This project provides an AI engineering platform for Claude Code, orchestrating multiple AI models (Codex, Gemini, Claude) to execute tasks in parallel. It offers 29 specialized expert personas, proven workflows like the Double Diamond methodology, and advanced features such as design system extraction, aiming to transform Claude Code into a comprehensive AI engineering team. The platform benefits users by streamlining complex AI workflows, providing diverse perspectives, and enhancing efficiency.

How It Works

The core approach involves multi-AI orchestration, running Codex CLI, Gemini CLI, and Claude simultaneously for parallel task execution and synthesis. It leverages 29 specialized AI personas for domain-specific expertise and integrates structured methodologies like the Double Diamond workflow. Key design choices include automatic detection for multi-AI execution, manual overrides, and graceful degradation based on provider availability. The novel "Validation Gate Pattern" ensures mandatory execution of core scripts, guaranteeing compliance and improving efficiency.

Quick Start & Requirements

• Primary install / run command:
  1. /plugin marketplace add https://github.com/nyldn/claude-octopus
  2. /plugin install claude-octopus@nyldn-plugins
• Non-default prerequisites and dependencies: Requires Claude Code environment. External AI providers (Codex CLI, Gemini CLI) are optional but enhance multi-AI features.
• Configuration: Run /octo:setup for a guided wizard to configure Codex and/or Gemini providers.
• Links: GitHub repository (implied by URL), Claude Code Plugin Marketplace.

Highlighted Details

• Multi-AI Parallel Execution: Runs Codex, Gemini, and Claude simultaneously for diverse viewpoints and faster results (2-5 min vs. 6-15 sequential), with a 75% consensus quality gate.
• 29 Expert AI Personas: Provides specialized roles (e.g., Backend Architect, Security Auditor, UX Researcher) that activate automatically or can be invoked explicitly.
• Double Diamond Workflows: Integrates a structured 4-phase methodology (Discover, Define, Develop, Deliver) for AI engineering projects, enforcing quality gates and preventing scope drift.
• Validation Gate Pattern (v7.15.0): Guarantees 100% execution of core scripts and multi-AI tasks, improving speed and efficiency.
• Interactive Research & Cost Transparency (v7.14.0): Users see estimated costs and interactively select research depth, focus, and format before execution.
• Context-Aware Intelligence: Auto-detects "Dev Work" vs. "Knowledge Work" contexts to adapt AI research and output accordingly.

Maintenance & Community

The project is actively maintained, with the current version being v7.15.0 (January 2026) and boasting over 95% test coverage. Contribution guidelines are provided, and issue tracking is available via GitHub.

Licensing & Compatibility

The project is released under the MIT License, which is permissive for commercial use and integration into closed-source projects.

Limitations & Caveats

Full multi-AI orchestration capabilities require external Codex or Gemini providers; without them, only Claude-based features are accessible. The platform is designed for the Claude Code environment, and performance/cost estimates are subject to real-world usage variations.