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deer-workflow

图片：License: MIT 图片：npm 图片：Bun 图片：TypeScript 图片：Codex CLI 图片：DeerFlow Stars 图片：GitHub Stars

An open-source Dynamic Workflow runtime for building observable, reusable Agent graphs.

deer-workflow is a pilot project for DeerFlow 3.0, also known as DeerWork.

Index

• Why Deer Workflow
• How to use
  • Quick Start
  • Examples
  • Documentation
• How to develop
  • Set up
  • Validate changes
  • Contribute
  • License

Why Deer Workflow

Deer Workflow is a code-first implementation of Graph Engineering: TypeScript defines the valid execution paths, while Coding Agents perform the semantic work inside each node.

• Code is the plan. Control flow, phases, inputs, and failure handling live in reviewable TypeScript rather than an opaque Agent conversation.
• Agents are replaceable. Codex is the default runtime, Claude Code is built in, and the public Agent interface remains vendor-neutral.
• Execution is observable. Interactive runs provide a phase-aware TUI; automation can consume a stable JSONL event stream.

How to use

Quick Start

Install Bun and sign in to Codex CLI, then install the released CLI:

bun install --global @deerwork-ai/deer-workflow

Describe the orchestration you want. Deer Workflow asks Codex to apply the bundled workflow-creator Skill and writes a runnable TypeScript module:

deer-workflow create \
  "Create a Workflow that accepts a topics string array, researches each topic in parallel, and synthesizes a report" \
  > workflow.ts

Run the generated Workflow with its example input:

deer-workflow run ./workflow.ts \
  --input '{"topics":["Agent Skills","Dynamic Workflows"]}'

Interactive terminals show phases and Markdown logs in a live TUI. For servers, CI, and process pipelines, add --print or -p to stream one JSON event per stdout line.

Want to understand or edit the generated module? Continue with the Getting Started guide.

Examples

• Deep Research discovers research angles, investigates them in parallel, verifies claims, and produces an interactive HTML report.
• Blog Writer plans an article, drafts its sections through a pipeline, reviews them, and returns structured output.

These examples live in the repository. Clone or download it before running their documented commands.

Documentation

• Getting Started — learn the execution model and build a Workflow step by step.
• API Reference — inspect exact functions, types, events, and runtime behavior.
• Workflow Creator Skill — see the instructions used to generate Workflow modules.
• 简体中文文档

How to develop

Set up

Clone the repository and install local dependencies and Git hooks:

git clone https://github.com/deerwork-ai/deer-workflow.git
cd deer-workflow
bun install

Run the CLI directly from source:

bun run dev -- --help

Validate changes

Run the complete quality gate before submitting changes:

bun run check

Contribute

Codex CLI is the default Agent runtime, not an architectural dependency. ClaudeAgent ships as another built-in harness; integrations for other Coding Agents are welcome.

See the Getting Started guide for the full command reference.

License

This project is licensed under the MIT License.