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beastmode

Orchestrate multiple agents for software development using isolated worktrees and adversarial review.

15|1|Updated Jun 15, 2026
Search Tags:#multi-agent#cost-optimization#ai-orchestration#software-development#adversarial-review#worktree-isolation
One-click install
npx skills add https://github.com/lac5q/beastmode --skill beastmode
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: beastmode
Source: https://github.com/lac5q/beastmode/tree/main
Command: npx skills add https://github.com/lac5q/beastmode --skill beastmode

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires Claude Code, Hermes Agent, OpenClaw, Codex CLI, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill simplifies and accelerates complex, multi-agent software development processes by providing a structured, scalable framework.

Core Features & Use Cases

  • Multi-Agent Orchestration: Efficiently manages various agents (e.g., Opus, Codex, Qwen, Gwen) through a consistent, scalable workflow.
  • Worktree Isolation: Ensures executor models perform in isolated worktrees to maintain project integrity.
  • Adversarial Review: Integrates an adversarial reviewer (like Codex/GSD) for rigorous validation of implementation steps.
  • Cost Optimization: Guides efficient utilization of expensive judgment models like Opus/Codex, leveraging cheap models like Qwen/Gwen for implementation.
  • Use Case: Perfect for developing complex features with rigorous requirements, such as architectural decisions, complex testing, and detailed documentation in the software industry.

Quick Start

Initialize the beastmode Skill with the SKILL.md file, and begin the orchestration by choosing a variant (Opus-led or Codex-led), selecting a harness, and following the beastmode loop.

Frequently Asked Questions about beastmode

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I orchestrate multiple AI agents for software development?▼

Multi-agent AI orchestration coordinates various agents like Opus, Codex, and Qwen through a structured, self-improving framework to handle decision-making, routine implementation, and continuous improvement across software development workflows.

How can I optimize AI costs when using expensive judgment models?▼

Cost optimization in multi-agent workflows leverages cheap models like Qwen and Gwen for routine implementation tasks, reserving expensive judgment models like Opus and Codex strictly for architectural decisions and adversarial review validation.

How does adversarial review work in AI code generation?▼

Adversarial review integrates a dedicated reviewer agent, such as Codex or GSD, to rigorously validate implementation steps and ensure code quality before changes are accepted into the main software development workflow.

Can I use Claude Code and Codex CLI for multi-agent orchestration?▼

Yes, Claude Code and Codex CLI are supported dependencies for multi-agent orchestration, serving as harnesses to execute the structured loop where executor models perform tasks in isolated worktrees to maintain project integrity.

What is worktree isolation in multi-agent software development?▼

Worktree isolation ensures executor models perform implementation tasks in isolated Git worktrees, preventing concurrent multi-agent operations from corrupting project integrity during complex software development workflows.

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