oh-my-openagent (OmO) is an open-source agent harness that sits above multiple AI coding tools and routes tasks to the most suitable model automatically. Previously known as oh-my-opencode, it rebranded in early 2026 to reflect its expanded model support: Claude Code, OpenCode, Codex, Kimi K2, DeepSeek V4, Gemini CLI, and more. The core insight is that different coding tasks have different optimal model-cost tradeoffs — high-complexity refactoring benefits from Claude Opus 4.7, while high-volume file generation runs cheaper on DeepSeek V4-Flash. OmO automates that routing decision. 53,900 GitHub stars and a growing plugin ecosystem. MIT licensed, installed via npm, works on macOS, Windows, and Linux.
oh-my-openagent (OmO) solves a different problem from single-model harnesses like GStack: instead of making one model work better, it routes each task to the best model available. As frontier model costs diverge — GPT-5.5 output at $30/M vs DeepSeek V4-Flash at $0.28/M — the efficiency case for automatic routing has grown substantially.
OmO sits above your existing coding tools. It does not replace Claude Code or OpenCode; it coordinates them, deciding which model gets each task based on configurable routing rules.
OmO’s agent-model-matching configuration lets you define task categories and model preferences:
Routing decisions can be explicit (task keyword triggers a specific model) or learned (OmO observes which models succeed on similar tasks and adjusts weights).
npm install -g oh-my-openagent
omo setup # Configure model API keys and routing preferencesFor teams with mixed workloads, OmO’s routing typically reduces costs 40–60% compared to running all tasks through a single frontier model. The savings compound when combined with caching — tasks routed to DeepSeek V4-Pro with warm cache see approximately 10× lower costs than the equivalent Claude Opus 4.7 call.
GStack and OmO solve adjacent but different problems. GStack makes Claude Code more structured — adding specialist reviewer roles, a security audit step, and parallel Conductor sessions. OmO makes your AI coding infrastructure more efficient by routing tasks across models. Many developers use both: GStack’s skills for structured Claude Code workflows, OmO for cost-efficient routing of volume tasks. They are complementary, not competing.
Development teams running multiple AI coding tools who want to optimize cost without sacrificing capability. Particularly valuable for teams with high AI usage volume where the per-token cost differential between frontier models matters at scale. Also useful for developers who need flexibility across models — particularly for teams where certain workloads require OpenAI API access alongside Anthropic.
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