What you can build with OMA.
Runnable recipes straight from the repo — each framed by the problem it solves. Browse by what you want to build, then open the source.
Recipes for real problems.
End-to-end scripts built around a concrete task, not a single primitive — open the source to see how the patterns compose on a real workflow.
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).
Works with your stack.
A library, not a platform — it composes with the protocols, servers, and frameworks already in your backend.
Primitives, patterns, and providers.
The lower-level pieces the cookbook composes — start here if you're learning the API or comparing models.
End-to-end, production-grade use cases — a higher bar, with tests and pinned models. See the contribution criteria to add one.
Generated at build time from the repo's packages/core/examples tree, so it always matches
the source. Browse all on GitHub→