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⚔️ 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 · Contributing

OpenClaw Python Agents Dashboard License Zero Dependencies

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🎬 Demo

Your browser does not support video playback. See the GIF below or download the video.
🎥 Full demo: AI Multi-Agent collaboration with Three Departments & Six Ministries

📸 GIF Preview (loads faster)

Edict Demo
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.


💡 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

🤔 Why Edict?

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

CrewAIMetaGPTAutoGenEdict
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 complexityMedHighMedLow · 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.


✨ 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)

PanelDescription
📋 Edicts KanbanTask cards by state, filters, search, heartbeat badges, stop/cancel/resume
🔭 Department MonitorPipeline visualization, distribution charts, health cards
📜 Memorial ArchiveAuto-generated archives with 5-phase timeline
📜 Edict Templates9 presets with parameter forms, cost estimates, one-click dispatch
👥 Officials OverviewToken leaderboard, activity stats
📰 Daily BriefingAuto-curated news, subscription management, Feishu push
⚙️ Model ConfigPer-agent LLM switching, automatic Gateway restart
🛠️ Skills ConfigView installed skills, add new ones
💬 SessionsLive session monitoring with channel labels
🎬 Court CeremonyImmersive daily opening animation with stats

🖼️ Screenshots

Edicts Kanban

Kanban

📸 More screenshots

Agent Monitor

Monitor

Task Detail

Detail

Model Config

Models

Skills

Skills

Officials

Officials

Sessions

Sessions

Memorials Archive

Memorials

Command Templates

Templates

Daily Briefing

Briefing

Court Ceremony

Ceremony


🚀 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.


🏛️ 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

DeptAgent IDRoleExpertise
👑 Crown PrincetaiziTriage, summarizeChat detection, intent extraction
📜 PlanningzhongshuReceive, plan, decomposeRequirements, architecture
🔍 ReviewmenxiaAudit, gatekeep, vetoQuality, risk, standards
📮 DispatchshangshuAssign, coordinate, collectScheduling, tracking
💰 FinancehubuData, resources, accountingData processing, reports
📝 DocumentationlibuDocs, standards, reportsTech writing, API docs
⚔️ EngineeringbingbuCode, algorithms, checksDevelopment, code review
⚖️ CompliancexingbuSecurity, compliance, auditSecurity scanning
🔧 InfrastructuregongbuCI/CD, deploy, toolingDocker, pipelines
📋 HRlibu_hrAgent management, trainingRegistration, permissions
🌅 BriefingzaochaoDaily briefing, newsScheduled reports, summaries

Permission Matrix

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

State Machine

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

📁 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

🔧 Technical Highlights

React 18 FrontendTypeScript + Vite + Zustand, 13 components
stdlib Backendserver.py on http.server, zero dependencies
Agent Thinking VisibleReal-time display of agent thinking, tool calls, results
One-click InstallWorkspace creation to Gateway restart
15s Auto-syncLive data refresh with countdown
Daily CeremonyImmersive opening animation

🗺️ 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

🤝 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

� Examples

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

ExampleCommandDepartments
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.


📄 License

MIT · Built by the OpenClaw community


📮 WeChat · Behind the Scenes

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

WeChat QR · cft0808
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

⭐ Star History

Star History Chart


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

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