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       Turbocharge your Copilot CLI with multi-agent orchestration

oh-my-copilot
Your Copilot has been working out, learning new ways to improve your life.


npm version npm downloads GitHub stars License: MIT
This work is based on oh-my-claudecode by Yeachan Heo, but with copilot cli focus.

Quick Start

# Step 1: Install
/plugin marketplace add https://github.com/RobinNorberg/oh-my-copilot
/plugin install oh-my-copilot@omcp
# or
npm i -g oh-my-copilot@latest

# Step 2: Setup
/setup

# Step 3: Build something
/autopilot: build a todo-app
# or
autopilot: build a todo-app

# If you enjoy the output, give the repo att ⭐ and tell a friend

Not Sure Where to Start?

If you're uncertain about requirements, have a vague idea, or want to micromanage the design:

/deep-interview "I want to build a todo-app"

The deep interview uses Socratic questioning to clarify your thinking before any code is written.


Key Features

  • Copilot CLI friendly — Perfect for development in the terminal
  • Natural language interface — no commands to memorize, just describe what you want
  • Team-first orchestration — staged pipeline with plan, exec, verify, and fix loop
  • Automatic parallelization — complex tasks distributed across our specialized agents
  • Smart model routing — Haiku for simple tasks, Sonnet for average and Opus for complex reasoning
  • Persistent execution — won't give up until the job is verified complete
  • Azure DevOps/GitHub native — auto-detection, work item management, PR operations, triage workflows
  • Stop your yolo abuse — using a layered permission model to help your agents perform safe work without your interference

Magic Keywords

Optional shortcuts for power users. Natural language works fine without them.

Keyword Category Effect Example
team orchestration Canonical Team orchestration team 3:executor "fix all TypeScript errors"
ask copilot orchestration Delegate to Copilot CLI ask claude "review auth architecture"
ask claude orchestration Delegate to Claude Code CLI ask claude "review auth architecture"
ask codex orchestration Delegate to Codex CLI ask codex "security analysis"
ask gemini orchestration Delegate to Gemini CLI ask gemini "suggest UX improvements"
cccg orchestration Quadri-model orchestration cccg review this PR
omcp team orchestration tmux CLI workers (codex/gemini/copilot) omcp team 2:codex "security review"
code review analysis Code review mode code review the auth module
critique analysis Pre-push adversarial critique critique my changes
debug, diagnose analysis Session/repo diagnostics debug why hooks aren't firing
deep-analyze analysis Deep analysis mode deep-analyze why tests are failing
deep-dive analysis Trace → interview pipeline deep-dive why auth is slow
deepinit analysis Deep codebase init with AGENTS.md deepinit
deep-interview analysis Socratic requirements clarification deep-interview "vague idea"
deep-review analysis Multi-pass code review (4 passes) deep-review this PR
deepsearch analysis Codebase-focused search routing deepsearch for auth middleware
deslop, anti-slop analysis AI code slop cleanup deslop the auth module
discover analysis Parallel codebase quality scan discover src/hooks/
external-context analysis Parallel external doc/web search external-context React Server Components
sciomc analysis Parallel scientist orchestration sciomc analyze test failures
security review analysis Security review mode security review the API endpoints
tdd, test first analysis TDD workflow enforcement tdd: implement password validation
trace analysis Evidence-driven causal tracing trace why auth is broken
verify analysis Verify changes work before claiming done verify the fix
ultrathink analysis Deep reasoning mode ultrathink about this architecture
ralplan planning Iterative planning consensus ralplan this feature
autopilot execution Full autonomous execution autopilot: build a todo app
cancelomc, stopomc execution Stop active OMC modes stopomc
experiment execution Hypothesis-driven experiment loop experiment: optimize API latency
ralph execution Persistence mode ralph: refactor auth
ralphthon execution Autonomous hackathon mode ralphthon: build MVP in 2 hours
self-improve execution Autonomous evolutionary code improvement self-improve the parser module
skillify execution Extract reusable skill from session skillify this workflow
ulw execution Maximum parallelism ulw fix all errors
gh setup github Configure GitHub integration gh setup
gh triage github GitHub issue/PR/CI triage gh triage
gh review github Interactive GitHub PR review gh review
gh auto-review github Automated code review via code-reviewer agent gh auto-review
gh project github Manage GitHub Projects (v2) boards gh project
ado sprint devops Sprint planning and iteration management ado sprint
ado setup devops Configure Azure DevOps integration ado setup
ado triage devops Azure DevOps work item triage ado triage
ado review devops Interactive Azure DevOps PR review ado review
ado auto-review devops Automated code review via code-reviewer agent ado auto-review
hud utility Configure status line display hud preset minimal
learner utility Learn a skill from the current conversation learner
remember utility Save reusable project knowledge remember this pattern
wiki utility Persistent markdown knowledge base wiki add auth architecture notes

Notes:

  • Informational filtering: Asking "what is ralph?" or "explain ultrawork" won't trigger execution — only actionable uses activate keywords.

Orchestration between agents

Team Mode

Team is the canonical orchestration surface. It runs a staged pipeline:

team-plan → team-prd → team-exec → team-verify → team-fix (loop)

/team 3:executor "fix all TypeScript errors"

CCCG

CCCG uses multi-model advisor synthesis — fans out via ask-copilot + ask-claude + ask-codex + ask-gemini, then Copilot synthesizes the results:

/cccg "review this branch — architecture, security, and UI components"

OMC Team Mode

Omc team spawn real tmux CLI workers for cross-model tasks:

omcp team 1:copilot "review the ingestion module for performance issues"
omcp team 2:claude "review the database module for sql issues"
omcp team 3:codex "review the auth module for security issues"
omcp team 5:gemini "redesign UI components for accessibility"

Full Team Mode docs →


Documentation


Requirements


Optional enhancements

Platform & tmux

OMC features like omcp team and rate-limit detection require tmux:

Platform tmux provider Install
macOS tmux brew install tmux
Ubuntu/Debian tmux sudo apt install tmux
Fedora tmux sudo dnf install tmux
Arch tmux sudo pacman -S tmux
Windows psmux (native) winget install psmux
Windows (WSL2) tmux (inside WSL) sudo apt install tmux

Windows users: psmux provides a native tmux binary for Windows with 76 tmux-compatible commands. No WSL required.

Multi-AI Orchestration

OMC can orchestrate multiple AI CLI providers as tmux workers for cross-validation, design consistency, and parallel execution. All four major CLI tools are supported:

Provider Install What it enables
Copilot CLI npm install -g @github/copilot Core orchestration platform
Claude Code npm install -g @anthropic-ai/claude-code Deep reasoning, architecture analysis
Gemini CLI npm install -g @google/gemini-cli Design review, UI consistency (1M token context)
Codex CLI npm install -g @openai/codex Architecture validation, code review cross-check
omcp team 2:claude "review auth architecture"
omcp team 2:codex "security analysis"
omcp team 2:gemini "UI consistency check"
omcp team 1:copilot "review existing tests"

Only Copilot CLI is required — the others are optional and add cross-provider validation.


Star History

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🤝 Contributing

Contributions welcome! Open an issue or PR on GitHub to the dev branch.


License

MIT — see LICENSE.