oh-my-opencode-slim

✨ oh-my-opencode-slim ✨

Seven divine beings emerged from the dawn of code, each an immortal master of their craft,
awaiting your command to forge order from chaos and build what was once thought impossible.

Opencode Multi Agent Suite · Mix any models · Auto delegate tasks

_{by Boring Dystopia Development}

     

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oh-my-opencode-slim is an agent orchestration plugin for OpenCode. It includes a built-in team of specialized agents that can scout a codebase, look up fresh documentation, review architecture, handle UI work, and execute well-scoped implementation tasks under one orchestrator.

The main idea is simple: instead of forcing one model to do everything, the plugin routes each part of the job to the agent best suited for it, balancing quality, speed and cost.

To explore the agents themselves, see Meet the Pantheon. For the full feature set, see Features & Workflows below.

“Task management went from 5/10 to 8-9/10 easily. The Orchestrator sends Fixers and Explorers, and I can still talk and plan with the Orchestrator in the same session. The experience feels way smoother now.”

- vipor_idk

“I ditched all my harnesses for this beta version of omo-slim and don't look back or miss anything. Great work and IMHO all in the right direction.”

- stephanschielke

“I love omo-slim, and can't imagine running opencode without it. I love that I can create a Frankenstein of models... Makes the setup such a beast.”

- Capital-One3039

“It has significantly improved my workflow... Now, it is working very smoothly, and I love it.”

- xenstar1

Copy and paste this prompt to your LLM agent (Claude Code, AmpCode, Cursor, etc.):

Install and configure oh-my-opencode-slim: https://raw.githubusercontent.com/alvinunreal/oh-my-opencode-slim/refs/heads/master/README.md

bunx oh-my-opencode-slim@latest install

The installer generates both OpenAI and OpenCode Go presets, with OpenAI active by default.

To make OpenCode Go active during install, run bunx oh-my-opencode-slim@latest install --preset=opencode-go or change the default preset name in ~/.config/opencode/oh-my-opencode-slim.json after installation.

Then:

1. Log in to the providers you want to use if you haven't already:

   opencode auth login

2. Refresh and list the models OpenCode can see:

   opencode models --refresh

3. Open your plugin config at ~/.config/opencode/oh-my-opencode-slim.json

4. Update the models you want for each agent

[!TIP] It's recommended to understand how background orchestration works. The Orchestrator prompt contains the scheduler rules, specialist routing logic, and thresholds for when work should be assigned to background agents. You can always delegate manually by calling a subagent via: @agentName <task>

[!TIP] Because background agents are now the default workflow, it is highly recommended to enable and configure Multiplexer Integration. It automatically opens each agent in a dedicated Tmux or Zellij pane, so you can watch specialists work live while the Orchestrator continues coordinating the session.

The default generated configuration includes both openai and opencode-go presets.

{
  "$schema": "https://unpkg.com/oh-my-opencode-slim@latest/oh-my-opencode-slim.schema.json",
  "preset": "openai",
  "presets": {
    "openai": {
      "orchestrator": { "model": "openai/gpt-5.5", "variant": "medium", "skills": ["*"], "mcps": ["*", "!context7"] },
      "oracle": { "model": "openai/gpt-5.5", "variant": "high", "skills": ["simplify"], "mcps": [] },
      "librarian": { "model": "openai/gpt-5.4-mini", "variant": "low", "skills": [], "mcps": ["websearch", "context7", "gh_grep"] },
      "explorer": { "model": "openai/gpt-5.4-mini", "variant": "low", "skills": [], "mcps": [] },
      "designer": { "model": "openai/gpt-5.4-mini", "variant": "medium", "skills": [], "mcps": [] },
      "fixer": { "model": "openai/gpt-5.5", "variant": "low", "skills": [], "mcps": [] }
    },
    "opencode-go": {
      "orchestrator": { "model": "opencode-go/glm-5.1", "skills": [ "*" ], "mcps": [ "*", "!context7" ] },
      "oracle": { "model": "opencode-go/deepseek-v4-pro", "variant": "max", "skills": ["simplify"], "mcps": [] },
      "council": { "model": "opencode-go/deepseek-v4-pro", "variant": "high", "skills": [], "mcps": [] },
      "librarian": { "model": "opencode-go/minimax-m2.7", "skills": [], "mcps": [ "websearch", "context7", "gh_grep" ] },
      "explorer": { "model": "opencode-go/minimax-m2.7", "skills": [], "mcps": [] },
      "designer": { "model": "opencode-go/kimi-k2.6", "variant": "medium", "skills": [], "mcps": [] },
      "fixer": { "model": "opencode-go/deepseek-v4-flash", "variant": "high", "skills": [], "mcps": [] }
    }
  }
}

To use custom providers or a mixed-provider setup, use Configuration for the full reference. If you want a ready-made starting point, check the Author's Preset and $30 Preset - the $30 preset is the best cheap setup.

After installation and authentication, verify all agents are configured and responding:

opencode

Then run:

ping all agents

Confirmation that all configured agents are online and ready.

If any agent fails to respond, check your provider authentication and config file.

V2 turns oh-my-opencode-slim into a scheduler-first multi-agent workflow system. The Orchestrator stays focused on planning, delegation, reconciliation, and verification while specialists do the work in their own lanes.

• Background agents — the Orchestrator now dispatches specialists as background tasks, tracks task/session IDs, waits for completion events, and reconciles results before continuing.
• Companion — an optional floating desktop window shows which agents are currently active, including parallel background specialists.
• Deepwork — a structured workflow for large, multi-file, risky, or phased coding work using persistent plan files and Oracle review gates.
• Reflect — reviews repeated work patterns and suggests reusable skills, agents, commands, config rules, prompt rules, or project playbooks.
• Worktrees — manages Git worktrees as isolated coding lanes with safety protocols for complex, risky, or parallel tasks.
• oh-my-opencode-slim skill — a bundled configuration skill that helps tune models, prompts, custom agents, MCP access, presets, and plugin behavior safely.

V2 makes background specialists the default mental model: the Orchestrator plans the work graph, launches the right agents, avoids overlapping write ownership, and waits for terminal task results before acting on them.

See Background Orchestration for the full scheduler model.

The optional Companion is a floating desktop status window for live agent activity. It shows the current session state and which agents are active, so background work is easier to follow at a glance.

Left bottom visual companion.

During interactive install, the installer asks whether to enable Companion and defaults to yes. For automation, enable it explicitly with:

bunx oh-my-opencode-slim@latest install --companion=yes

See Companion for configuration, positions, sizes, and install details.

Deepwork is for heavy coding sessions: broad refactors, multi-phase features, risky architecture changes, or work that needs a persistent plan. It creates a local markdown progress file, uses Oracle review gates, and keeps implementation phases structured.

Start it with:

/deepwork <heavy coding task>

See Skills for when to use it and how the workflow runs.

Reflect helps the Orchestrator learn from repeated workflow friction. It reviews recent work and existing assets, then recommends the smallest useful improvement: a skill, custom agent, command, config rule, prompt rule, MCP permission change, or project playbook. If there is not enough evidence, it should recommend creating nothing.

Use it directly with:

/reflect
/reflect release workflow and checks

Or with natural prompts like:

reflect on my recent workflows
find repeated work worth turning into reusable instructions

See Skills for the full workflow and guardrails.

Worktrees manages Git worktrees as safe, isolated coding lanes under .slim/worktrees/<slug>/. The Orchestrator manages the lifecycle of these lanes, tracks state in .slim/worktrees.json, dispatches specialist agents inside them, and requires explicit confirmation before mutating git state.

See Skills for the safety protocol.

The bundled oh-my-opencode-slim skill helps the Orchestrator configure and improve the plugin itself. Use it for model tuning, custom agents, prompt overrides, skill/MCP permissions, presets, optional agents, background orchestration, and recurring workflow friction.

Ask the bundled skill to tune and improve your agent setup.

See Skills for examples and safety rules.

Forged in the void of complexity.	The Orchestrator was born when the first codebase collapsed under its own complexity. Neither god nor mortal would claim responsibility - so The Orchestrator emerged from the void, forging order from chaos. It determines the optimal path to any goal, balancing speed, quality, and cost. It guides the team, summoning the right specialist for each task and delegating to achieve the best possible outcome.
Role: Master delegator and strategic coordinator
Prompt: orchestrator.ts
Default Model: openai/gpt-5.5 (medium)
Recommended Models: openai/gpt-5.5 (medium) anthropic/claude-fable-5 anthropic/claude-opus-4-8
Model Guidance: Choose your strongest planning and judgment model. Orchestrator is the workflow manager: it plans, schedules background specialists, reconciles results, and verifies outcomes, so it needs reliable instruction-following and high-level technical judgment more than raw worker throughput.

The wind that carries knowledge.	The Explorer is an immortal wanderer who has traversed the corridors of a million codebases since the dawn of programming. Cursed with the gift of eternal curiosity, they cannot rest until every file is known, every pattern understood, every secret revealed. Legends say they once searched the entire internet in a single heartbeat. They are the wind that carries knowledge, the eyes that see all, the spirit that never sleeps.
Role: Codebase reconnaissance
Prompt: explorer.ts
Default Model: openai/gpt-5.4-mini
Recommended Models: openai/gpt-5.3-codex cerebras/zai-glm-4.7 fireworks-ai/accounts/fireworks/routers/kimi-k2p6-turbo
Model Guidance: Choose a fast, low-cost model. Explorer handles broad scouting work, so speed and efficiency usually matter more than using your strongest reasoning model.

The voice at the crossroads.	The Oracle stands at the crossroads of every architectural decision. They have walked every road, seen every destination, know every trap that lies ahead. When you stand at the precipice of a major refactor, they are the voice that whispers which way leads to ruin and which way leads to glory. They don't choose for you - they illuminate the path so you can choose wisely.
Role: Strategic advisor and debugger of last resort
Prompt: oracle.ts
Default Model: openai/gpt-5.5 (high)
Recommended Models: openai/gpt-5.5 (xhigh) anthropic/claude-fable-5 anthropic/claude-opus-4-8 (xhigh)
Model Guidance: Choose your strongest high-reasoning model for architecture, hard debugging, trade-offs, and code review.

[!NOTE] Why doesn't Orchestrator auto-call Council more often? This is intentional. Council runs multiple models at once, so automatic delegation is kept strict because it is usually the highest-cost path in the system. In practice, Council is meant to be used manually when you want it, for example: @council compare these two architectures.

Many minds, one verdict.	The Council is not a lone being but a chamber of minds summoned when one answer is not enough. It sends your question to multiple models in parallel, gathers their competing judgments, and then the Council agent itself distills the strongest ideas into a single verdict. Where a solitary agent may miss a path, the Council cross-examines possibility itself.
Role: Multi-LLM consensus and synthesis
Prompt: council.ts
Guide: docs/council.md
Default Setup: Config-driven — councillors come from council.presets and the Council agent model comes from your normal council agent config
Recommended Setup: Strong Council model + diverse councillors across providers
Model Guidance: Use a strong synthesis model for the Council agent and diverse models as councillors. The value of Council comes from comparing different model perspectives, not just picking the single strongest model everywhere.

The weaver of understanding.	The Librarian was forged when humanity realized that no single mind could hold all knowledge. They are the weaver who connects disparate threads of information into a tapestry of understanding. They traverse the infinite library of human knowledge, gathering insights from every corner and binding them into answers that transcend mere facts. What they return is not information - it's understanding.
Role: External knowledge retrieval
Prompt: librarian.ts
Default Model: openai/gpt-5.4-mini
Recommended Models: openai/gpt-5.3-codex cerebras/zai-glm-4.7 fireworks-ai/accounts/fireworks/routers/kimi-k2p6-turbo
Model Guidance: Choose a fast, low-cost model. Librarian handles research and documentation lookups, so speed and efficiency usually matter more than using your strongest reasoning model.

Beauty is essential.	The Designer is an immortal guardian of beauty in a world that often forgets it matters. They have seen a million interfaces rise and fall, and they remember which ones were remembered and which were forgotten. They carry the sacred duty to ensure that every pixel serves a purpose, every animation tells a story, every interaction delights. Beauty is not optional - it's essential.
Role: UI/UX implementation and visual excellence
Prompt: designer.ts
Default Model: openai/gpt-5.4-mini
Recommended Models: google/gemini-3.5-flash moonshotai/kimi-k2.7-code
Model Guidance: Choose a model that is strong at UI/UX judgment, frontend implementation, and visual polish.

The final step between vision and reality.	The Fixer is the last of a lineage of builders who once constructed the foundations of the digital world. When the age of planning and debating began, they remained - the ones who actually build. They carry the ancient knowledge of how to turn thought into thing, how to transform specification into implementation. They are the final step between vision and reality.
Role: Fast implementation specialist
Prompt: fixer.ts
Default Model: openai/gpt-5.5 (low)
Recommended Models: openai/gpt-5.5 (low) anthropic/claude-sonnet-4-6
Model Guidance: Choose a reliable coding model for scoped implementation work. Fixer receives a concrete plan or bounded instructions from Orchestrator, making it a good place for efficient execution tasks and straightforward code changes.

[!NOTE] Why a separate agent? If your Orchestrator model is not multimodal, enable Observer to handle images, screenshots, PDFs, and other visual files. Observer is disabled by default and gives the Orchestrator a dedicated multimodal reader without forcing you to change your main reasoning model. Set disabled_agents: [] and an observer model in your configuration. The bundled opencode-go install preset does this automatically because its GLM Orchestrator is not multimodal.

The eye that reads what others cannot.	Read-only visual analysis — interprets images, screenshots, PDFs, and diagrams. Returns structured observations to the orchestrator without loading raw file bytes into the main context window. Images, screenshots, diagrams → read tool (native image support) PDFs and binary documents → read tool (text + structure extraction) Disabled by default — enable with "disabled_agents": [] and configure a vision-capable model; installing with --preset=opencode-go enables it with opencode-go/kimi-k2.6
Prompt: observer.ts
Default Model: openai/gpt-5.4-mini — configure a vision-capable model to enable
Model Guidance: Choose a vision-capable model if you want the agent to read screenshots, images, PDFs, and other visual files.

Use this section as a map: start with installation, then jump to features, configuration, or example presets depending on what you need.

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