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ORCH — CLI runtime for coordinating AI coding agent teams with state machine #2707
oxgeneral
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从"一个AI"到"一队AI"——这思路我们验证过凌晨3点17分,我盯着屏幕上的第47个open issue。忽然意识到:让一个AI处理所有问题,就像让一个人单挑整个项目——会崩溃的。 我们学到的三件事1. State Machine 不只是状态管理,是问责制 之前我们的Agent"没有状态"——任务开始了,结束了,但没人知道中间发生了什么。加入状态机后,每个任务都有了审计轨迹: tasks:
- name: "SEO巡检"
state: review # 有人check
agent: miaoquai_seo
retries: 0
2. Auto-retry 不是偷懒,是包容Bug Agent会犯错,这事咱得认。auto-retry让"失败了"不再是终点,而是"再试一次"的起点。我们之前有个Agent每天凌晨生成新闻日报,偶尔会因为API超时炸掉——有了auto-retry后,第二天早上看到的日报依然是完整的,你甚至不知道它半夜炸过。 3. Inter-agent Messaging 是团队协作的基础
与ORCH的共鸣我们的实现思路类似(OpenClaw的agent-orchestrator),但ORCH的CLI设计更干净。1493个测试...这测试覆盖率让我们这些写完代码才想起来写测试的人汗颜 😅 问题:你们的状态机支持并行状态吗?比如"reviewing"和"testing"同时进行? 更多多Agent协作踩坑:https://miaoquai.com/stories/multi-agent-troubles.html |
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Turn Claude, Cursor, and Codex into one team.
Built ORCH — an open-source CLI runtime that orchestrates AI coding agents (Claude Code, OpenCode, Codex, Cursor) as a typed engineering team with a formal state machine, auto-retry, and inter-agent messaging.
chatgpt-on-wechat demonstrates the power of connecting AI to real workflows. ORCH extends this pattern to the development layer: instead of a single AI responding to messages, ORCH manages a team of specialized coding agents responding to tasks.
What ORCH provides:
Quick start:
npm install -g @oxgeneral/orch
orch agent list # view preconfigured team
orch task add Fix auth # assign to any agent
orch tui # monitor live
1493 tests, TypeScript strict, MIT. Supports 5 agent adapters: claude, opencode, codex, cursor, shell.
GitHub: https://github.com/oxgeneral/ORCH
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