deep-agents-core

To build Deep Agents applications, use this guide to configure multi-step task planning, context management, and subagent delegation. It provides architecture patterns and configuration options for robust agent workflows.

Context management in agent frameworks handles persistent memory and state tracking across multi-step workflows. This skill guides configuring memory backends and middleware to maintain context during complex agent operations.

Configure human-in-the-loop operations for LangChain deep agents by using the provided harness architecture and middleware options. This skill covers setting up interactive checkpoints for agent task validation.

Yes, you need prior knowledge of the Deep Agents framework and related libraries. This skill provides a comprehensive configuration guide for task planning, context management, and skill loading rather than introductory tutorials.

Implement subagent delegation and persistent memory by following this guide's architecture options for backend storage and middleware. It details configuring create_deep_agent() to manage delegated tasks and state.

Without context management, complex agent workflows fail to maintain persistent memory and state across multi-step tasks. This skill solves those limitations by providing configuration options for memory and backend storage.