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TrendingMomentumPulseExplore
  1. Home
  2. Organizations
  3. ✨Data Intelligence Lab@HKU✨
✨Data Intelligence Lab@HKU✨Organization

✨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

51%

Top three share

Shows whether the organization is driven by one breakout repo or several visible projects.

Breadth

30 repos

Visible snapshot

17 repositories updated in the last 90 days.

Leading language

Python

Portfolio mix

Python (24), TypeScript (4), Shell (1)

Average size

8.9K

Stars per repository

Useful for distinguishing one flagship-heavy publisher from a repeatable portfolio.

Back to organizationsCompare repositories
Updated: 2026-08-17(22d ago)GitHub API fallback30 repositories

Portfolio Shape

51%

of the visible star count comes from this organization's top three repositories.

Average Repository Size

8.9K

stars per repository in this same snapshot.

Current Mix

Python

is the most common language here, with 17 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 51%

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 51% 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 (24), TypeScript (4), 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.

Source: GitHub API fallback. This is the same cache-first snapshot used by the organization ranking list, so the summary view and the detail view should stay aligned.

Top Repositories

#RepositoryLanguageStars🍴 ForksUpdated
1hkuds/CLI-Anything

"CLI-Anything: Making ALL Software Agent-Native" -- CLI-Hub: https://clianything.cc/

Python49.1K4.5K2 weeks ago
2hkuds/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

Python47.9K8.4KToday
3hkuds/DeepTutor

DeepTutor: Lifelong Personalized Tutoring. https://deeptutor.info/.

Python39K4.9KToday
4hkuds/Vibe-Trading

"Vibe-Trading: Your Personal Trading Agent"

Python33K5.4KToday
5hkuds/RAG-Anything

"RAG-Anything: All-in-One RAG Framework"

Python23.3K2.7K5 days ago
6hkuds/AI-Trader

"AI-Trader: 100% Fully-Automated Agent-Native Trading"

Python22.2K3.4K2 months ago
7hkuds/OpenHarness

"OpenHarness: Open Agent Harness with a Built-in Personal Agent--Ohmo!"

Python15.7K2.6K3 months ago
8hkuds/ClawWork

"ClawWork: OpenClaw as Your AI Coworker - 💰 $15K earned in 11 Hours"

Python8.5K1.1K6 months ago
9hkuds/OpenSpace

"OpenSpace: The Skill Management Layer for AI Agents" -- https://open-space.cloud/

Python7.5K9123 weeks ago
10hkuds/ClawTeam

"ClawTeam: Agent Swarm Intelligence" (One Command → Full Automation)

Python5.5K7594 months ago
11hkuds/Paper2Slides

"Paper2Slides: From Paper to Presentation in One Click"

Python3.8K4753 months ago
12hkuds/FastCode

"FastCode: Accelerating and Streamlining Your Code Understanding"

Python2.3K2762 months ago
13hkuds/VideoAgent

[EMNLP2026] "VideoAgent: All-in-One Agentic Framework for Video Understanding and Editing, and Remaking"

Python1.9K2381 months ago
14hkuds/OpenOPC

OpenOPC: Build Your Personal AI-Native Company — Self-Built, Self-Run, Self-Grown

Python1.6K2983 days ago
15hkuds/AgentSpace

"AgentSpace: Human + Agents. One Team. One Workspace"

TypeScript9761311 months ago
16hkuds/OpenPhone

[ACL 2026] "OpenPhone: Mobile Agentic Foundation Models for AI Phone"

Python9711841 months ago
17hkuds/AnyTool

"AnyTool: Universal Tool-Use Layer for AI Agents"

Python686936 months ago
18hkuds/LightReasoner

[ACL 2026 Oral] "LightReasoner: Can Small Language Models Teach Large Language Models Reasoning?"

Python610343 months ago
19hkuds/CatchMe

"CatchMe: Make Your AI Agents Truly Personal"

Python496812 months ago
20hkuds/DeepInnovator

"DeepInnovator: AI Research Assistant - Idea Spark & Scientific Discovery"

Python289596 months ago
21hkuds/MoChat

"MoChat: OpenClaw as Your Social Agent https://mochat.io"

TypeScript231506 months ago
22hkuds/FutureShow

"FutureShow: Can AI Predict the Future? Live Real-World Forecasting"

Python173257 months ago
23hkuds/Litewrite

"Litewrite: Vibe Writing is Coming - Write Faster and Better! https://litewrite.ai"

TypeScript158206 months ago
24hkuds/UpSkill

Upskill your model: Flash price. Pro performance.

Shell91151 months ago
25hkuds/MGP

Memory Governance Protocol

Python59111 months ago
26hkuds/FastAgent

"FastAgent: Simple, Fast, and Strong LLM Agents"

Python58197 months ago
27hkuds/DeepResearch-Eval

"DeepResearch-Eval: An End-to-End Evaluation Framework for DeepResearch Systems"

Python511210 months ago
28hkuds/HELIX

Helix's mission: optimize harnesses for models, then automatically turn harness-generated rollouts into trainable agent data.

TypeScript3353 weeks ago
29hkuds/AutoMemory

Build the memory your agent actually needs — automatically.

Python2412 months ago
30hkuds/AI-Researcher-Gallery501 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.
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Learn and methodology

Keep trust-building context reachable, but behind the first data read instead of ahead of it.
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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.