⚔️ Edict · Multi-Agent Orchestration

I modeled an AI multi-agent system after China's 1,300-year-old imperial governance.
Turns out, ancient bureaucracy understood separation of powers better than modern AI frameworks.

_{12 AI agents (11 business roles + 1 compatibility role) form the Three Departments & Six Ministries: Crown Prince triages, Planning proposes, Review vetoes, Dispatch assigns, Ministries execute.
Built-in institutional review gates that CrewAI doesn't have. A real-time dashboard that AutoGen doesn't have.}

🎬 Demo · 🚀 Quick Start · 🏛️ Architecture · 📋 Features · 中文 · 日本語 · Contributing

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🎬 Demo

_{🎥 Full demo: AI Multi-Agent collaboration with Three Departments & Six Ministries}

📸 GIF Preview (loads faster)

_{Issue edict → Crown Prince triage → Planning → Review → Ministries execute → Report back (30s)}

🐳 No OpenClaw? Run docker run -p 7891:7891 cft0808/edict to try the full dashboard with simulated data.

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💡 The Idea

Most multi-agent frameworks let AI agents talk freely, producing opaque results you can't audit or intervene in. Edict takes a radically different approach — borrowing the governance system that ran China for 1,400 years:

You (Emperor) → Crown Prince (Triage) → Planning Dept → Review Dept → Dispatch Dept → 6 Ministries → Report Back
   皇上              太子               中书省          门下省         尚书省           六部          回奏

This isn't a cute metaphor. It's real separation of powers for AI:

• Crown Prince (太子) triages messages — casual chat gets auto-replied, real commands become tasks
• Planning (中书省) breaks your command into actionable sub-tasks
• Review (门下省) audits the plan — can reject and force re-planning
• Dispatch (尚书省) assigns approved tasks to specialist ministries
• 7 Ministries execute in parallel, each with distinct expertise
• Data sanitization auto-strips file paths, metadata, and junk from task titles
• Everything flows through a real-time dashboard you can monitor and intervene

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🤔 Why Edict?

"Instead of one AI doing everything wrong, 9 specialized agents check each other's work."

	CrewAI	MetaGPT	AutoGen	Edict
Built-in review/veto	❌	⚠️	⚠️	✅ Dedicated reviewer
Real-time Kanban	❌	❌	❌	✅ 10-panel dashboard
Task intervention	❌	❌	❌	✅ Stop / Cancel / Resume
Full audit trail	⚠️	⚠️	❌	✅ Memorial archive
Agent health monitoring	❌	❌	❌	✅ Heartbeat detection
Hot-swap LLM models	❌	❌	❌	✅ From the dashboard
Skill management	❌	❌	❌	✅ View / Add skills
News aggregation	❌	❌	❌	✅ Daily digest + webhook
Setup complexity	Med	High	Med	Low · One-click / Docker

Core differentiator: Institutional review + Full observability + Real-time intervention

🔍 Why the "Review Department" is the killer feature (click to expand)

CrewAI and AutoGen agents work in a "done, ship it" mode — no one checks output quality. It's like a company with no QA department where engineers push code straight to production.

Edict's Review Department (门下省) exists specifically for this:

• 📋 Audit plan quality — Is the Planning Department's decomposition complete and sound?
• 🚫 Veto subpar output — Not a warning. A hard reject that forces re-planning.
• 🔄 Mandatory rework loop — Nothing passes until it meets standards.

This isn't an optional plugin — it's part of the architecture. Every command must pass through Review. No exceptions.

This is why Edict produces reliable results on complex tasks: there's a mandatory quality gate before anything reaches execution. Emperor Taizong figured this out 1,300 years ago — unchecked power inevitably produces errors.

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✨ Features

🏛️ Twelve-Department Agent Architecture

• Crown Prince (太子) message triage — auto-reply casual chat, create tasks for real commands
• Three Departments (Planning · Review · Dispatch) for governance
• Seven Ministries (Finance · Docs · Engineering · Compliance · Infrastructure · HR + Briefing) for execution
• Strict permission matrix — who can message whom is enforced
• Each agent: own workspace, own skills, own LLM model
• Data sanitization — auto-strips file paths, metadata, invalid prefixes from titles/remarks

📋 Command Center Dashboard (10 Panels)

Panel	Description
📋 Edicts Kanban	Task cards by state, filters, search, heartbeat badges, stop/cancel/resume
🔭 Department Monitor	Pipeline visualization, distribution charts, health cards
📜 Memorial Archive	Auto-generated archives with 5-phase timeline
📜 Edict Templates	9 presets with parameter forms, cost estimates, one-click dispatch
👥 Officials Overview	Token leaderboard, activity stats
📰 Daily Briefing	Auto-curated news, subscription management, Feishu push
⚙️ Model Config	Per-agent LLM switching, automatic Gateway restart
🛠️ Skills Config	View installed skills, add new ones
💬 Sessions	Live session monitoring with channel labels
🎬 Court Ceremony	Immersive daily opening animation with stats

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🖼️ Screenshots

Edicts Kanban

📸 More screenshots

Agent Monitor

Task Detail

Model Config

Skills

Officials

Sessions

Memorials Archive

Command Templates

Daily Briefing

Court Ceremony

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🚀 Quick Start

Docker

docker run -p 7891:7891 cft0808/edict

Open http://localhost:7891

Full Install

Prerequisites: OpenClaw · Python 3.9+ · macOS/Linux

git clone https://github.com/cft0808/edict.git
cd edict
chmod +x install.sh && ./install.sh

The installer automatically:

• Creates workspaces for all departments (~/.openclaw/workspace-*, including Crown Prince/HR/Briefing)
• Writes SOUL.md personality files for each department
• Registers agents + permission matrix in openclaw.json
• Initializes data directory + first sync
• Restarts Gateway

Launch

# Terminal 1: Data sync loop (every 15s)
bash scripts/run_loop.sh

# Terminal 2: Dashboard server
python3 dashboard/server.py

# Open browser
open http://127.0.0.1:7891

📖 See Getting Started Guide for detailed walkthrough.

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🏛️ Architecture

                           ┌───────────────────────────────────┐
                           │         👑 Emperor (You)           │
                           │     Feishu · Telegram · Signal     │
                           └─────────────────┬─────────────────┘
                                             │ Issue edict
                           ┌─────────────────▼─────────────────┐
                           │     👑 Crown Prince (太子)          │
                           │   Triage: chat → reply / cmd → task │
                           └─────────────────┬─────────────────┘
                                             │ Forward edict
                           ┌─────────────────▼─────────────────┐
                           │      📜 Planning Dept (中书省)      │
                           │     Receive → Plan → Decompose      │
                           └─────────────────┬─────────────────┘
                                             │ Submit for review
                           ┌─────────────────▼─────────────────┐
                           │       🔍 Review Dept (门下省)       │
                           │     Audit → Approve / Reject 🚫     │
                           └─────────────────┬─────────────────┘
                                             │ Approved ✅
                           ┌─────────────────▼─────────────────┐
                           │      📮 Dispatch Dept (尚书省)      │
                           │   Assign → Coordinate → Collect     │
                           └───┬──────┬──────┬──────┬──────┬───┘
                               │      │      │      │      │
                         ┌─────▼┐ ┌───▼───┐ ┌▼─────┐ ┌───▼─┐ ┌▼─────┐
                         │💰 Fin.│ │📝 Docs│ │⚔️ Eng.│ │⚖️ Law│ │🔧 Ops│
                         │ 户部  │ │ 礼部  │ │ 兵部  │ │ 刑部 │ │ 工部  │
                         └──────┘ └──────┘ └──────┘ └─────┘ └──────┘
                                                               ┌──────┐
                                                               │📋 HR  │
                                                               │ 吏部  │
                                                               └──────┘

Agent Roles

Dept	Agent ID	Role	Expertise
👑 Crown Prince	taizi	Triage, summarize	Chat detection, intent extraction
📜 Planning	zhongshu	Receive, plan, decompose	Requirements, architecture
🔍 Review	menxia	Audit, gatekeep, veto	Quality, risk, standards
📮 Dispatch	shangshu	Assign, coordinate, collect	Scheduling, tracking
💰 Finance	hubu	Data, resources, accounting	Data processing, reports
📝 Documentation	libu	Docs, standards, reports	Tech writing, API docs
⚔️ Engineering	bingbu	Code, algorithms, checks	Development, code review
⚖️ Compliance	xingbu	Security, compliance, audit	Security scanning
🔧 Infrastructure	gongbu	CI/CD, deploy, tooling	Docker, pipelines
📋 HR	libu_hr	Agent management, training	Registration, permissions
🌅 Briefing	zaochao	Daily briefing, news	Scheduled reports, summaries

Permission Matrix

From ↓ \ To →	Prince	Planning	Review	Dispatch	Ministries
Crown Prince	—	✅
Planning	✅	—	✅	✅
Review		✅	—	✅
Dispatch		✅	✅	—	✅ all
Ministries				✅

State Machine

Emperor → Prince Triage → Planning → Review → Assigned → Executing → ✅ Done
                              ↑          │                       │
                              └── Veto ──┘              Blocked ──

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📁 Project Structure

edict/
├── agents/                     # 12 agent personality templates (SOUL.md)
│   ├── taizi/                  #   Crown Prince (triage)
│   ├── zhongshu/               #   Planning Dept
│   ├── menxia/                 #   Review Dept
│   ├── shangshu/               #   Dispatch Dept
│   ├── hubu/ libu/ bingbu/     #   Finance / Docs / Engineering
│   ├── xingbu/ gongbu/         #   Compliance / Infrastructure
│   ├── libu_hr/                #   HR Dept
│   └── zaochao/                #   Morning Briefing
├── dashboard/
│   ├── dashboard.html          # Dashboard (single file, zero deps, works out of the box)
│   ├── dist/                   # Pre-built React frontend (included in Docker image)
│   └── server.py               # API server (stdlib, zero deps)
├── scripts/                    # Data sync & automation scripts
│   ├── kanban_update.py        #   Kanban CLI with data sanitization (~300 lines)
│   └── ...                     #   fetch_morning_news, sync, screenshots, etc.
├── tests/                      # E2E tests
│   └── test_e2e_kanban.py      #   Kanban sanitization tests (17 assertions)
├── data/                       # Runtime data (gitignored)
├── docs/                       # Documentation + screenshots
├── install.sh                  # One-click installer
└── LICENSE                     # MIT

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🔧 Technical Highlights

React 18 Frontend	TypeScript + Vite + Zustand, 13 components
stdlib Backend	server.py on http.server, zero dependencies
Agent Thinking Visible	Real-time display of agent thinking, tool calls, results
One-click Install	Workspace creation to Gateway restart
15s Auto-sync	Live data refresh with countdown
Daily Ceremony	Immersive opening animation

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🗺️ Roadmap

Full roadmap with contribution opportunities: ROADMAP.md

Phase 1 — Core Architecture ✅

• Twelve-department agent architecture + permissions
• Crown Prince triage layer (chat vs task auto-routing)
• Real-time dashboard (10 panels)
• Task stop / cancel / resume
• Memorial archive (5-phase timeline)
• Edict template library (9 presets)
• Court ceremony animation
• Daily news + Feishu webhook push
• Hot-swap LLM models + skill management
• Officials overview + token stats
• Session monitoring
• Edict data sanitization (title/remark cleaning, dirty data rejection)
• Duplicate task overwrite protection
• E2E kanban tests (17 assertions)

Phase 2 — Institutional Depth 🚧

• Imperial approval mode (human-in-the-loop)
• Merit/demerit ledger (agent scoring)
• Express courier (inter-agent message visualization)
• Imperial Archives (knowledge base + citation)

Phase 3 — Ecosystem

• Docker Compose + demo image
• Notion / Linear adapters
• Annual review (yearly performance reports)
• Mobile responsive + PWA
• ClawHub marketplace listing

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🤝 Contributing

All contributions welcome! See CONTRIBUTING.md

• 🎨 UI — themes, responsiveness, animations
• 🤖 New agents — specialized roles
• 📦 Skills — ministry-specific packages
• 🔗 Integrations — Notion · Jira · Linear · GitHub Issues
• 🌐 i18n — Japanese · Korean · Spanish
• 📱 Mobile — responsive, PWA

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<EFBFBD> Examples

The examples/ directory contains real end-to-end use cases:

Example	Command	Departments
Competitive Analysis	"Analyze CrewAI vs AutoGen vs LangGraph"	Planning→Review→Finance+Engineering+Docs
Code Review	"Review this FastAPI code for security issues"	Planning→Review→Engineering+Compliance
Weekly Report	"Generate this week's engineering team report"	Planning→Review→Finance+Docs

Each case includes: Full command → Planning proposal → Review feedback → Ministry outputs → Final report.

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📄 License

MIT · Built by the OpenClaw community

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📮 WeChat · Behind the Scenes

In ancient China, the “Dǐbào” (imperial gazette) delivered edicts across the empire. Today we have a WeChat account.

Scan to follow · cft0808

What you’ll find:

• 🏛️ Architecture deep-dives — how 12 agents achieve separation of powers
• 🔥 War stories — when agents fight, burn tokens, or go on strike
• 💡 Token-saving tricks — run the full pipeline at 1/10 the cost
• 🎭 Behind the SOUL.md — how to write prompts that make AI agents stay in character

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⭐ Star History

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⚔️ Governing AI with the wisdom of ancient empires
_{以古制御新技，以智慧驾驭 AI}