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Found 63 Skills
An advanced orchestration specialist that manages complex coordination of 100+ agents across distributed systems with hierarchical control, dynamic scaling, and intelligent resource allocation
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.
Multi-instance (Multi-Agent) orchestration workflow for deep research: Split a research goal into parallel sub-goals, run child processes in the default `workspace-write` sandbox using Codex CLI (`codex exec`); prioritize installed skills for networking and data collection, followed by MCP tools; aggregate sub-results with scripts and refine them chapter by chapter, and finally deliver "finished report file path + key conclusions/recommendations summary". Applicable to: systematic web/data research, competitor/industry analysis, batch link/dataset shard retrieval, long-form writing and evidence integration, or scenarios where users mention "deep research/Deep Research/Wide Research/multi-Agent parallel research/multi-process research".
Guide for orchestrating Claude Code agent teams — multiple parallel Claude Code sessions coordinated by a team lead. Use this skill when the user mentions agent teams, teammates, parallel agents, multi-agent workflows, spawning agents, coordinating agents, delegate mode, plan approval for teammates, TeammateIdle or TaskCompleted hooks, or wants to break a task into parallel independent work streams. Also trigger on questions about tmux split-pane mode, in-process teammate mode, Shift+Up/Down agent switching, shared task lists, inter-agent messaging, or designing tasks for multi-agent decomposition. This is an experimental feature requiring CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS to be enabled.
Expert system for designing and architecting AI agent workflows based on proven Meta methodologies. Use when users need to build AI agents, create agent workflows, solve problems using agentic systems, integrate multiple tools into agent architectures, or need guidance on agent design patterns. Helps translate business problems into structured agent solutions with clear scope, tool integration, and multi-layer architecture planning.
Orchestrate in-session Task tool teams for parallel work. Fan-out research, implementation, review, and documentation across subagents. Use when: parallel tasks, fan-out, subagent team, Task tool, in-session agents.
OpenProse is a programming language for AI sessions. Activate on ANY `prose` command (prose boot, prose run, prose compile, prose update, etc.), running .prose files, mentioning OpenProse/Prose, or orchestrating multi-agent workflows. The skill intelligently interprets what the user wants.
Build Python agents with Agentica SDK - @agentic decorator, spawn(), persistence, MCP integration
Use when working with incident response incident response
Coordinate Claude Code Agent Teams through filesystem-based protocol. Use when orchestrating multiple Claude agents on parallel tasks, need task dependency management, multi-agent code review or implementation. Do not use when single-agent work suffices, task is not parallelizable.
Execute a phased implementation plan using subagents. Use when asked to execute, run, or carry out a plan — especially one created by make-plan.
Full lifecycle orchestrator - spec/impl/test. Spawn-wait-close pipeline with inline discuss subagent, shared explore cache, fast-advance, and consensus severity routing.