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PM Workbench — AI 产品经理工作台

一句话定位:给产品经理的开源 AI 工作台——会议录音进来,原型/PRD/评审记录出去,Agent 有手、有记忆、还会自己造工具。

English intro below

它解决什么问题

产品经理 80% 的时间耗在"搬运"上:开会记纪要、回来整理成需求、写 PRD、画原型、跟踪评审——每个环节都在重复输入。PM Workbench 把这条流水线交给一个 53 工具的 AI Agent

会议录音(小程序实时转写)
  → AI 总结 + 自动提取需求改动点
  → 一键变更原型(Agent 直接改 HTML)
  → PRD 同步更新 → 评审记录自动留档
  → 需求全流程可追踪

Related MCP server: ProduckAI MCP Server

核心能力

能力

说明

🎙 会议闭环

小程序录音实时转写 → AI 总结 → 需求改动点提取 → 一键派原型 Agent 修改

🤖 53 工具 Agent

主 Agent 编排 + 5 个专业子 Agent(原型/PRD/调研/评审/周报)

🛠 自造工具(创造模式)

跟 Agent 说"造一个工具",它自己创建并立即使用——借鉴 DeepSeek Harness

🧠 越用越聪明

Reflexion 教训回灌 + Voyager 成功打法库 + Mem0 式事实记忆

📋 六环 SOP

一句"走完这个需求",调研→原型→PRD→评审自动流转

📖 MCP 协议

53 工具按标准 MCP 暴露,Claude Code / Cursor 可直连

💰 成本账本

每轮对话 token 成本追踪(DeepSeek 约 ¥0.01/轮)

📱 全端覆盖

Web 工作台 + 微信小程序(录音/零散点捕获)

技术栈

Next.js 14 · TypeScript · DeepSeek(对话模型 + reasoner 双路由)· lowdb · 腾讯云 ASR · 微信小程序

快速开始

git clone https://github.com/huangshu-jing/pm-workbench
cd pm-workbench
npm install
npm run dev
# 打开 http://localhost:3000,设置页填入 DeepSeek API Key 即可

架构(一句话版)

入口(Web / 小程序)→ Orchestrator 主 Agent(意图裁剪/分层提示词/上下文压缩)
  → 子 Agent 层(六环 SOP 流程引擎)
  → 能力层(53 工具 + 自造工具注册表)
  → 记忆层(事实抽取 + 向量检索)→ lowdb 数据层

完整架构借鉴了 Pi Agent、OpenClaw、Mem0、MetaGPT、DeepSeek Harness 的设计,按垂类场景轻量化裁剪。

License

MIT


PM Workbench — AI Workbench for Product Managers

One-liner: An open-source AI workbench for PMs — meeting recordings in, prototypes/PRDs/review records out, with an agent that has hands, memory, and can even build its own tools.

PMs waste 80% of their time on "transporting" information: taking meeting notes, turning them into requirements, writing PRDs, drawing prototypes, tracking reviews. PM Workbench hands this pipeline to a 53-tool AI agent.

  • 🎙 Meeting loop: record on your phone → live transcription → AI summary → extracted change points → one-click prototype edit by agent

  • 🤖 Orchestrator + 5 specialized sub-agents (prototype/PRD/research/review/report)

  • 🛠 Creation mode: say "build me a tool" and the agent creates and uses it immediately (inspired by DeepSeek Harness)

  • 🧠 Gets smarter with use: Reflexion lesson injection + Voyager success-play library + Mem0-style fact memory

  • 📋 Six-stage SOP: say "run this requirement end-to-end" and research→prototype→PRD→review flows automatically

  • 📖 MCP protocol: all 53 tools exposed via standard MCP — connect from Claude Code or Cursor

Stack: Next.js 14 · TypeScript · DeepSeek (chat + reasoner dual routing) · lowdb · Tencent ASR · WeChat Mini Program

git clone https://github.com/huangshu-jing/pm-workbench && cd pm-workbench
npm install && npm run dev

MIT License

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