Use when specifying or implementing LangGraph applications - from architecture planning and specification writing to actual code implementation. Also use for designing agent workflows or learning LangGraph patterns. This is a comprehensive guide for building AI agents with LangGraph, covering core concepts, architecture patterns, memory management, tool integration, and advanced features.
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01_core_concepts_edge.md01_core_concepts_node.md01_core_concepts_overview.md01_core_concepts_state.md02_graph_architecture_agent.md02_graph_architecture_evaluator_optimizer.md02_graph_architecture_orchestrator_worker.md02_graph_architecture_overview.md02_graph_architecture_parallelization.md02_graph_architecture_prompt_chaining.md02_graph_architecture_routing.md02_graph_architecture_subgraph.md02_graph_architecture_workflow_vs_agent.md03_memory_management_checkpointer.md03_memory_management_overview.md03_memory_management_persistence.md03_memory_management_store.md04_tool_integration_command_api.md04_tool_integration_overview.md04_tool_integration_tool_definition.md