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agent-system-architecture

Design multi-agent system architectures with orchestration patterns and wiring diagrams.

3|Updated Apr 5, 2026
Search Tags:#architecture#multi-agent#orchestration#observability#state-management#agent-design#wiring
One-click install
npx skills add https://github.com/dvy1987/agent-loom --skill agent-system-architecture
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-system-architecture
Source: https://github.com/dvy1987/agent-loom/tree/main/.agents/skills/agent-system-architecture
Command: npx skills add https://github.com/dvy1987/agent-loom --skill agent-system-architecture

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Designing reliable multi-agent systems is complex and error-prone: teams struggle with choosing the right orchestration pattern, defining safe state management, avoiding race conditions, and keeping observability and human-in-the-loop controls in place. This Skill captures proven patterns and hard rules so architects can produce correct, minimal-complexity designs that meet performance, safety, and maintainability constraints.

Core Features & Use Cases

  • Orchestration pattern selection: Guidance for choosing sequential, parallel, hierarchical, handoff, or group-chat wiring based on task ambiguity and coordination costs.
  • Wiring & State strategy: Recommendations for message-passing vs shared-blackboard, triggers, termination conditions, and partitioning outputs to avoid race conditions.
  • Observability & HITL: Templates for supervisor/monitoring components that log token usage, latency, and success/failure rates, and explicit points for human approval on high-risk decisions.
  • Use Case: Designing a parallel PR-review pipeline with specialist agents (quality, security, coverage), a lightweight aggregator, and a Mermaid wiring diagram plus saved architecture spec.

Quick Start

Design a parallel PR review agent system that runs quality, security, and coverage agents, outputs a Mermaid wiring diagram and an implementation-ready architecture spec.

Frequently Asked Questions about agent-system-architecture

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I design a multi-agent system architecture for complex workflows?▼

Designing a multi-agent system architecture requires selecting an orchestration pattern, defining state management, and mapping observability checkpoints. This Skill produces wiring diagrams and implementation-ready specs for coordinating multiple AI agents across complex workflows.

What is the best way to orchestrate parallel AI agents in a PR review pipeline?▼

The best way to orchestrate parallel PR review agents is using a parallel wiring pattern with specialist agents for quality, security, and coverage, combined with a lightweight aggregator. This approach minimizes race conditions while partitioning outputs for reliable aggregation.

How does state management work when coordinating multiple AI agents?▼

State management for multiple AI agents uses either message-passing or shared-blackboard strategies to route data safely. It involves defining explicit triggers, termination conditions, and partitioning outputs to prevent race conditions across the workflow.

When should I use hierarchical orchestration versus sequential wiring for agent design?▼

Use hierarchical or sequential orchestration patterns based on task ambiguity and coordination costs. Sequential wiring suits linear dependencies, while hierarchical or group-chat patterns handle complex routing and multi-domain orchestration more effectively.

Can I add human-in-the-loop checkpoints to an automated data-processing agent flow?▼

Yes, human-in-the-loop (HITL) checkpoints can be explicitly defined within the agent architecture for high-risk decisions. The design specifies exact approval points alongside monitoring components that log token usage, latency, and success rates.

What are the limitations of group-chat orchestration in multi-agent architectures?▼

Group-chat orchestration limitations include higher coordination costs and potential race conditions if state management is improperly partitioned. This Skill helps identify these constraints and recommends safer wiring patterns when task ambiguity is low.

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