eliasforge/fable-agent-orchestration

Analysis updated 2026-05-18

★ 2Audience · developerComplexity · 3/5LicenseSetup · moderate

Mindmap

mindmap
  root((repo))
    What it does
      Coordinates AI coding agents
      Human lead as conductor
      Agents open pull requests
    Workflow model
      Split work into slices
      Isolated git worktrees
      Critic review roles
    Skills included
      Worktree isolation
      Prevent fake tests
      Recover stalled work
      Adversarial reviews
    Use cases
      Large multi-agent projects
      Automated code review
      Prevent instruction drift
    License
      AGPL v3 or later
      Earlier Apache 2.0 versions

mindmap root((repo)) What it does Coordinates AI coding agents Human lead as conductor Agents open pull requests Workflow model Split work into slices Isolated git worktrees Critic review roles Skills included Worktree isolation Prevent fake tests Recover stalled work Adversarial reviews Use cases Large multi-agent projects Automated code review Prevent instruction drift License AGPL v3 or later Earlier Apache 2.0 versions

What do people build with it?

USE CASE 1

Coordinate multiple AI coding agents on a large software project by splitting work into isolated slices.

USE CASE 2

Set up a review pipeline where critic agents verify test results and code quality before merging.

USE CASE 3

Prevent AI agents from faking test results by requiring proof checked against real code and CI.

USE CASE 4

Recover stalled agent work and control instruction drift across long multi-agent sessions.

What is it built with?

Claude Code

How does it compare?

	eliasforge/fable-agent-orchestration	0-bingwu-0/live-interpreter	010zx00x1/faresnipe
Stars	2	2	2
Language	—	Python	Python
Setup difficulty	moderate	moderate	easy
Complexity	3/5	2/5	2/5
Audience	developer	general	general

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Requires Claude Code and familiarity with git worktrees, no external dependencies but you need to understand the orchestration model before applying the skills.

Free to use and modify but any modified version must also be open source under the same license, including when used as a network service.

In plain English

This repository is a collection of reusable workflow skills for coordinating multiple AI coding agents on large software projects. It is designed to work with Claude Code, an AI assistant. The core idea is that a human or lead agent acts as a conductor who manages scope, reviews work, and decides what gets merged. The individual coding agents each handle a small, isolated piece of the implementation work. The main orchestration loop involves splitting work into independent slices, launching one agent per slice in an isolated git worktree, and giving each agent a detailed packet describing its role, scope, and proof requirements. Each agent must open a pull request rather than merge its own work. Two separate critic roles then review the submission, one checking the tests and one checking the code. Their claims are verified against real code and continuous integration results before anything is merged. The conductor can relaunch the next slice while reviews run. The repository contains a single-file skill document, a public playbook, a machine-readable catalog, and a set of individual skill files. The skills cover topics like worktree isolation, preventing fake test results, recovering stalled work, controlling instruction drift, and running adversarial reviews. There are over twenty named skills in total, each addressing a specific failure mode in multi-agent engineering workflows. The project is explicit about what it excludes. It does not contain private project formulas, identity material, secrets, session transcripts, or third-party source code. It credits three external MIT and Apache licensed projects as inspiration for specific skills, but states that no external code was vendored. All skills are rewritten syntheses for this repository's own orchestration model. The repository is licensed under the GNU Affero General Public License v3.0 or later. Earlier versions published under Apache 2.0 remain available under their original terms. The README is thorough and clearly documents the boundary between public and private material.

Copy-paste prompts

Prompt 1

Help me set up a multi-agent coding workflow using the fable-agent-orchestration skills. I want to split a large feature into independent slices, launch one Claude Code agent per slice in an isolated git worktree, and have each agent open a pull request.

Prompt 2

Write a detailed work packet for an AI coding agent that includes its role, scope boundaries, and proof requirements so it cannot fake its test results.

Prompt 3

Design a critic review process with two roles: one that checks tests and one that checks code. Show me how to verify their claims against real code and CI results before merging.

Prompt 4

Create a recovery plan for a stalled AI coding agent that was working in an isolated git worktree. Include steps to detect instruction drift and relaunch the next work slice.

Frequently asked questions

What is fable-agent-orchestration?

A collection of reusable workflow skills for coordinating multiple AI coding agents on large software projects, designed for use with Claude Code. A conductor manages scope and reviews while isolated coding agents each handle a small piece of work.

What license does fable-agent-orchestration use?

Free to use and modify but any modified version must also be open source under the same license, including when used as a network service.

How hard is fable-agent-orchestration to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is fable-agent-orchestration for?

Mainly developer.

Open on GitHub → Explain another repo

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