Multi-Agent System Architecture with Claude
Design and implement scalable multi-agent systems with Claude
What You Can Do
This skill guides you through architecting production-grade multi-agent systems that orchestrate multiple Claude instances to solve complex problems in parallel. You'll learn proven patterns for agent communication, task decomposition, resource allocation, and failure handling—plus get templates for coordination protocols and monitoring dashboards.
Features
templates for supervisor, peer-to-peer, and pipeline architectures with code examples
decision trees for breaking monolithic problems into agent-sized subtasks with dependency tracking
standardized schemas for inter-agent communication with retry logic and timeout handling
patterns for graceful degradation, fallback agents, and circuit breakers when agents fail
monitor token usage, queue pending tasks, and auto-scale agent pools based on load
verify agent compatibility, test communication paths, and validate end-to-end workflows
manage shared knowledge bases, coordinate agent context, and prevent race conditions
measure agent latency, throughput, and cost; identify bottlenecks
Example Output
Example 1: Supervisor Architecture
Input: "Analyze sales data and generate quarterly report"
Supervisor Agent:
- Routes to Data Analysis Agent: Fetches sales metrics
- Routes to Insights Agent: Identifies trends
- Routes to Writing Agent: Compiles final report
- Aggregates results into polished deliverable
Output: Structured report with tables, charts, and executive summary
Example 2: Peer Coordination Protocol
Message schema:
{
"sender_id": "agent-3",
"task_id": "task-842",
"action": "request_validation",
"payload": {...},
"priority": "high",
"timeout_ms": 5000
}
Response routing: Fastest responding peer validates → broadcasts result to all agents
Example 3: Failure Recovery
Scenario: Primary agent times out
- Supervisor detects timeout after 5s
- Fallback agent activated with reduced problem scope
- Result merged with partial output from primary
- Incident logged for analysis
What's Included
- SKILL.md: Complete architecture guide with decision trees, coordinator pseudocode, and tradeoff analysis
- Agent Orchestration Template: Boilerplate supervisor and worker agent implementations
- Communication Protocol Spec: JSON schema for inter-agent messages with versioning strategy
- Failure Handling Checklist: Step-by-step verification for timeout detection, retry logic, and graceful degradation
- Task Decomposition Worksheet: Template for breaking problems into agent-sized subtasks with dependency diagrams
- Resource Monitoring Dashboard: Template for tracking token usage, agent health, and queue depth
- Integration Test Plan: Scenarios for verifying multi-agent coordination under load
Who It's For
- AI/ML Engineers building production multi-agent systems and needing architectural guidance
- Platform Architects designing scalable systems that coordinate multiple AI models
- DevOps Teams managing agent deployments, monitoring, and orchestration infrastructure
- Product Managers planning agent-based features and understanding coordination trade-offs
- Researchers experimenting with emergent behavior in agent networks
Best For
- Designing distributed systems where multiple Claude instances collaborate on a shared goal
- Decomposing complex workflows into parallelizable agent tasks
- Building resilient systems that gracefully handle agent failures and bottlenecks
- Optimizing token usage and cost through intelligent task distribution and caching
- Implementing real-time monitoring and observability for agent behavior at scale
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