agentic-systems

Provide design patterns for autonomous agents and multi-agent systems.

1|Updated Mar 6, 2026
One-click install
npx skills add https://github.com/davekim917/bootstrap --skill agentic-systems
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: agentic-systems
Source: https://github.com/davekim917/bootstrap/tree/main/plugins/domain/skills/agentic-systems
Command: npx skills add https://github.com/davekim917/bootstrap --skill agentic-systems

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Design patterns and architectures for building autonomous agents and multi-agent systems.

Core Features & Use Cases

  • ReAct-style and Plan-and-Execute agent loop patterns to manage decision and action cycles.
  • Orchestrator/Worker and Peer-to-Peer multi-agent architectures for scalable collaboration.
  • Tool design, memory systems, and HITL safety guards to ensure reliability and governance in production.

Quick Start

Set up a basic autonomous agent loop with an orchestrator and worker to begin planning and execution.

Frequently Asked Questions about agentic-systems

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

FAQPage Schema
What design patterns are used for building autonomous agents?

Autonomous agents use design patterns like ReAct and Plan-and-Execute loops to manage decision and action cycles. These patterns structure how agents reason about tasks, select tools, and evaluate outcomes during autonomous operation.

How do I structure a multi-agent system for scalable collaboration?

Multi-agent systems can be structured using Orchestrator/Worker or Peer-to-Peer architectures. These patterns enable scalable collaboration by defining clear roles for task delegation, inter-agent communication, and coordinated execution across multiple autonomous agents.

What safeguards do I need for human-in-the-loop agent workflows?

Human-in-the-loop (HITL) workflows require safety guards, explicit iteration caps, and error handling protocols. These safeguards ensure reliable governance by allowing human oversight of autonomous decisions, safe tool use, and inter-agent trust in production environments.

Can I use MCP protocols for tool integration in multi-agent systems?

Yes, MCP protocols can be applied for tool integration in multi-agent systems. Tool design and memory systems work with MCP to standardize how autonomous agents access external capabilities, manage context, and execute actions safely.

How does observability work in autonomous agent loops?

Observability in autonomous agent loops tracks decision cycles, tool execution, and inter-agent communication. It provides visibility into ReAct patterns, memory usage, and error handling to maintain reliability and debug production agent workflows.

When should I use Orchestrator/Worker vs Peer-to-Peer agent architectures?

Use Orchestrator/Worker architectures when you need centralized task delegation and control, and Peer-to-Peer when agents need equal autonomy for direct collaboration. Both support scalable multi-agent systems with different governance and communication models.