Portfolio concentration
97%
Top three share
Shows whether the organization is driven by one breakout repo or several visible projects.
Breadth
30 repos
Visible snapshot
19 repositories updated in the last 90 days.
Leading language
Python
Portfolio mix
Python (9), Unknown (7), Go (3)
Average size
830
Stars per repository
Useful for distinguishing one flagship-heavy publisher from a repeatable portfolio.
97%
of the visible star count comes from this organization's top three repositories.
830
stars per repository in this same snapshot.
Python
is the most common language here, with 19 repositories updated in the last 90 days.
Why this rank
This organization stands out because one flagship repo drives 92% of its visible star count.
Organization pages work best when you separate portfolio breadth from flagship concentration. In Alibaba's case, the visible top three repositories account for about 97% 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 (9), Unknown (7), Go (3). That makes this page useful not just for popularity checks, but also for seeing what technical shape an organization's public ecosystem actually has.
| # | Repository | Language | Stars |
|---|---|---|---|
| 1 | alibaba/open-code-review Fast, efficient, battle-tested at Alibaba's scale. Hybrid architecture code review tool: deterministic pipelines + LLM Agent, precise line-level comments, built-in multi-language ruleset (NPE, thread-safety, XSS, SQL injection), OpenAI & Anthropic compatible. | Go | 22.8K |
| 2 | alibaba/skill-up An evaluation and evolution tool for Agent Skills. | Go | 892 |
| 3 | alibaba/UnifiedModel The semantic layer that makes enterprise data understandable to AI agents — model entities and relations once, query through SPL/MCP/REST, and connect telemetry, services, and business objects in one object graph. | Go | 375 |
| 4 | alibaba/loongsuite-pilot Local-first telemetry collector for AI coding agents — unified OpenTelemetry events for Claude Code, Codex, Cursor and more. Token usage, cost, traces and security audit, exported anywhere. | TypeScript | 182 |
| 5 | alibaba/neug The one data index for your agentic applications | C++ | 149 |
| 6 | alibaba/atrex-kernel-agent An end-to-end agent project for GPU kernel implementation, analysis, profiling, and iterative optimization. It helps an agent turn PyTorch logic or an existing kernel into a high-performance GPU kernel through a structured, profile-driven workflow. | Python | 110 |
| 7 | alibaba/OmniDoc-TokenBench | Python | 71 |
| 8 | alibaba/MobiZen-GUI | Python | 48 |
| 9 | alibaba/webmcp-nexus 面向 WebMCP 标准的非侵入式前端集成套件:写一个普通 TS 函数加一段 JSDoc,即可被任意 MCP 客户端调用 —— 含 SDK、Vite/Webpack 插件与 AI 编码 Skill。 | TypeScript | 41 |
| 10 | alibaba/atrex-bench End-to-end benchmark for AI-generated GPU kernels, drawn from real production traces — turn a PyTorch reference into a DSL kernel (Triton, Gluon, FlyDSL, CuteDSL) and grade it on compilation, numerical correctness, and speed-of-light efficiency, on both AMD and NVIDIA GPUs. | Python | 29 |
| 11 | alibaba/obz-cli Multi-backend observability CLI for metrics, logs, and traces — unified interface, AI-Agent friendly | Rust | 27 |
| 12 | alibaba/tron-one-agent | Java | 26 |
| 13 | alibaba/loongsuite-js OpenTelemetry instrumentation plugins for JavaScript-based AI coding agents. Collect traces, tool calls, and LLM metrics from Claude Code and OpenClaw — zero code changes required. | TypeScript | 24 |
| 14 | alibaba/loongsuite-semantic-conventions-genai Loongsuite GenAI Semantic Conventions | Open Policy Agent | 19 |
| 15 | alibaba/dag-frame | C++ | 13 |
| 16 | alibaba/EfficientRL Official repository for ICML 2026 paper "Long Live The Balance: Information Bottleneck Driven Tree-based Policy Optimization" | 11 | |
| 17 | alibaba/CA-TTS | Python | 11 |
| 18 | alibaba/AILens Full-stack observability for AI — starting with end-to-end RL post-training, expanding to Agent and inference engine monitoring. | Python | 9 |
| 19 | alibaba/harbor Harbor is a framework for running agent evaluations and creating and using RL environments.(Fork for contributing. All changes intended for upstream PRs.) | Python | 7 |
| 20 | alibaba/AIprofiling | Rust | 6 |
| 21 | alibaba/UniGate | 5 | |
| 22 | alibaba/verl-recipe A set of examples based on verl for end-to-end RL training recipes.(Fork for contributing. All changes intended for upstream PRs.) | Python | 5 |
| 23 | alibaba/utp | HTML | 4 |
| 24 | alibaba/ray Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.((Fork for contributing. All changes intended for upstream PRs.)) | 4 | |
| 25 | alibaba/slime slime is an LLM post-training framework for RL Scaling.(Fork for contributing. All changes intended for upstream PRs.) | Python | 4 |
| 26 | alibaba/complex-mcp | 2 | |
| 27 | alibaba/FlagTree FlagTree is a unified compiler supporting multiple AI chip backends for custom Deep Learning operations(Fork for contributing. All changes intended for upstream PRs.) | 2 | |
| 28 | alibaba/isa-l Intelligent Storage Acceleration Library(Fork for contributing. All changes intended for upstream PRs.) | C | 1 |
| 29 | alibaba/OSWorld [NeurIPS 2024] OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments(Fork for contributing. All changes intended for upstream PRs.) | 1 | |
| 30 | alibaba/aiconfigurator Offline optimization of your disaggregated Dynamo graph(Fork for contributing. All changes intended for upstream PRs.) | 0 |
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.