This is a decision framework, not code. It walks you through five gates before you write any Deep Agents implementation: confirming you actually need Deep Agents over lighter alternatives like direct function calling, picking a backend (ephemeral StateBackend, disk-based FilesystemBackend, or persistent StoreBackend), deciding if subagents make sense for your task complexity, defining human-in-the-loop interrupts, and choosing custom middleware. Each gate requires a written artifact to pass. The tables comparing Deep Agents to LangChain LCEL or raw LangGraph are honest about when the overhead isn't worth it. Use this when architectural mistakes would be expensive to unwind later, or when you need to document why you chose CompositeBackend routing over a simpler setup.
npx skills add https://github.com/existential-birds/beagle --skill deepagents-architecture