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deer-flow

Coordinate long-horizon AI tasks across multiple agents with sandboxing and memory.

Updated Mar 15, 2026
Search Tags:#multi-agent#memory#ai-agent#sandbox#long-term#deerflow#tool-gateway
One-click install
npx skills add https://github.com/gujincheng1128/my-awesome-app --skill deer-flow-gujincheng1128
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: deer-flow
Source: https://github.com/gujincheng1128/my-awesome-app/tree/main/skills/deer-flow
Command: npx skills add https://github.com/gujincheng1128/my-awesome-app --skill deer-flow-gujincheng1128

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

DeerFlow solves the complexity of coordinating long-horizon AI tasks across multiple agents by providing a structured, memory-enabled, tool-integrated framework.

Core Features & Use Cases

  • Long-horizon task orchestration with sub-agents and message gateway support for research, coding, and content creation.
  • Sandbox execution, memory system, and tool gateway for safe, repeatable workflows.
  • Use Case: Manage multi-step projects like literature reviews, code-generation pipelines, or academic research with traceable task histories.

Quick Start

Run DeerFlow to initialize the Researcher, Coder, and Creator agents and begin a multi-step workflow.

Frequently Asked Questions about deer-flow

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I coordinate long-horizon AI tasks across multiple agents?▼

DeerFlow coordinates long-horizon AI tasks by initializing Researcher, Coder, and Creator agents within sandboxed environments. It applies persistent memory and a unified tool gateway to manage multi-step workflows, enabling reliable and scalable agent collaboration for complex projects.

Can I use sandboxed environments for multi-agent code generation pipelines?▼

Yes, DeerFlow supports multi-agent code generation pipelines by executing tasks within sandboxed environments. This ensures safe, repeatable workflows while the integrated memory system and tool gateway manage state and coordinate sub-agents reliably throughout the pipeline.

What is the best way to manage multi-step research workflows with persistent memory?▼

Managing multi-step research workflows with persistent memory requires a framework like DeerFlow that applies long-horizon task orchestration. It utilizes a dedicated memory system and tool gateway to maintain state across sub-agents, producing traceable task histories for literature reviews and academic research.

Does multi-agent orchestration work with a unified tool gateway for content creation?▼

DeerFlow integrates a unified tool gateway to provide multi-agent orchestration for content creation workflows. This gateway supplies sandboxed agents with shared tool access, ensuring reliable, scalable collaboration and traceable execution across complex creative projects.

Do I need a message gateway to scale multi-agent collaboration?▼

Scaling multi-agent collaboration requires a message gateway to synchronize sub-agents effectively. DeerFlow includes message gateway support to manage inter-agent communication, ensuring that complex multi-step tasks in research, coding, and creative workflows remain coordinated and reliable.

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