- name
- multi-agent-orchestrator
- description
- Design, build, and manage multi-agent teams that turn a solo operator into a 1000-person organization. Covers team role design (CEO/PM/Engineer/Analyst/Writer/Monitor), inter-agent communication patterns, task distribution, conflict resolution, and priority management. Based on real production experience running 13-agent teams on OpenClaw. Use when the user wants to build an agent team, orchestrate multiple AI agents, design agent roles, set up agent communication, create a one-person company with AI agents, implement multi-agent workflows, or scale from solo to team-of-agents. Triggers on multi-agent, agent team, agent orchestration, AI team, agent collaboration, agent roles, one-person company, solo founder scaling, agent communication, task delegation to agents, swarm intelligence.
Multi-Agent Orchestrator
Build production-grade agent teams. Battle-tested with 13 concurrent agents running real operations—financial analysis, content production, code engineering, and executive decision-making.
Core Philosophy
One human, many agents. Each agent has a narrow, well-defined role. Communication flows through structured channels. The human sets direction; agents handle execution.
Three laws of agent teams:
- Specialization over generality — Each agent does ONE thing well
- Structured communication — No ad-hoc messaging; use defined protocols
- Human-in-the-loop for decisions — Agents execute, humans decide
Workflow
Step 1: Define Your Team Composition
Read references/team-roles.md to select roles from the template library.
Start minimal (3 agents), scale to what you need:
| Team Size | Composition | Use Case |
|---|---|---|
| Solo+1 | Human + 1 Assistant | Personal productivity boost |
| Core (3) | CEO + PM + Engineer | Small project delivery |
| Full (5+) | + Analyst + Writer + Monitor | Business operations |
| Enterprise (8+) | + Specialist roles per domain | Multi-domain scaling |
Step 2: Design Communication Architecture
Read references/communication-patterns.md for protocol details.
Choose your communication stack:
| Pattern | Latency | Best For |
|---|---|---|
| Shared directory | Minutes | Async handoffs, document sharing |
| Message passing (sessions_send) | Seconds | Real-time coordination |
| Heartbeat scheduling | Periodic | Monitoring, health checks |
| Event queue | Async | Complex multi-step workflows |
Step 3: Set Up Task Management
Read references/task-management.md for tracking systems and report formats.
Implement the three-layer task system:
- Strategic (CEO layer) — Goals and OKRs
- Tactical (PM layer) — Sprint planning and allocation
- Operational (Engineer layer) — Ticket execution and delivery
Step 4: Launch and Iterate
# Minimum viable team setup
1. Create AGENTS.md for each agent with role + scope
2. Set up shared directory structure
3. Define reporting cadence
4. Run first task cycle
5. Review and adjust roles/communicationQuick-Start Templates
Solo Founder Starter Pack (3 agents)
CEO (Strategic) — Owns vision, priorities, decision gates PM (Coordination) — Translates goals into tasks, tracks progress Engineer (Execution) — Builds, tests, ships
Content Machine (4 agents)
Strategist — Topic research, audience analysis, content calendar Writer — Draft production, SEO optimization Editor — Quality review, brand voice consistency Publisher — Distribution, scheduling, performance tracking
Research & Analysis (4 agents)
Data Collector — Gather raw data from sources Analyst — Process, analyze, identify patterns Synthesizer — Produce actionable reports Monitor — Track changes, alert on anomalies
Anti-Patterns (Learn from Our Mistakes)
| Anti-Pattern | Why It Fails | Fix |
|---|---|---|
| Agent with 5+ responsibilities | Context thrashing, low quality | Split into specialized agents |
| All-to-all communication | Message chaos, conflicts | Hub-and-spoke or hierarchical |
| No escalation path | Decisions stall, work stops | Define clear human escalation triggers |
| Copy-paste between agents | Knowledge silos, inconsistency | Shared knowledge base or wiki |
| Agents making strategic decisions | Misaligned with human intent | Agents propose, humans dispose |
Platform Compatibility
This skill is platform-agnostic. The principles apply to:
- OpenClaw — Native multi-agent with sessions_send, shared dirs, cron
- Claude Code — Multiple sessions with file-based coordination
- Codex — Task files and workspace sharing
- Cursor — Agent rules files (.cursor/rules/) with workspace coordination
Real-World Case Study
晟瑞智联 AI Team (13 agents, OpenClaw)
┌─────────┐
│ 于哥 │ (Human CEO)
└────┬────┘
│
┌────┴────┐
│ 老A │ (CEO Agent / Strategic)
│ Friday │ (Executive Assistant)
└────┬────┘
│
┌──────────────┼──────────────┐
│ │ │
┌────┴────┐ ┌────┴────┐ ┌────┴────┐
│ 艾琳 │ │ 瓦里斯 │ │ 唐 │
│ (PM) │ │(Engineer)│ │(Writer) │
└────┬────┘ └────┬────┘ └────┬────┘
│ │ │
┌────┴────┐ ┌────┴────┐ ┌────┴────┐
│Simons │ │ 小E │ │ +6 │
│(Analyst)│ │(Monitor)│ │specialists│
└─────────┘ └─────────┘ └─────────┘Communication: Shared directories for async, sessions_send for real-time, cron-based heartbeat for monitoring.
References
- Team Roles:
references/team-roles.md— Complete role templates with AGENTS.md examples - Communication:
references/communication-patterns.md— Protocols, file structures, message formats - Task Management:
references/task-management.md— Tracking systems, report formats, escalation rules