AI Agentsagent-fleetagent-swarmclaude-codecodex-cligit-worktrees
Installation
# Add to your Claude Code skills
git clone https://github.com/ComposioHQ/agent-orchestrator
README.md
Spawn parallel AI coding agents, each in its own git worktree. Agents autonomously fix CI failures, address review comments, and open PRs — you supervise from one dashboard.
Agent Orchestrator manages fleets of AI coding agents working in parallel on your codebase. Each agent gets its own git worktree, its own branch, and its own PR. When CI fails, the agent fixes it. When reviewers leave comments, the agent addresses them. You only get pulled in when human judgment is needed.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
git clone https://github.com/ComposioHQ/agent-orchestrator.git
cd agent-orchestrator && bash scripts/setup.sh
Start
Point it at any repo — it clones, configures, and launches the dashboard in one command:
ao start https://github.com/your-org/your-repo
Or from inside an existing local repo:
cd ~/your-project && ao start
That's it. The dashboard opens at http://localhost:3000 and the orchestrator agent starts managing your project.
Add more projects
ao start ~/path/to/another-repo
How It Works
You start — ao start launches the dashboard and an orchestrator agent
Orchestrator spawns workers — each issue gets its own agent in an isolated git worktree
Agents work autonomously — they read code, write tests, create PRs
Reactions handle feedback — CI failures and review comments are automatically routed back to the agent
You review and merge — you only get pulled in when human judgment is needed
The orchestrator agent uses the AO CLI internally to manage sessions. You don't need to learn or use the CLI — the dashboard and orchestrator handle everything.
Configuration
ao start auto-generates agent-orchestrator.yaml with sensible defaults. You can edit it afterwards to customize behavior:
# agent-orchestrator.yaml
# Runtime data is auto-derived under ~/.agent-orchestrator/{hash}-{projectId}/
port: 3000
defaults:
runtime: tmux
agent: claude-code
workspace: worktree
notifiers: [desktop]
projects:
my-app:
repo: owner/my-app
path: ~/my-app
defaultBranch: main
sessionPrefix: app
reactions:
ci-failed:
auto: true
action: send-to-agent
retries: 2
changes-requested:
auto: true
action: send-to-agent
escalateAfter: 30m
approved-and-green:
auto: false # flip to true for auto-merge
action: notify
CI fails → agent gets the logs and fixes it. Reviewer requests changes → agent addresses them. PR approved with green CI → you get a notification to merge.
All interfaces defined in packages/core/src/types.ts. A plugin implements one interface and exports a PluginModule. That's it.
Why Agent Orchestrator?
Running one AI agent in a terminal is easy. Running 30 across different issues, branches, and PRs is a coordination problem.
Without orchestration, you manually: create branches, start agents, check if they're stuck, read CI failures, forward review comments, track which PRs are ready to merge, clean up when done.
With Agent Orchestrator, you: ao start and walk away. The system handles isolation, feedback routing, and status tracking. You review PRs and make decisions — the rest is automated.
Documentation
| Doc | What it covers |
| ---------------------------------------- | ------------------------------------------------------------ |
| Setup Guide | Detailed installation, configuration, and troubleshooting |
| CLI Reference | All ao commands (mostly used by the orchestrator agent) |
| Examples | Config templates (GitHub, Linear, multi-project, auto-merge) |
| Development Guide | Architecture, conventions, plugin pattern |
| Contributing | How to contribute, build plugins, PR process |
Development
pnpm install && pnpm build # Install and build all packages
pnpm test # Run tests (3,288 test cases)
pnpm dev # Start web dashboard dev server
Contributions welcome. The plugin system makes it straightforward to add support for new agents, runtimes, trackers, and notification channels. Every plugin is an implementation of a TypeScript interface — see CONTRIBUTING.md and the Development Guide for the pattern.
