docs: lead Quick Start with runTeam, add output example and Node version
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README.md
63
README.md
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@ -20,33 +20,15 @@ Build AI agent teams that decompose goals into tasks automatically. Define agent
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## Quick Start
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Requires Node.js >= 18.
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```bash
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npm install @jackchen_me/open-multi-agent
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```
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Set `ANTHROPIC_API_KEY` (and optionally `OPENAI_API_KEY` or `GITHUB_TOKEN` for Copilot) in your environment.
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```typescript
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import { OpenMultiAgent } from '@jackchen_me/open-multi-agent'
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const orchestrator = new OpenMultiAgent({ defaultModel: 'claude-sonnet-4-6' })
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// One agent, one task
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const result = await orchestrator.runAgent(
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{
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name: 'coder',
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model: 'claude-sonnet-4-6',
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tools: ['bash', 'file_write'],
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},
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'Write a TypeScript function that reverses a string, save it to /tmp/reverse.ts, and run it.',
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)
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console.log(result.output)
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```
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## Multi-Agent Team
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This is where it gets interesting. Three agents, one goal:
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Three agents, one goal — the framework handles the rest:
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```typescript
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import { OpenMultiAgent } from '@jackchen_me/open-multi-agent'
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@ -91,6 +73,23 @@ console.log(`Success: ${result.success}`)
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console.log(`Tokens: ${result.totalTokenUsage.output_tokens} output tokens`)
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```
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What happens under the hood:
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```
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agent_start coordinator
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task_start architect
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task_complete architect
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task_start developer
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task_start developer // independent tasks run in parallel
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task_complete developer
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task_start reviewer // unblocked after implementation
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task_complete developer
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task_complete reviewer
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agent_complete coordinator // synthesizes final result
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Success: true
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Tokens: 12847 output tokens
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```
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## Three Ways to Run
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| Mode | Method | When to use |
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@ -107,6 +106,28 @@ console.log(`Tokens: ${result.totalTokenUsage.output_tokens} output tokens`)
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## More Examples
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<details>
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<summary><b>Single Agent</b> — one agent, one prompt</summary>
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```typescript
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import { OpenMultiAgent } from '@jackchen_me/open-multi-agent'
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const orchestrator = new OpenMultiAgent({ defaultModel: 'claude-sonnet-4-6' })
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const result = await orchestrator.runAgent(
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{
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name: 'coder',
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model: 'claude-sonnet-4-6',
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tools: ['bash', 'file_write'],
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},
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'Write a TypeScript function that reverses a string, save it to /tmp/reverse.ts, and run it.',
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)
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console.log(result.output)
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```
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</details>
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<details>
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<summary><b>Task Pipeline</b> — explicit control over task graph and assignments</summary>
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71
README_zh.md
71
README_zh.md
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@ -20,37 +20,15 @@
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## 快速开始
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需要 Node.js >= 18。
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```bash
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npm install @jackchen_me/open-multi-agent
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```
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在环境变量中设置 `ANTHROPIC_API_KEY`（以及可选的 `OPENAI_API_KEY` 或用于 Copilot 的 `GITHUB_TOKEN`）。
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```typescript
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import { OpenMultiAgent } from '@jackchen_me/open-multi-agent'
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const orchestrator = new OpenMultiAgent({ defaultModel: 'claude-sonnet-4-6' })
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// 一个智能体，一个任务
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const result = await orchestrator.runAgent(
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{
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name: 'coder',
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model: 'claude-sonnet-4-6',
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tools: ['bash', 'file_write'],
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},
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'Write a TypeScript function that reverses a string, save it to /tmp/reverse.ts, and run it.',
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)
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console.log(result.output)
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```
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## 作者
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> JackChen — 前 WPS 产品经理，现独立创业者。关注小红书[「杰克西｜硅基杠杆」](https://www.xiaohongshu.com/user/profile/5a1bdc1e4eacab4aa39ea6d6)，持续获取我的 AI Agent 观点和思考。
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## 多智能体团队
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这才是有意思的地方。三个智能体，一个目标：
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三个智能体，一个目标——框架处理剩下的一切：
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```typescript
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import { OpenMultiAgent } from '@jackchen_me/open-multi-agent'
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@ -95,6 +73,27 @@ console.log(`成功: ${result.success}`)
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console.log(`Token 用量: ${result.totalTokenUsage.output_tokens} output tokens`)
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```
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执行过程：
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```
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agent_start coordinator
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task_start architect
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task_complete architect
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task_start developer
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task_start developer // 无依赖的任务并行执行
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task_complete developer
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task_start reviewer // 实现完成后自动解锁
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task_complete developer
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task_complete reviewer
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agent_complete coordinator // 综合所有结果
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Success: true
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Tokens: 12847 output tokens
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```
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## 作者
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> JackChen — 前 WPS 产品经理，现独立创业者。关注小红书[「杰克西｜硅基杠杆」](https://www.xiaohongshu.com/user/profile/5a1bdc1e4eacab4aa39ea6d6)，持续获取我的 AI Agent 观点和思考。
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## 三种运行模式
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| 模式 | 方法 | 适用场景 |
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@ -111,6 +110,28 @@ console.log(`Token 用量: ${result.totalTokenUsage.output_tokens} output tokens
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## 更多示例
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<details>
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<summary><b>单智能体</b> — 一个智能体，一个提示词</summary>
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```typescript
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import { OpenMultiAgent } from '@jackchen_me/open-multi-agent'
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const orchestrator = new OpenMultiAgent({ defaultModel: 'claude-sonnet-4-6' })
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const result = await orchestrator.runAgent(
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{
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name: 'coder',
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model: 'claude-sonnet-4-6',
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tools: ['bash', 'file_write'],
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},
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'Write a TypeScript function that reverses a string, save it to /tmp/reverse.ts, and run it.',
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)
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console.log(result.output)
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```
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</details>
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<details>
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<summary><b>任务流水线</b> — 显式控制任务图和分配</summary>
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