DeerFlow — Super Agent Harness (OpenClaw)
DeerFlow (Deep Exploration and Efficient Research Flow) is an open-source super agent harness that orchestrates sub-agents, memory, and sandboxes to do almost anything — powered by extensible skills.
Source: C:\Users\Harry\Downloads\deer-flow\
Original: https://github.com/bytedance/deer-flow
License: MIT
本技能基於 GitHub 上的 bytedance/deer-flow 修改與封裝。
Overview
DeerFlow 2.0 is a ground-up rewrite by ByteDance Volcengine for orchestrating complex AI agent workflows:
- Sub-agent orchestration — spawn and coordinate specialized sub-agents
- Persistent memory — maintain context and knowledge across sessions
- Sandboxed execution — safe code and tool execution
- Extensible skills — pluggable skill architecture
- Deep research — automated multi-step research pipelines
Structure
deer-flow/
├── backend/ # Python backend (FastAPI)
├── frontend/ # Web UI
├── skills/ # Extensible skill definitions
├── scripts/ # Utility scripts
├── contracts/ # API contracts
├── docker/ # Docker configuration
├── docs/ # Documentation
└── tests/ # Test suite
Usage in OpenClaw
When the user asks about deep research agents, multi-step agent workflows, or sub-agent orchestration:
- Reference DeerFlow's skill architecture for extensibility patterns
- Use the sub-agent spawning patterns documented in the project
- Consult
docs/for architecture and deployment
Quick Install
cd C:\Users\Harry\Downloads\deer-flow
make install # or follow Install.md