AutoDev vs goose
Side-by-side comparison of two AI agent tools
Short answer
- goose is growing faster: +3,352 GitHub stars in the last 30 days vs +22 for AutoDev.
- Pick AutoDev for: AutoDev: the AI-native Multi-Agent development platform built on Kotlin Multiplatform, covering all 7 phases. Pick goose for: an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test.
From GitHub data refreshed daily.
AutoDevopen-source
🧙AutoDev: the AI-native Multi-Agent development platform built on Kotlin Multiplatform, covering all 7 phases of SDLC.
gooseopen-source
an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM
Metrics
| AutoDev | goose | |
|---|---|---|
| Stars | 4.6k | 54.9k |
| Star velocity /mo | 22.105263157894736 | 3.4k |
| Commits (90d) | 1 | 805 |
| Releases (6m) | 0 | 10 |
| Overall score | 0.3893208015242423 | 0.8821825173304099 |
Pros
- +基于Kotlin Multiplatform的统一架构，实现真正的写一次到处运行
- +覆盖SDLC全部7个阶段的专业化AI代理，提供端到端开发支持
- +支持8个以上平台的原生体验，包括主流IDE、桌面、移动和Web端
- +支持任何LLM模型且可多模型配置，灵活性极高
- +能够自主完成端到端开发任务，不仅仅是代码建议
- +开源架构支持自定义扩展和MCP服务器集成
Cons
- -3.0版本仍处于Alpha阶段，可能存在稳定性问题
- -iOS平台功能仍在生产就绪阶段，可能功能不够完整
- -作为多平台解决方案，可能在某些特定平台上的体验不如专门为该平台优化的工具
- -需要本地安装和配置，对新手用户可能有一定门槛
- -作为自主代理执行任务时可能需要用户监督和验证结果
Use Cases
- •大型软件项目需要统一的跨平台开发体验和完整生命周期管理
- •分布式团队成员使用不同操作系统和开发环境时的协作开发
- •希望在移动端进行代码审查或轻量级开发任务的移动办公场景
- •从零开始构建完整项目原型，包括代码编写和测试
- •对现有代码库进行重构和优化改进
- •管理复杂的工程流水线和自动化开发工作流
FAQ
- Which is more popular, AutoDev or goose?
- goose has more GitHub stars (54,890 vs 4,551).
- Which is more actively developed, AutoDev or goose?
- goose had more commits in the last 90 days (805 vs 1).
- Should I use AutoDev or goose?
- Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.