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Found 518 Skills
Amazon Bedrock AgentCore multi-agent orchestration with Agent-to-Agent (A2A) protocol. Supervisor-worker patterns, agent collaboration, and hierarchical delegation. Use when building multi-agent systems, orchestrating specialized agents, or implementing complex workflows.
Use when designing multi-agent systems, implementing supervisor patterns, coordinating multiple agents, or asking about "multi-agent", "supervisor pattern", "swarm", "agent handoffs", "orchestration", "parallel agents"
Guide for coordinating PM, Frontend, Backend, Mobile, and QA agents on complex projects via CLI
TypeScript-native multi-agent orchestration framework that decomposes goals into task DAGs automatically with MCP and live tracing
Guides engineering of multi-agent systems—agent roles and specialization, orchestration topologies (supervisor, peer-to-peer, hierarchical, blackboard), task decomposition and routing, inter-agent messaging (A2A-style patterns), shared vs partitioned state, fan-out/fan-in and DAG workflows, synchronization and consensus, conflict resolution, fault tolerance and retries across agents, cost/latency/token budgets, cross-agent observability, testing multi-agent flows, and deployment (queues, durable workflows). Framework-agnostic; high-level LangGraph, Deep Agents, and agenthub—not single-agent loops (agentic-ai-developer), ML training (ai-engineer), strategy-only whiteboard (enterprise-strategist), or PM planning (technical-program-manager). Use for multi-agent system, multi-agent engineer, agent orchestration, supervisor agent, agent topology, fan-out fan-in, agent handoff protocol, multi-agent workflow, agent coordination, blackboard pattern, hierarchical agents, A2A, agent DAG, multi-agent architecture.
Synchronize work between Antigravity and Claude Code agents
Multi-agent PR and code review workflow for projects using multiple AI assistants (Claude, GitHub Copilot/Codex, Gemini Code Assist). Use when working with pull requests, code reviews, commits, or addressing review feedback. Teaches how to check all feedback sources (conversation, inline, reviews), respond to inline bot comments, create Fix Reports, and coordinate between agents that use different comment formats. Critical for ensuring no feedback is missed from external review bots.
Design multi-agent architectures for complex tasks. Use when single-agent context limits are exceeded, when tasks decompose naturally into subtasks, or when specializing agents improves quality.
oh-my-claudecode — Teams-first multi-agent orchestration layer for Claude Code. 32 specialized agents, smart model routing, persistent execution loops, and real-time HUD visibility. Zero learning curve.
Ultimate multi-agent framework for Google Antigravity. Orchestrates specialized domain agents (PM, Frontend, Backend, Mobile, QA, Debug) via Serena Memory.
Multi-agent orchestration layer for OpenAI Codex CLI. Provides 30 specialized agents, 40+ workflow skills, team orchestration in tmux, persistent MCP servers, and staged pipeline execution.
Use the Orca CLI to coordinate multiple coding agents via inter-agent messaging, task DAGs, dispatch with preamble injection, decision gates, and coordinator loops. Use when an agent needs to send or check inter-agent messages; create, dispatch, or track orchestration tasks; coordinate multi-agent workflows; or act as a coordinator dispatching work across terminals. Triggers include "orchestrate agents", "dispatch task", "send message to agent", "check inbox", "coordinate agents", "multi-agent", "create task DAG", "worker_done", "escalation", or any task involving inter-agent coordination through Orca.