deep-agents-core
Foundation framework for building multi-step agents with built-in planning, memory, and skill delegation.
- Provides six core middleware options: task planning, filesystem context management, subagent delegation, persistent memory, human approval workflows, and on-demand skill loading
- Includes three always-present built-in tools:
write_todosfor task tracking, filesystem operations (ls,read_file,write_file,edit_file,glob,grep), andtaskfor spawning specialized subagents - Supports two backend strategies: FilesystemBackend for local skill directories and StoreBackend for environments without filesystem access
- Requires SKILL.md format with YAML frontmatter for skill discovery; skills load on-demand based on agent relevance rather than at startup
- Task Planning: TodoListMiddleware for breaking down complex tasks
- Context Management: Filesystem tools with pluggable backends
- Task Delegation: SubAgent middleware for spawning specialized agents
- Long-term Memory: Persistent storage across threads via Store
- Human-in-the-loop: Approval workflows for sensitive operations
- Skills: On-demand loading of specialized capabilities
The agent harness provides these capabilities automatically - you configure, not implement.
| Use Deep Agents When | Use LangChain's create_agent When |
|---|---|
| Multi-step tasks requiring planning | Simple, single-purpose tasks |
| Large context requiring file management | Context fits in a single prompt |
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