Oh My OpenCode is a multi-model agent orchestration harness for OpenCode. It transforms a single AI agent into a coordinated development team that actually ships code.
Or read the full [Installation Guide](./installation.md) for manual setup, provider authentication, and troubleshooting.
### Your First Task
Once installed, just type:
```
ultrawork
```
That's it. The agent figures everything out — explores your codebase, researches patterns, implements the feature, verifies with diagnostics. Keeps working until done.
Want more control? Press **Tab** to enter [Prometheus mode](./orchestration.md) for interview-based planning, then run `/start-work` for full orchestration.
This isn't about making Claude Code better. It's about breaking free from the idea that one model, one provider, one way of working is enough. Anthropic wants you locked in. OpenAI wants you locked in. Everyone wants you locked in.
Oh My OpenCode doesn't play that game. It orchestrates across models, picking the right brain for the right job. Claude for orchestration. GPT for deep reasoning. Gemini for frontend. Haiku for quick tasks. All working together, automatically.
└─→ [Category-based agents] — Specialized by task type
```
When Sisyphus delegates to a subagent, it doesn't pick a model name. It picks a **category** — `visual-engineering`, `ultrabrain`, `quick`, `deep`. The category automatically maps to the right model. You touch nothing.
For a deep dive into how agents collaborate, see the [Orchestration System Guide](./orchestration.md).
Sisyphus is your main orchestrator. He plans, delegates to specialists, and drives tasks to completion with aggressive parallel execution. He doesn't stop halfway. He doesn't get distracted. He finishes.
Sisyphus has Claude-optimized prompts. No GPT prompt exists for Sisyphus. Claude-family models work best because that's what the prompts were engineered for.
Named with intentional irony. Anthropic blocked OpenCode from using their API because of this project. So the team built an autonomous GPT-native agent instead.
Hephaestus runs on GPT-5.3 Codex. Give him a goal, not a recipe. He explores the codebase, researches patterns, and executes end-to-end without hand-holding. He is the legitimate craftsman because he was born from necessity, not privilege.
Use Hephaestus when you need deep architectural reasoning, complex debugging across many files, or cross-domain knowledge synthesis. Switch to him explicitly when the work demands GPT-5.3 Codex's particular strengths.
- **Multi-model orchestration.** Pure Codex is single-model. OmO routes different tasks to different models automatically. GPT for deep reasoning. Gemini for frontend. Haiku for speed. The right brain for the right job.
- **Background agents.** Fire 5+ agents in parallel. Something Codex simply cannot do. While one agent writes code, another researches patterns, another checks documentation. Like a real dev team.
- **Category system.** Tasks are routed by intent, not model name. `visual-engineering` gets Gemini. `ultrabrain` gets GPT-5.3 Codex. `quick` gets Haiku. No manual juggling.
- **Accumulated wisdom.** Subagents learn from previous results. Conventions discovered in task 1 are passed to task 5. Mistakes made early aren't repeated. The system gets smarter as it works.
Prometheus interviews you like a real engineer. Asks clarifying questions. Identifies scope and ambiguities. Builds a detailed plan before a single line of code is touched.
Read-only high-IQ consultant for architecture decisions and complex debugging. Consult Oracle when facing unfamiliar patterns, security concerns, or multi-system tradeoffs.
The agent figures everything out. Explores your codebase. Researches patterns. Implements the feature. Verifies with diagnostics. Keeps working until done.
Prometheus interviews you like a real engineer. Asks clarifying questions. Identifies scope and ambiguities. Builds a detailed plan before a single line of code is touched.
Then run `/start-work` and Atlas takes over. Tasks are distributed to specialized subagents. Each completion is verified independently. Learnings accumulate across tasks. Progress tracks across sessions.
Models are auto-configured at install time. The interactive installer asks which providers you have, then generates optimal model assignments for each agent and category.
At runtime, fallback chains ensure work continues even if your preferred provider is down. Each agent has a provider priority chain. The system tries providers in order until it finds an available model.
- GPT-5.3-codex — deep coding powerhouse, required for Hephaestus
- GPT-5.2 — high intelligence, default for Oracle
- GPT-5-Nano — ultra-cheap, fast utility tasks
**Different-behavior models**:
- Gemini 3 Pro — excels at visual/frontend tasks
- MiniMax M2.5 — fast and smart for utility tasks
- Grok Code Fast 1 — optimized for code grep/search
See the [Agent-Model Matching Guide](./agent-model-matching.md) for complete details on which models work best for each agent, safe vs dangerous overrides, and provider priority chains.
---
## Why It's Better Than Pure Claude Code
Claude Code is good. But it's a single agent running a single model doing everything alone.
Oh My OpenCode turns that into a coordinated team:
**Parallel execution.** Claude Code processes one thing at a time. OmO fires background agents in parallel — research, implementation, and verification happening simultaneously. Like having 5 engineers instead of 1.
**Hash-anchored edits.** Claude Code's edit tool fails when the model can't reproduce lines exactly. OmO's `LINE#ID` content hashing validates every edit before applying. Grok Code Fast 1 went from 6.7% to 68.3% success rate just from this change.
**Intent Gate.** Claude Code takes your prompt and runs. OmO classifies your true intent first — research, implementation, investigation, fix — then routes accordingly. Fewer misinterpretations, better results.
**LSP + AST tools.** Workspace-level rename, go-to-definition, find-references, pre-build diagnostics, AST-aware code rewrites. IDE precision that vanilla Claude Code doesn't have.
**Skills with embedded MCPs.** Each skill brings its own MCP servers, scoped to the task. Context window stays clean instead of bloating with every tool.
**Discipline enforcement.** Todo enforcer yanks idle agents back to work. Comment checker strips AI slop. Ralph Loop keeps going until 100% done. The system doesn't let the agent slack off.
**The fundamental advantage.** Models have different temperaments. Claude thinks deeply. GPT reasons architecturally. Gemini visualizes. Haiku moves fast. Single-model tools force you to pick one personality for all tasks. Oh My OpenCode leverages them all, routing by task type. This isn't a temporary hack — it's the only architecture that makes sense as models specialize further. The gap between multi-model orchestration and single-model limitation widens every month. We're betting on that future.
---
## The Intent Gate
Before acting on any request, Sisyphus classifies your true intent.
Are you asking for research? Implementation? Investigation? A fix? The Intent Gate figures out what you actually want, not just the literal words you typed. This means the agent understands context, nuance, and the real goal behind your request.
Claude Code doesn't have this. It takes your prompt and runs. Oh My OpenCode thinks first, then acts.
