This is a decision framework for LangGraph projects, not a how-to-build guide. It walks you through when to use LangGraph versus simpler alternatives, how to pick between TypedDict and Pydantic for state, which checkpointer to use in production, and the tradeoffs between supervisor versus peer-to-peer multi-agent patterns. The best part is the sequenced gates at the end: four explicit pass conditions you must hit before locking in a design, like documenting a reducer for every state field and setting retry policies for flaky nodes. Use it during architecture reviews or when a team member is about to overengineer a single LLM call into a stateful graph.
npx skills add https://github.com/existential-birds/beagle --skill langgraph-architecture