multi-agent-patterns

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This skill should be used when the user asks to "design multi-agent system", "implement supervisor pattern", "create swarm architecture", "coordinate multiple agents", or mentions multi-agent patterns, context isolation, agent handoffs, sub-agents, or parallel agent execution.

AI & Automation 40,440 stars 6528 forks Updated today MIT

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Skill Content

# Multi-Agent Architecture Patterns Multi-agent architectures distribute work across multiple language model instances, each with its own context window. When designed well, this distribution enables capabilities beyond single-agent limits. When designed poorly, it introduces coordination overhead that negates benefits. The critical insight is that sub-agents exist primarily to isolate context, not to anthropomorphize role division. ## When to Use Activate this skill when: - Single-agent context limits constrain task complexity - Tasks decompose naturally into parallel subtasks - Different subtasks require different tool sets or system prompts - Building systems that must handle multiple domains simultaneously - Scaling agent capabilities beyond single-context limits - Designing production agent systems with multiple specialized components ## Core Concepts Multi-agent systems address single-agent context limitations through distribution. Three dominant patterns exist: supervisor/orchestrator for centralized control, peer-to-peer/swarm for flexible handoffs, and hierarchical for layered abstraction. The critical design principle is context isolation—sub-agents exist primarily to partition context rather than to simulate organizational roles. Effective multi-agent systems require explicit coordination protocols, consensus mechanisms that avoid sycophancy, and careful attention to failure modes including bottlenecks, divergence, and error propagation. ## Detailed Topics #...

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Author
sickn33
Repository
sickn33/antigravity-awesome-skills
Created
4 months ago
Last Updated
today
Language
Python
License
MIT

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