An agent team in a folder.

Say what you need. An AI team does the work and asks when it needs you.

See how it works
  1. You

    Help me plan our community event.

  2. WOUF · lead

    I'll ask the worker to draft a plan and the review bot to check it.

  3. WOUF · a question from the worker

    What date should the plan use?

  4. You

    June 12.

  5. Done · worker and review

    The reviewed draft is ready for you: a plan and decision notes in the task files.

  1. You

    Organize our volunteer tasks.

  2. WOUF · lead

    I'll have the worker prepare a task list and review check it.

  3. WOUF · a question from the worker

    Who should own the welcome desk?

  4. You

    Sam.

  5. Done · worker and review

    The reviewed task list is ready in the task files, with Sam as owner.

  1. You

    Add a check for missing titles.

  2. WOUF · lead

    I'll brief worker and ask review to check the change.

  3. WOUF · a question from the worker

    Should an empty title be rejected?

  4. You

    Yes.

  5. Done · worker and review

    The reviewed change and its test are ready on the task branch for your decision.

An illustrative scenario, not a transcript: what the bots say depends on the model, your setup and your answers. See the examples

How it works

Like a small company works with a team.

You talk to one lead. The lead does not do the work itself: it hands each task to a worker, has a review bot check the result and brings the questions to you.

  1. You say what you need

    In plain words, in the AI assistant you already use, in one folder.

  2. The lead hands it on

    It writes a short brief for the worker and passes questions back to you.

  3. The worker does it

    With a sandboxed setup each bot works in its own workspace, separate from your project and home folders.

  4. Review checks, you decide

    A second bot checks the result before it comes to you. What happens with it is your call.

What it does for you

Five things built in.

  • Each bot in its own workspace

    Choose a sandboxed setup to give each bot its own workspace, separate from your project and home folders.

  • A check before review

    The gate command you configure, your tests for example, runs before review without an AI call. This repository's own gate adds a complexity check (scripts/complexity.py) that you can copy into yours.

  • Side by side, checked first

    For a batch, WOUF checks that the tasks' declared file areas do not overlap before starting them together.

  • Shared between teams

    Teams can exchange signed handoffs through a shared Git repository, without a dedicated WOUF server.

  • Work you can follow

    Team events and readable summaries can live in your Git repository, so you can follow the work over time.

Get started

Three steps, then you just talk.

You choose where to run your team and which available model service to use; WOUF does not require its own cloud or server.

  1. Have an AI assistant for the terminal

    For example Claude Code, Codex CLI or Antigravity. Install one and sign in once.

    • Claude Code
    • Codex CLI
    • Antigravity (agy)
    • Grok Build
    • any CLI that reads AGENTS.md
  2. Make a folder and open it in the terminal

    Then start your assistant there.

    Never opened a terminal? Here is how.

    On a Mac: make the folder in Finder. Open the Terminal app, type cd and a space, drag the folder into the window and press Return.

    On Windows 11: open the folder in File Explorer, right-click an empty spot in it and choose “Open in Terminal”.

    Now type the name of your assistant, for example claude, and press Enter.

  3. Paste one sentence

    The assistant sets everything up in that folder and asks a few questions, each with a recommendation. Typing your key is the one step it leaves to you.

The sentence to paste into your AI assistant

Set up the agent team from https://github.com/vaiev/wouf/blob/main/INSTALL.md in this folder. I am not technical: explain in plain words and do the steps for me.

Afterwards you just talk: “WOUF, what can you do?”

Limits

Honest about the edges.

  • Host mode has no sandbox

    Docker, Podman and bubblewrap runs give a bot a separate workspace. Host mode runs without a sandbox and can reach your computer with your permissions.

  • What you give a bot, it has

    Inputs, repository content and keys you hand to a bot can still reach it. A sandbox is not a guarantee against every exploit or leak.

  • The network is open by default

    The shipped container setting gives open network access. Cloud models need the internet, so what a bot works on goes to the model provider.

  • Rules are instructions

    Roles and questions are instructions to the models, not a guarantee that they comply.

  • Legal rules are yours to check

    Whether a setup meets the law where you work depends on the model and how you run it. WOUF does not settle that for you.

All limits in the docs

Built with WOUF

It builds itself.

WOUF's own work is planned as tasks. In its development repository, more than half of the commits name the task they came from.

Three of those commits

T-0090 docs(guide): the guide in Markdown, four how-tos, changelog 0.1.0

T-0096 fix(goal): VERIFY reports head and count mismatches, phase semantics defined

T-0021 feat: federate, signed envelopes between two leads

These are records of the development repository, not proof that every change was made by bots. The public repository starts each release from a fresh history, so its commits do not carry them; the changelog says what came in, and docs/examples/T-0001.md follows one task from brief to approval.

Your turn: copy the sentence, paste it into your AI assistant.