diff --git a/README.md b/README.md
index 34b0a1b..12340be 100644
--- a/README.md
+++ b/README.md
@@ -104,165 +104,23 @@ Tokens: 12847 output tokens
-## More Examples
+## Examples
-
-Single Agent — one agent, one prompt
+All examples are runnable scripts in [`examples/`](./examples/). Run any of them with `npx tsx`:
-```typescript
-import { OpenMultiAgent } from '@jackchen_me/open-multi-agent'
-
-const orchestrator = new OpenMultiAgent({ defaultModel: 'claude-sonnet-4-6' })
-
-const result = await orchestrator.runAgent(
- {
- name: 'coder',
- model: 'claude-sonnet-4-6',
- tools: ['bash', 'file_write'],
- },
- 'Write a TypeScript function that reverses a string, save it to /tmp/reverse.ts, and run it.',
-)
-
-console.log(result.output)
+```bash
+npx tsx examples/01-single-agent.ts
```
-
-
-
-Task Pipeline — explicit control over task graph and assignments
-
-```typescript
-const result = await orchestrator.runTasks(team, [
- {
- title: 'Design the data model',
- description: 'Write a TypeScript interface spec to /tmp/spec.md',
- assignee: 'architect',
- },
- {
- title: 'Implement the module',
- description: 'Read /tmp/spec.md and implement the module in /tmp/src/',
- assignee: 'developer',
- dependsOn: ['Design the data model'], // blocked until design completes
- },
- {
- title: 'Write tests',
- description: 'Read the implementation and write Vitest tests.',
- assignee: 'developer',
- dependsOn: ['Implement the module'],
- },
- {
- title: 'Review code',
- description: 'Review /tmp/src/ and produce a structured code review.',
- assignee: 'reviewer',
- dependsOn: ['Implement the module'], // can run in parallel with tests
- },
-])
-```
-
-
-
-
-Custom Tools — define tools with Zod schemas
-
-```typescript
-import { z } from 'zod'
-import { defineTool, Agent, ToolRegistry, ToolExecutor, registerBuiltInTools } from '@jackchen_me/open-multi-agent'
-
-const searchTool = defineTool({
- name: 'web_search',
- description: 'Search the web and return the top results.',
- inputSchema: z.object({
- query: z.string().describe('The search query.'),
- maxResults: z.number().optional().describe('Number of results (default 5).'),
- }),
- execute: async ({ query, maxResults = 5 }) => {
- const results = await mySearchProvider(query, maxResults)
- return { data: JSON.stringify(results), isError: false }
- },
-})
-
-const registry = new ToolRegistry()
-registerBuiltInTools(registry)
-registry.register(searchTool)
-
-const executor = new ToolExecutor(registry)
-const agent = new Agent(
- { name: 'researcher', model: 'claude-sonnet-4-6', tools: ['web_search'] },
- registry,
- executor,
-)
-
-const result = await agent.run('Find the three most recent TypeScript releases.')
-```
-
-
-
-
-Multi-Model Teams — mix Claude, GPT, and local models in one workflow
-
-```typescript
-const claudeAgent: AgentConfig = {
- name: 'strategist',
- model: 'claude-opus-4-6',
- provider: 'anthropic',
- systemPrompt: 'You plan high-level approaches.',
- tools: ['file_write'],
-}
-
-const gptAgent: AgentConfig = {
- name: 'implementer',
- model: 'gpt-5.4',
- provider: 'openai',
- systemPrompt: 'You implement plans as working code.',
- tools: ['bash', 'file_read', 'file_write'],
-}
-
-// Any OpenAI-compatible API — Ollama, vLLM, LM Studio, etc.
-const localAgent: AgentConfig = {
- name: 'reviewer',
- model: 'llama3.1',
- provider: 'openai',
- baseURL: 'http://localhost:11434/v1',
- apiKey: 'ollama',
- systemPrompt: 'You review code for correctness and clarity.',
- tools: ['file_read', 'grep'],
-}
-
-const team = orchestrator.createTeam('mixed-team', {
- name: 'mixed-team',
- agents: [claudeAgent, gptAgent, localAgent],
- sharedMemory: true,
-})
-
-const result = await orchestrator.runTeam(team, 'Build a CLI tool that converts JSON to CSV.')
-```
-
-
-
-
-Streaming Output
-
-```typescript
-import { Agent, ToolRegistry, ToolExecutor, registerBuiltInTools } from '@jackchen_me/open-multi-agent'
-
-const registry = new ToolRegistry()
-registerBuiltInTools(registry)
-const executor = new ToolExecutor(registry)
-
-const agent = new Agent(
- { name: 'writer', model: 'claude-sonnet-4-6', maxTurns: 3 },
- registry,
- executor,
-)
-
-for await (const event of agent.stream('Explain monads in two sentences.')) {
- if (event.type === 'text' && typeof event.data === 'string') {
- process.stdout.write(event.data)
- }
-}
-```
-
-
+| Example | What it shows |
+|---------|---------------|
+| [01 — Single Agent](examples/01-single-agent.ts) | `runAgent()` one-shot, `stream()` streaming, `prompt()` multi-turn |
+| [02 — Team Collaboration](examples/02-team-collaboration.ts) | `runTeam()` auto-orchestration with coordinator pattern |
+| [03 — Task Pipeline](examples/03-task-pipeline.ts) | `runTasks()` explicit dependency graph (design → implement → test + review) |
+| [04 — Multi-Model Team](examples/04-multi-model-team.ts) | `defineTool()` custom tools, mixed Anthropic + OpenAI providers, `AgentPool` |
+| [05 — Copilot](examples/05-copilot-test.ts) | GitHub Copilot as an LLM provider |
+| [06 — Local Model](examples/06-local-model.ts) | Ollama + Claude in one pipeline via `baseURL` (works with vLLM, LM Studio, etc.) |
+| [07 — Fan-Out / Aggregate](examples/07-fan-out-aggregate.ts) | `runParallel()` MapReduce — 3 analysts in parallel, then synthesize |
## Architecture
diff --git a/README_zh.md b/README_zh.md
index 86436dc..0f38c51 100644
--- a/README_zh.md
+++ b/README_zh.md
@@ -108,165 +108,23 @@ Tokens: 12847 output tokens
-## 更多示例
+## 示例
-
-单智能体 — 一个智能体，一个提示词
+所有示例都是可运行脚本，位于 [`examples/`](./examples/) 目录。使用 `npx tsx` 运行：
-```typescript
-import { OpenMultiAgent } from '@jackchen_me/open-multi-agent'
-
-const orchestrator = new OpenMultiAgent({ defaultModel: 'claude-sonnet-4-6' })
-
-const result = await orchestrator.runAgent(
- {
- name: 'coder',
- model: 'claude-sonnet-4-6',
- tools: ['bash', 'file_write'],
- },
- 'Write a TypeScript function that reverses a string, save it to /tmp/reverse.ts, and run it.',
-)
-
-console.log(result.output)
+```bash
+npx tsx examples/01-single-agent.ts
```
-
-
-
-任务流水线 — 显式控制任务图和分配
-
-```typescript
-const result = await orchestrator.runTasks(team, [
- {
- title: 'Design the data model',
- description: 'Write a TypeScript interface spec to /tmp/spec.md',
- assignee: 'architect',
- },
- {
- title: 'Implement the module',
- description: 'Read /tmp/spec.md and implement the module in /tmp/src/',
- assignee: 'developer',
- dependsOn: ['Design the data model'], // 等待设计完成后才开始
- },
- {
- title: 'Write tests',
- description: 'Read the implementation and write Vitest tests.',
- assignee: 'developer',
- dependsOn: ['Implement the module'],
- },
- {
- title: 'Review code',
- description: 'Review /tmp/src/ and produce a structured code review.',
- assignee: 'reviewer',
- dependsOn: ['Implement the module'], // 可以和测试并行执行
- },
-])
-```
-
-
-
-
-自定义工具 — 使用 Zod schema 定义工具
-
-```typescript
-import { z } from 'zod'
-import { defineTool, Agent, ToolRegistry, ToolExecutor, registerBuiltInTools } from '@jackchen_me/open-multi-agent'
-
-const searchTool = defineTool({
- name: 'web_search',
- description: 'Search the web and return the top results.',
- inputSchema: z.object({
- query: z.string().describe('The search query.'),
- maxResults: z.number().optional().describe('Number of results (default 5).'),
- }),
- execute: async ({ query, maxResults = 5 }) => {
- const results = await mySearchProvider(query, maxResults)
- return { data: JSON.stringify(results), isError: false }
- },
-})
-
-const registry = new ToolRegistry()
-registerBuiltInTools(registry)
-registry.register(searchTool)
-
-const executor = new ToolExecutor(registry)
-const agent = new Agent(
- { name: 'researcher', model: 'claude-sonnet-4-6', tools: ['web_search'] },
- registry,
- executor,
-)
-
-const result = await agent.run('Find the three most recent TypeScript releases.')
-```
-
-
-
-
-多模型团队 — 在一个工作流中混合使用 Claude、GPT 和本地模型
-
-```typescript
-const claudeAgent: AgentConfig = {
- name: 'strategist',
- model: 'claude-opus-4-6',
- provider: 'anthropic',
- systemPrompt: 'You plan high-level approaches.',
- tools: ['file_write'],
-}
-
-const gptAgent: AgentConfig = {
- name: 'implementer',
- model: 'gpt-5.4',
- provider: 'openai',
- systemPrompt: 'You implement plans as working code.',
- tools: ['bash', 'file_read', 'file_write'],
-}
-
-// 任何 OpenAI 兼容 API — Ollama、vLLM、LM Studio 等
-const localAgent: AgentConfig = {
- name: 'reviewer',
- model: 'llama3.1',
- provider: 'openai',
- baseURL: 'http://localhost:11434/v1',
- apiKey: 'ollama',
- systemPrompt: 'You review code for correctness and clarity.',
- tools: ['file_read', 'grep'],
-}
-
-const team = orchestrator.createTeam('mixed-team', {
- name: 'mixed-team',
- agents: [claudeAgent, gptAgent, localAgent],
- sharedMemory: true,
-})
-
-const result = await orchestrator.runTeam(team, 'Build a CLI tool that converts JSON to CSV.')
-```
-
-
-
-
-流式输出
-
-```typescript
-import { Agent, ToolRegistry, ToolExecutor, registerBuiltInTools } from '@jackchen_me/open-multi-agent'
-
-const registry = new ToolRegistry()
-registerBuiltInTools(registry)
-const executor = new ToolExecutor(registry)
-
-const agent = new Agent(
- { name: 'writer', model: 'claude-sonnet-4-6', maxTurns: 3 },
- registry,
- executor,
-)
-
-for await (const event of agent.stream('Explain monads in two sentences.')) {
- if (event.type === 'text' && typeof event.data === 'string') {
- process.stdout.write(event.data)
- }
-}
-```
-
-
+| 示例 | 展示内容 |
+|------|----------|
+| [01 — 单智能体](examples/01-single-agent.ts) | `runAgent()` 单次调用、`stream()` 流式输出、`prompt()` 多轮对话 |
+| [02 — 团队协作](examples/02-team-collaboration.ts) | `runTeam()` 自动编排 + 协调者模式 |
+| [03 — 任务流水线](examples/03-task-pipeline.ts) | `runTasks()` 显式依赖图（设计 → 实现 → 测试 + 评审） |
+| [04 — 多模型团队](examples/04-multi-model-team.ts) | `defineTool()` 自定义工具、Anthropic + OpenAI 混合、`AgentPool` |
+| [05 — Copilot](examples/05-copilot-test.ts) | GitHub Copilot 作为 LLM 提供者 |
+| [06 — 本地模型](examples/06-local-model.ts) | Ollama + Claude 混合流水线，通过 `baseURL` 接入（兼容 vLLM、LM Studio 等） |
+| [07 — 扇出聚合](examples/07-fan-out-aggregate.ts) | `runParallel()` MapReduce — 3 个分析师并行，然后综合 |
## 架构