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Magnus Hedemark
4a73657522
Comprehensive LangGraph skill covering: - Core architecture: Graph API, Functional API, state management, agent loops - Three multi-agent patterns: supervisor (~94% accuracy), swarm (~40% fewer LLM calls), hierarchical teams (subgraphs with nested state) - Persistence: checkpointers vs stores, per-invocation/per-thread/stateless modes - Production: Agent Server deployment, LangSmith observability, 8 failure modes - Evals: routing accuracy, resolution coverage, LLM-as-judge methodology - Troubleshooting: symptom→cause→fix tables per pattern - 3 Python scripts: supervisor scaffold, swarm scaffold, eval generator - 3 runnable templates: supervisor, swarm, subgraph composition Ships 8 reference files, 3 scripts, and 3 templates.