DRAGON: A Hierarchical Multi-Agent Orchestration Framework for Distributed AI Systems

We present DRAGON (Decompose-Route-Allocate-Generate-Orchestrate-Network), a hierarchical multi-agent orchestration framework for building distributed AI systems composed of heterogeneous, independently-operating agents. DRAGON organizes 21 specialized agents across four functional divisions—BUILD, CREATE, SECURITY, and HERMES—each powered by distinct models and skill sets, totaling 21 models and 51 skills. The framework implements a five-stage sequential pipeline: Decompose → Route → Allocate → Coordinate → Yield, which transforms complex user requests into coordinated multi-agent workflows. DRAGON incorporates a constitution-based alignment mechanism (DRAGON_CONSTITUTION.md) inspired by Anthropic's constitutional AI approach, providing reason-based ethical guardrails rather than rigid rule enforcement. Inter-agent communication follows the Agent-to-Agent (A2A) protocol, enabling standardized message passing across agents running on diverse hardware—from edge devices to server-class Apple Silicon workstations. The framework operates on a distributed agent mesh composed of OpenClaw (server-side orchestrator, 80+ tools, 6 channels) and Hermes (edge/mobile agent, Telegram gateway, on-device inference), connected via the Hayula Connect bidirectional bridge. We compare DRAGON against existing multi-agent frameworks including AutoGPT, BabyAGI, and CrewAI, identifying key architectural advantages in structured task decomposition, hierarchical routing, and constitution-based safety alignment. DRAGON is released under the CC0 1.0 Universal license.