FROST Framework Introduces Five-Dimension Model to Govern Multi-Agent AI Systems

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The FROST Team released a code tutorial on July 9, 2026, demonstrating how to build a governable multi-agent system using the FROST V4.0 framework's five-dimension meta-model. The tutorial addresses a common gap in popular agent frameworks like LangChain, CrewAI, and AutoGen, which lack built-in governance capabilities around permissions, decision traceability, and unauthorized actions. FROST V4.0 organizes governance across five modules — Armory, TaskRegistry, EventCatalog, PlatformRegistry, and RuleRegistry — each targeting a distinct control problem in multi-agent deployments. The framework is designed with zero external dependencies, relying solely on Python's standard library, and is available as two separate repositories: FROST for conceptual grounding and FROST-SOP for production engineering. The tutorial walks developers step by step through registering skills with metadata, defining task dependency graphs, and tracking agent behavior through a centralized event catalog.

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