orchestrating-multi-agent-systems

📁 jeremylongshore/claude-code-plugins-plus-skills 📅 Feb 4, 2026
11
总安装量
11
周安装量
#27729
全站排名
安装命令
npx skills add https://github.com/jeremylongshore/claude-code-plugins-plus-skills --skill orchestrating-multi-agent-systems

Agent 安装分布

codex 11
amp 10
github-copilot 10
gemini-cli 10
opencode 10
kimi-cli 9

Skill 文档

Orchestrating Multi Agent Systems

Overview

This skill provides automated assistance for the described functionality.

Prerequisites

Before using this skill, ensure you have:

  • Node.js 18+ installed for TypeScript agent development
  • AI SDK v5 package installed (npm install ai)
  • API keys for AI providers (OpenAI, Anthropic, Google, etc.)
  • Understanding of agent-based architecture patterns
  • TypeScript knowledge for agent implementation
  • Project directory structure for multi-agent systems

Instructions

  1. Create project directory with necessary subdirectories
  2. Initialize npm project with TypeScript configuration
  3. Install AI SDK v5 and provider-specific packages
  4. Set up configuration files for agent orchestration
  5. Write agent initialization code with AI SDK
  6. Configure system prompts for agent behavior
  7. Define tool functions for agent capabilities
  8. Implement handoff rules for inter-agent delegation

See {baseDir}/references/implementation.md for detailed implementation guide.

Output

  • TypeScript files with AI SDK v5 integration
  • System prompts tailored to each agent role
  • Tool definitions and implementations
  • Handoff rules and coordination logic
  • Workflow definitions for task sequences
  • Routing rules for intelligent task distribution

Error Handling

See {baseDir}/references/errors.md for comprehensive error handling.

Examples

See {baseDir}/references/examples.md for detailed examples.

Resources

  • AI SDK v5 official documentation for agent creation
  • Provider-specific integration guides (OpenAI, Anthropic, Google)
  • Tool definition and implementation examples
  • Handoff and routing pattern references
  • Coordinator-worker pattern for task distribution