Skip to main content

AI Orchestration Tool for Claude Code - Multi-agent orchestration for complex development tasks

Project description

Ensemble

"One task. Many minds. One result."

AI Orchestration Tool for Claude Code.

Overview

Ensemble is an AI orchestration system that combines the best practices from:

  • shogun - Autonomous AI collaboration with tmux parallel execution
  • takt - Workflow enforcement with quality gates
  • Boris's practices - Effective use of skills, subagents, CLAUDE.md, and hooks

Features

  • Autonomous AI Coordination: One instruction triggers multiple AI agents working together
  • Flexible Execution Patterns:
    • Pattern A: Simple tasks via subagent
    • Pattern B: Medium tasks via tmux parallel panes
    • Pattern C: Large tasks via git worktree separation
  • Parallel Review: Architecture + Security reviews run in parallel
  • Self-Improvement: Automatic learning and CLAUDE.md updates
  • Compaction Recovery: Built-in protocol to prevent role amnesia

Installation

Using uv (recommended)

# Install globally
uv tool install ensemble-claude

# Or add to your project
uv add ensemble-claude

Using pip

pip install ensemble-claude

From source

git clone https://github.com/ChikaKakazu/ensemble.git
cd ensemble

# Using uv
uv pip install -e .

# Or using pip
pip install -e .

Quick Start

# 1. Initialize Ensemble in your project
ensemble init

# 2. Launch the tmux sessions (2 separate sessions)
ensemble launch

# 3. Open another terminal to view workers session
tmux attach -t ensemble-workers

# 4. Run a task in the Conductor session
/go implement user authentication

# Light workflow (minimal cost)
/go-light fix typo in README

CLI Commands

Command Description
ensemble init Initialize Ensemble in current project
ensemble init --full Also copy agent/command definitions locally
ensemble launch Start 2 tmux sessions (conductor + workers)
ensemble launch --no-attach Start sessions without attaching
ensemble --version Show version

Requirements

  • Python 3.10+
  • Claude Code CLI (claude command available)
  • tmux
  • git 2.20+ (for worktree support)
  • Claude Max plan recommended (for parallel execution)

Agent Architecture

┌─────────────┐
│  Conductor  │ ← Orchestrator (planning, judgment, delegation)
└──────┬──────┘
       │
  ┌────┴────┐
  ▼         ▼
┌────────┐ ┌──────────┐
│Dispatch│ │ Learner  │
└───┬────┘ └──────────┘
    │        ↑ Learning records
    ▼
┌─────────────────────────────┐
│  Reviewer / Security-Reviewer│ ← Parallel reviews
└─────────────────────────────┘
    │
    ▼ (worktree mode)
┌──────────┐
│Integrator│ ← Merge & integrate
└──────────┘

License

MIT License - see LICENSE for details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ensemble_claude-0.4.6.tar.gz (83.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ensemble_claude-0.4.6-py3-none-any.whl (94.7 kB view details)

Uploaded Python 3

File details

Details for the file ensemble_claude-0.4.6.tar.gz.

File metadata

  • Download URL: ensemble_claude-0.4.6.tar.gz
  • Upload date:
  • Size: 83.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for ensemble_claude-0.4.6.tar.gz
Algorithm Hash digest
SHA256 04c4bd1a37e0d5208ab9b652d441184eb3c55e14b070a3cc9b4b8adf6c6e55ef
MD5 5b3e9c68d968015b19536a548d5815b8
BLAKE2b-256 b9413e341ad225b781d85d6810f448886d95b937f9eda52b65c4f68ab33dee94

See more details on using hashes here.

Provenance

The following attestation bundles were made for ensemble_claude-0.4.6.tar.gz:

Publisher: publish.yml on ChikaKakazu/ensemble

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file ensemble_claude-0.4.6-py3-none-any.whl.

File metadata

File hashes

Hashes for ensemble_claude-0.4.6-py3-none-any.whl
Algorithm Hash digest
SHA256 3682f326d7bd9135514899b79501f7aa8d1dbe8f44feca728d1c380dec34390f
MD5 837228976e4dacdbdbd0f93579124b1b
BLAKE2b-256 233c9969eb4a90806b34b3bcf90a3615dc136e27a703d04cd316dfd621f17440

See more details on using hashes here.

Provenance

The following attestation bundles were made for ensemble_claude-0.4.6-py3-none-any.whl:

Publisher: publish.yml on ChikaKakazu/ensemble

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page