forks | Updated |
|---|---|---|---|---|---|
| 1 | hkuds/nanobot Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat apps | Python | 46.4K | 8.2K | Today |
| 2 | hkuds/CLI-Anything "CLI-Anything: Making ALL Software Agent-Native" -- CLI-Hub: https://clianything.cc/ | Python | 46.3K | 4.3K | 2 weeks ago |
| 3 | hkuds/DeepTutor DeepTutor: Lifelong Personalized Tutoring. https://deeptutor.info/. | Python | 31.1K | 4.1K | Today |
| 4 | hkuds/Vibe-Trading "Vibe-Trading: Your Personal Trading Agent" | Python | 28.6K | 4.6K | Today |
| 5 | hkuds/RAG-Anything "RAG-Anything: All-in-One RAG Framework" | Python | 22.5K | 2.6K | 1 weeks ago |
| 6 | hkuds/AI-Trader "AI-Trader: 100% Fully-Automated Agent-Native Trading" | Python | 21.1K | 3.2K | 1 months ago |
| 7 | hkuds/OpenHarness "OpenHarness: Open Agent Harness with a Built-in Personal Agent--Ohmo!" | Python | 15.1K | 2.4K | 1 months ago |
| 8 | hkuds/ClawWork "ClawWork: OpenClaw as Your AI Coworker - 💰 $15K earned in 11 Hours" | Python | 8.3K | 1.1K | 4 months ago |
| 9 | hkuds/OpenSpace "OpenSpace: The Skill Management Layer for AI Agents" -- https://open-space.cloud/ | Python | 7.2K | 869 | 2 days ago |
| 10 | hkuds/ClawTeam "ClawTeam: Agent Swarm Intelligence" (One Command → Full Automation) | Python | 5.5K | 757 | 2 months ago |
| 11 | hkuds/Paper2Slides "Paper2Slides: From Paper to Presentation in One Click" | Python | 3.8K | 474 | 2 months ago |
| 12 | hkuds/FastCode "FastCode: Accelerating and Streamlining Your Code Understanding" | Python | 2.3K | 275 | 3 weeks ago |
| 13 | hkuds/VideoAgent "VideoAgent: All-in-One Agentic Framework for Video Understanding, Editing, and Remaking" | Python | 1.6K | 217 | 1 weeks ago |
| 14 | hkuds/OpenOPC OpenOPC: Build Your Personal AI-Native Company — Self-Built, Self-Run, Self-Grown | Python | 1K | 169 | Yesterday |
| 15 | hkuds/OpenPhone [ACL 2026] "OpenPhone: Mobile Agentic Foundation Models for AI Phone" | Python | 936 | 183 | 2 weeks ago |
| 16 | hkuds/AgentSpace "AgentSpace: Human + Agents. One Team. One Workspace" | TypeScript | 890 | 124 | 5 days ago |
| 17 | hkuds/AnyTool "AnyTool: Universal Tool-Use Layer for AI Agents" | Python | 681 | 95 | 5 months ago |
| 18 | hkuds/LightReasoner [ACL 2026 Oral] "LightReasoner: Can Small Language Models Teach Large Language Models Reasoning?" | Python | 604 | 35 | 2 months ago |
| 19 | hkuds/CatchMe "CatchMe: Make Your AI Agents Truly Personal" | Python | 429 | 71 | 1 months ago |
| 20 | hkuds/DeepInnovator "DeepInnovator: AI Research Assistant - Idea Spark & Scientific Discovery" | Python | 279 | 59 | 4 months ago |
| 21 | hkuds/MoChat "MoChat: OpenClaw as Your Social Agent https://mochat.io" | TypeScript | 230 | 51 | 5 months ago |
| 22 | hkuds/FutureShow "FutureShow: Can AI Predict the Future? Live Real-World Forecasting" | Python | 175 | 26 | 6 months ago |
| 23 | hkuds/Litewrite "Litewrite: Vibe Writing is Coming - Write Faster and Better! https://litewrite.ai" | TypeScript | 159 | 21 | 5 months ago |
| 24 | hkuds/UpSkill Upskill your model: Flash price. Pro performance. | Shell | 89 | 14 | 3 days ago |
| 25 | hkuds/FastAgent "FastAgent: Simple, Fast, and Strong LLM Agents" | Python | 60 | 19 | 5 months ago |
| 26 | hkuds/RecGPT [EMNLP2025] "RecGPT: A Foundation Model for Sequential Recommendation" | Python | 59 | 8 | 9 months ago |
| 27 | hkuds/MGP Memory Governance Protocol | Python | 57 | 11 | 1 weeks ago |
| 28 | hkuds/DeepResearch-Eval "DeepResearch-Eval: An End-to-End Evaluation Framework for DeepResearch Systems" | Python | 50 | 12 | 9 months ago |
| 29 | hkuds/AutoMemory Build the memory your agent actually needs — automatically. | Python | 20 | 1 | 3 weeks ago |
| 30 | hkuds/AI-Researcher-Gallery | 5 | 0 | 1 years ago |
Next step after the organization read
Open a flagship repository, compare a couple of portfolio leaders, or return to the organization map when you want a broader concentration read.
Learn and methodology
Keep trust-building context reachable, but behind the first data read instead of ahead of it.
How to read this organization snapshot
Total stars are useful as a discovery signal, but they do not tell you whether a team maintains every repository equally. Pair this page with release cadence, maintainer activity, and the flagship concentration shown above before making adoption decisions.
For broader background on GitStar's ranking logic and editorial guidance, see Methodology & Editorial Standards.