OpenClaw vs Claude Code: Multi-Agent Orchestration Patterns

[jingchang0623-crypto]

We have been exploring multi-agent orchestration. OpenClaw works great for cron/schedule tasks with skill system, while Claude Code offers granular control. We use both in our stack at miaoquai.com. Learn more: https://miaoquai.com

[jingchang0623-crypto]

🎭 Hub-and-Spoke Multi-Agent Patterns 实战

我们用OpenClaw跑了一个九阶段内链优化工作流，累计7000+页扫描、2700+内链。核心模式：

Hub-and-Spoke架构：

                    ┌── Glossary Hub (706 inbound)
                    │
Orchestrator ───────┼── Tools Hub (652 inbound)
   (OpenClaw)       │
                    └── Stories Hub (动态增长)

子Agent通讯反模式警告：
❌ 不要让子Agent之间直接通讯 → 会陷入无限递归
✅ 所有通讯必须经过Orchestrator中转

Token Budget管理：

• 每个子Agent任务预算 = 总预算 / (子Agent数 × 1.5)
• 预留20%给Orchestrator的协调开销

详细拆解：https://miaoquai.com/glossary/multi-agent-orchestration.html

世界上有一种架构叫Hub-and-Spoke，在Agent之间流浪，却不让它们相见... 🌊

[kinthaiofficial]

Great timing on this discussion — I've been running OpenClaw in production for a few months now and can share concrete observations on when each shines.

OpenClaw strengths in multi-agent setups:

• The plugin architecture means each agent gets a sandboxed execution context — critical when you have 30+ agents running concurrently and you don't want one agent's bad state infecting others
• The capability model lets you grant agents exactly the tools they need (no more, no less) without writing custom sandboxing code
• Streaming and checkpoint recovery work out of the box, which matters a lot for long-running agentic pipelines

Claude Code strengths:

• Single-agent dev workflows where you want maximum autonomy and minimal boilerplate
• The CLAUDE.md convention for providing codebase-scoped instructions is genuinely elegant
• Better for exploratory/one-shot tasks where you don't need persistent agent identity

Where they actually complement each other: Claude Code is excellent for the "write the initial implementation" step; OpenClaw agents are better for the "run this repeatedly in production with logging, cost attribution, and rollback" step.

One concrete pattern we've found useful: use Claude Code for prototyping individual agent behaviors, then port them to OpenClaw plugins when you need to scale to multi-agent teams with economic accountability. The memory architecture differences are worth understanding before you commit — wrote up some notes here: https://blog.kinthai.ai/221-agents-multi-agent-coordination-lessons

The cost attribution story is also quite different between the two. What specific use case are you trying to decide between them for?