Oh My OpenAgent
Open-source multi-agent orchestration framework that coordinates specialized AI coders across planning, execution, and verification.
Pick Oh My OpenAgent if you want a configurable, model-agnostic multi-agent harness layered on OpenCode or Codex CLI for autonomous coding runs.
Skip it if you want a hosted, point-and-click coding agent or a single-model assistant without CLI setup and multi-provider API keys.
Oh My OpenAgent (omo) is an open-source agent harness for software development that splits work across 11 specialized agents and routes each task to the model best suited for it. It ships in two editions, a full OpenCode build and a lighter Codex CLI build, and exposes a Team Mode that runs up to 8 agents in parallel, with session continuity via a 'boulder.json' resume file and 60+ lifecycle hooks for customization.
It is aimed at developers who want more structure than a single chat-style coding agent and don't mind wiring a config-heavy harness around their existing CLI. The signature 'Ultra Work' (ulw) mode kicks off autonomous multi-step runs that separate planning from execution and then independently verify the result. Pricing isn't published on the site because the framework itself is free under the SUL-1.0 license; you pay only the underlying model providers.
Under the hood it brokers between Claude Opus 4.7 Max for orchestration, plus Sonnet 4.6, multiple GPT 5.5 variants, Gemini 3.1 Pro, and others depending on the task category. There's no hosted SaaS or REST API — it's a local framework you install on top of OpenCode or Codex CLI, so usability depends on how comfortable you are managing model keys and CLI tooling.
A serious attempt at a real orchestration layer rather than another chat wrapper — the plan/execute/verify split and per-category model routing are the right ideas. It's CLI-first and assumes you'll bring keys for Claude, GPT, and Gemini, so it's squarely for developers, not casual users.
— The AI Tool Bible editorial team
Pros
- ✅ Routes tasks to model best suited per category instead of one-size-fits-all
- ✅ Parallel Team Mode runs up to 8 agents at once
- ✅ Plan/execute/verify separation reduces single-agent drift
- ✅ Open source under SUL-1.0 with extensive hook system
- ✅ Session resumption via boulder.json keeps long runs recoverable
Cons
- ⚠️ No hosted product — local CLI install with config overhead
- ⚠️ Requires paid API keys from multiple model providers to use fully
- ⚠️ Documentation and ecosystem still young compared to mainstream agents
Use cases
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