About this template
Three agents. One Pi session. No second orchestrator.
One Pi session is serial. Recon, then web research, then the edit — each waiting on the one before it while you watch.
This fork pre-wires three subagents that run as parallel Pi processes: scout for codebase recon, researcher for the web, worker for the code change. You keep the conversation you were already in.
No n8n. No CI runner. No second harness.
Run multiple AI agents from one prompt
Set a model key, start Pi, and hand it a task that obviously wants three heads:
Scout the auth package, research the library's current recommended pattern, then have worker implement the fix.
Scout, researcher and worker fan out from there. Their work renders inline, in the same terminal, while it happens — you are not tailing a log in a second window.
What lands in your fork
| Agent | Job |
|---|---|
| scout | Fast codebase recon — read, grep, find |
| researcher | Web research |
| worker | Code changes |
- A single
subagenttool surface — one thing to invoke, not three - Depth caps, so a subagent spawning a subagent can't recurse away with your model budget
- Live inline rendering of child work, inside the conversation
What you must supply: your own Pi model key
Nothing is baked into this template.
export ANTHROPIC_API_KEY=... # or OPENAI_API_KEY / GEMINI_API_KEY
pi
That is the whole setup. The rig is already installed.
Your first five minutes
Fork it. Export a key. Start Pi.
Then give it one real task from a repo you know well, phrased as recon → research → edit, and read what each agent came back with. If scout names the right files, you have your answer.
Honest limits of this multi-agent rig
This is the Pi harness. If you need Claude Code, Codex or OpenClaw specifically, this is the wrong fork.
Depth caps are the point, so you will not get an unbounded swarm out of it. It also wants a repo on disk — pure chat with nothing to scout gets you very little of the value. And three agents burn three agents' worth of tokens, on your key, on your bill.
Fork it, fan one real task across scout → researcher → worker, and see whether serial ever feels acceptable again. Your first purchase carries a 30-day money-back guarantee.