用 OMA 能搭出什么。
直接来自仓库、可直接运行的实例——每一个都围绕它解决的问题来组织。按你想搭的东西浏览，然后打开源码。
面向真实问题的实例。
围绕一个具体任务、而非单个原语写成的端到端脚本——打开源码，看这些模式如何在真实工作流里组合。
Parallel source monitoring (Twitter/Reddit/News), contradiction detection, and aggregated intelligence reporting.
4-task DAG (extract → compliance-check + summary → notify) with step-level retry. Run normally or with FORCE_FAIL=task2 to exercise retry.
5-task DAG with three parallel root tasks (log patterns + deploy correlation + blast radius) feeding root-cause hypothesis and final postmortem synthesis.
Fan-out post-processing of a transcript into summary, structured action items, and sentiment.
Multi-source hint arbitration with an external safety veto that sits outside the generation loop.
Multi-source paper replication triage with artifact discovery, seeded conflicts, and a structured go/no-go plan.
Interactive interviewer loop with observer flags, shared memory, and structured debrief.
Source-isolated rare disease information triage with mock fixtures, seeded misinformation/conflict detection, and safety-boundary arbitration.
Translate → back-translate with a different provider → flag semantic drift (cross-model).
与你的技术栈协同。
它是库，不是平台——与你后端里已有的协议、服务器和框架组合使用。
原语、模式与提供方。
Cookbook 所组合的那些更底层的零件——如果你在学 API 或在对比模型，从这里开始。
端到端、生产级的用例——更高的门槛，带测试、锁定模型。想加一个，先看贡献标准。
在构建时从仓库的 packages/core/examples 目录生成，所以它始终与源码一致。在 GitHub 上浏览全部→