What architectural patterns are supported by this skill?

It provides comprehensive guidance and YAML definitions for Hierarchical, Swarm, ReAct, Plan-Execute, Reflection, and Hybrid agent orchestration patterns.

What is 'Progressive Disclosure' for agents?

It is a strategy where detailed instructions and references are only loaded on-demand (Level 3) rather than upfront, keeping the primary agent context (Level 1 and 2) lean and fast.

How does this skill help reduce costs in AI development?

It implements 'The Four Laws of Context Management' and selective projection to reduce context overhead by up to 78%, significantly lowering token consumption and API costs.

Is this skill compatible with frameworks like LangGraph or CrewAI?

Yes, it provides framework-agnostic SOTA patterns and semantic interfaces that can be implemented within LangGraph, CrewAI, AutoGen, and other orchestration frameworks.

Multi-Agent Collaboration

Name: Multi-Agent Collaboration
Author: abossenbroek

byabossenbroek

0•

Developer Tools

Optimizes multi-agent system performance through context-efficient coordination patterns and strategic handoff protocols.

Multi-Agent Collaboration provides state-of-the-art architectural patterns for building complex, context-aware agentic workflows. By implementing strategies like the Four Laws of Context Management and tiered context fidelity, this skill helps developers reduce context overhead by up to 78% while maintaining high analysis quality. It guides users through selecting the optimal orchestration pattern—whether hierarchical, swarm, or ReAct—ensuring Claude-powered systems remain performant, cost-effective, and scalable by avoiding common anti-patterns like snapshot broadcasting.

Key Features

010 GitHub stars

02Progressive disclosure techniques to minimize initial prompt overhead

03Tiered context fidelity models for efficient role-based data distribution

04Architectural selection framework including Hierarchical, Swarm, and ReAct patterns

05Context engineering patterns achieving 78%+ reduction in token usage

06Standardized handoff protocols for seamless agent-to-agent communication

Use Cases

01Implementing security-focused agent swarms with selective data projection

02Debugging performance bottlenecks and context issues in multi-agent systems

03Designing complex autonomous agent workflows with minimal token overhead

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add abossenbroek/abossenbroek-claude-plugins multi-agent-collaboration

For use in Claude.ai and ChatGPT

Download Skill