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docs: update role counts — Chinese 179→211, English 217→170+, total 380+
Role counts now match upstream repos: - agency-agents-zh: 211 (165 translated + 46 China-market originals) - agency-agents: 170+ (actively growing)
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CLAUDE.md

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@@ -9,7 +9,7 @@ ao run <workflow.yaml> [options] # Execute workflow
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ao run <workflow.yaml> --resume last --from <step-id> # Re-run from a specific step
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ao validate <workflow.yaml> # Validate without running
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ao plan <workflow.yaml> # Show DAG execution plan
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ao roles # List all 179 available roles
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ao roles # List all 211 available roles
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```
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## Resume — Iterative Optimization
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## Role Directory
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Roles are in `agency-agents-zh/` (or `node_modules/agency-agents-zh/`). Each role is a `.md` file with frontmatter + system prompt. Use `ao roles` to list all 179 roles.
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Roles are in `agency-agents-zh/` (or `node_modules/agency-agents-zh/`). Each role is a `.md` file with frontmatter + system prompt. Use `ao roles` to list all 211 roles.
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## Project Structure
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README.en.md

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[![License: Apache-2.0](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](./LICENSE)
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[![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg)](./CONTRIBUTING.md)
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**One sentence → full plan · 179 expert AI roles · Zero-code YAML · 9 LLM providers · 6 need no API key**
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**One sentence → full plan · 211 expert AI roles · Zero-code YAML · 9 LLM providers · 6 need no API key**
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> **Note:** `ao compose --run` auto-detects your language. For English input, it uses [agency-agents](https://github.com/msitarzewski/agency-agents) (217 English roles). Use `ao init --lang en` to download the English role library. The 32 built-in workflow templates are currently in Chinese — English templates coming in v0.6.
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> **Note:** `ao compose --run` auto-detects your language. For English input, it uses [agency-agents](https://github.com/msitarzewski/agency-agents) (170+ English roles). Use `ao init --lang en` to download the English role library. The 32 built-in workflow templates are currently in Chinese — English templates coming in v0.6.
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> If you find this useful, please **Star** it — helps others discover the project.
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@@ -46,7 +46,7 @@ ao compose "I'm a programmer looking to start a side hustle with AI content, tar
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==================================================
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```
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**No code. No config. No role selection.** One sentence → AI auto-decomposes the task → matches roles from 179 experts → executes as DAG → outputs a complete plan.
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**No code. No config. No role selection.** One sentence → AI auto-decomposes the task → matches roles from 211 experts → executes as DAG → outputs a complete plan.
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### What Can You Build
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| | ChatGPT / Claude | CrewAI / LangGraph | **Agency Orchestrator** |
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|---|--------|-----------|---------------------|
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| Roles | 1 generalist | Write your own | **179 expert roles** |
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| Roles | 1 generalist | Write your own | **211 expert roles** |
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| Usage | Chat | Write Python | **One sentence / YAML** |
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| API key || Required | **6 providers need none** |
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| Dependencies || pip + dozens of packages | **npm + 2 deps** |
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```bash
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ao demo # Zero-config multi-agent demo
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ao init # Download 179 Chinese AI roles
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ao init --lang en # Download 217 English AI roles
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ao init # Download 211 Chinese AI roles
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ao init --lang en # Download 170+ English AI roles
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ao init --workflow # Interactive workflow creator
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ao compose "description" # AI-powered workflow generation
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ao compose "description" --run # Generate AND execute in one command
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```
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The AI will:
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1. Select matching roles from 179 available (e.g., Code Reviewer, Security Engineer, Performance Benchmarker)
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1. Select matching roles from 211 available (e.g., Code Reviewer, Security Engineer, Performance Benchmarker)
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2. Design the DAG (3-way parallel → summary)
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3. Generate complete YAML with variable passing and task descriptions
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4. Save to `workflows/` — ready to `ao run`
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## Ecosystem
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```
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Your AI subscription ──→ agency-orchestrator ──→ 396 expert roles collaborate ──→ quality output
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│ (179 Chinese + 217 English)
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Your AI subscription ──→ agency-orchestrator ──→ 380+ expert roles collaborate ──→ quality output
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│ (211 Chinese + 170+ English)
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┌────────────────┼────────────────┐
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▼ ▼ ▼
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14 AI Coding Tools CLI Mode MCP Server
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| Project | Description |
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|---------|-------------|
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| [agency-agents](https://github.com/msitarzewski/agency-agents) | 217 English AI role definitions by [@msitarzewski](https://github.com/msitarzewski) — the English role library for this engine |
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| [agency-agents-zh](https://github.com/jnMetaCode/agency-agents-zh) | 179 Chinese AI role definitions — the Chinese role library for this engine |
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| [agency-agents](https://github.com/msitarzewski/agency-agents) | 170+ English AI role definitions by [@msitarzewski](https://github.com/msitarzewski) — the English role library for this engine |
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| [agency-agents-zh](https://github.com/jnMetaCode/agency-agents-zh) | 211 Chinese AI role definitions — the Chinese role library for this engine |
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| [ai-coding-guide](https://github.com/jnMetaCode/ai-coding-guide) | AI coding tools field guide — 66 Claude Code tips + 9 tools best practices + copyable config templates |
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| [superpowers-zh](https://github.com/jnMetaCode/superpowers-zh) | AI coding superpowers — 20 skills for Claude Code / Cursor |
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| [shellward](https://github.com/jnMetaCode/shellward) | AI agent security middleware — prompt injection detection, DLP, command safety |

README.md

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[![License: Apache-2.0](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](./LICENSE)
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[![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg)](./CONTRIBUTING.md)
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**一句话出结果 · 179 个专业 AI 角色 · YAML 零代码 · 9 种大模型 · 6 种免 API key**
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**一句话出结果 · 211 个专业 AI 角色 · YAML 零代码 · 9 种大模型 · 6 种免 API key**
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> 觉得有用?请点个 **Star** — 帮助更多人发现这个项目。
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==================================================
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```
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**不用写代码,不用写配置,不用选角色。** 一句话 → AI 自动拆解任务 → 从 179 个角色中匹配 → 按 DAG 并行执行 → 输出完整方案。
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**不用写代码,不用写配置,不用选角色。** 一句话 → AI 自动拆解任务 → 从 211 个角色中匹配 → 按 DAG 并行执行 → 输出完整方案。
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### 你能用它做什么
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| | ChatGPT / Claude | CrewAI / LangGraph | **Agency Orchestrator** |
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|---|--------|-----------|---------------------|
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| 角色数 | 1 个通用 | 自己写 | **179 个专业角色** |
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| 角色数 | 1 个通用 | 自己写 | **211 个专业角色** |
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| 使用方式 | 对话 | 写 Python | **一句话 / YAML** |
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| API key || 必须 | **6 种免 API key** |
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| 依赖 || pip + 几十个包 | **npm + 2 个依赖** |
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| 并行 || 手动建图 | **DAG 自动检测** |
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| 中文角色 ||| **179** |
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| 中文角色 ||| **211** |
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| 价格 | 订阅制 | 开源 + API 费 | **完全免费** |
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## 3 步开始
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```bash
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ao demo # 零配置体验多智能体协作
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ao init # 下载 179 个中文 AI 角色
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ao init --lang en # 下载 217 个英文 AI 角色
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ao init # 下载 211 个中文 AI 角色
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ao init --lang en # 下载 170+ 个英文 AI 角色
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ao init --workflow # 交互式创建工作流
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ao compose "一句话描述" # AI 智能编排工作流
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ao compose "一句话描述" --run # 编排并立即执行
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### AI 智能编排(Compose)
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一句话描述需求,AI 自动从 179 个角色中选角色、设计 DAG、生成完整 workflow YAML:
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一句话描述需求,AI 自动从 211 个角色中选角色、设计 DAG、生成完整 workflow YAML:
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```bash
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ao compose "PR 代码审查,要覆盖安全和性能"
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```
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AI 会自动:
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1.179 角色中匹配出 Code Reviewer、Security Engineer、Performance Benchmarker
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1.211 角色中匹配出 Code Reviewer、Security Engineer、Performance Benchmarker
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2. 设计 DAG(三路并行 → 汇总)
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3. 生成带 `depends_on`、变量串联的完整 YAML
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4. 保存到 `workflows/` — 直接 `ao run` 就能跑
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## 生态与社区
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```
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你的 AI 会员 ──→ agency-orchestrator ──→ 396 个 AI 角色协作 ──→ 高质量输出
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│ (179 中文 + 217 英文)
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你的 AI 会员 ──→ agency-orchestrator ──→ 380+ 个 AI 角色协作 ──→ 高质量输出
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│ (211 中文 + 170+ 英文)
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┌────────────────┼────────────────┐
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▼ ▼ ▼
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14 个 AI 编程工具 CLI 模式 MCP Server
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| 项目 | 说明 |
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|------|------|
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| [agency-agents-zh](https://github.com/jnMetaCode/agency-agents-zh) | 179 个中文 AI 角色定义 — 本引擎的中文角色库 |
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| [agency-agents](https://github.com/msitarzewski/agency-agents) | 217 个英文 AI 角色定义 by [@msitarzewski](https://github.com/msitarzewski) — 本引擎的英文角色库 |
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| [agency-agents-zh](https://github.com/jnMetaCode/agency-agents-zh) | 211 个中文 AI 角色定义 — 本引擎的中文角色库 |
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| [agency-agents](https://github.com/msitarzewski/agency-agents) | 170+ 个英文 AI 角色定义 by [@msitarzewski](https://github.com/msitarzewski) — 本引擎的英文角色库 |
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| [ai-coding-guide](https://github.com/jnMetaCode/ai-coding-guide) | AI 编程工具实战指南 — 66 个 Claude Code 技巧 + 9 款工具最佳实践 + 可复制配置模板 |
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| [superpowers-zh](https://github.com/jnMetaCode/superpowers-zh) | AI 编程超能力 · 中文版 — 20 个 skills,让你的 AI 编程助手真正会干活 |
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| [shellward](https://github.com/jnMetaCode/shellward) | AI 智能体安全中间件 — 注入检测、数据防泄露、命令安全、零依赖、MCP Server |

docs/PRD.md

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## 解决什么问题
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agency-agents 定义了 179 个 AI 角色的「能力边界」(能做什么、怎么做),但缺少「协作层」:
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agency-agents 定义了 211 个 AI 角色的「能力边界」(能做什么、怎么做),但缺少「协作层」:
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- 一个任务需要多个角色配合时,谁先谁后?
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| | CrewAI | LangGraph | 本项目 |
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| 语言 | Python | Python | TypeScript(Node.js 生态) |
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| 角色定义 | 自己写 | 自己写 | **179 个现成中文角色,一行引用** |
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| 角色定义 | 自己写 | 自己写 | **211 个现成中文角色,一行引用** |
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| 上手成本 | 写 Python 类 | 学图概念 | **写 YAML** |
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| 中文适配 ||| **原生中文** |
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| 安全层 ||| **可选集成 shellward** |
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核心差异:别人是「给你一个框架,角色你自己写」,我们是「角色已经写好 179 个,你只需要编排」。
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核心差异:别人是「给你一个框架,角色你自己写」,我们是「角色已经写好 211 个,你只需要编排」。
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## 核心设计原则
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## 与现有项目的关系
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```
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agency-agents-zh (179 个角色定义)
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agency-agents-zh (211 个角色定义)
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▼ 引用
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agency-orchestrator (编排引擎) ← 本项目

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