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Found 409 Skills
Spawn and manage parallel AI coding agents via tmux. Use when you need to orchestrate workers, delegate sub-tasks, run multi-agent improvement loops, or manage agent lifecycles with orca CLI commands like spawn, list, kill, steer, logs, and daemon.
Orchestrate multi-agent AI workflows with ultrawork, discipline agents, team mode, and hash-anchored editing for autonomous code development
TypeScript-native multi-agent orchestration framework that decomposes goals into task DAGs automatically with MCP and live tracing
Inter-agent communication patterns including message passing, shared memory, blackboard systems, and event-driven architectures for LLM agentsUse when "agent communication, message passing, inter-agent, blackboard, agent events, multi-agent, communication, message-passing, events, coordination" mentioned.
Multi-agent coordination discipline: one-message-then-wait (send complete context, wait for reply before sending again), idle notifications are heartbeats (no action unless extended + blocking + user asked), no polling loops (event-driven only), never fabricate agent responses (wait for real system events), sequential agent spawning (acknowledge between each), and proper shutdown protocol (request, wait, respect rejection). Activate when orchestrating multiple agents, managing agent teams, coordinating handoffs between agents, spawning subagents, or building multi-agent workflows. Triggers on: "coordinate agents", "spawn multiple agents", "manage agent team", "agent keeps sending messages", "polling loop", "agent idle", "shut down agent", "multi-agent workflow", "agent handoff", "coordinate parallel work", "stop bothering the other agent". Also relevant when an agent is fabricating responses, sending follow-up messages before replies arrive, or reacting to idle notifications unnecessarily.
Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
Multi-agent swarm orchestration where AI agents spawn, coordinate, and self-organize into collaborative teams. Use when running parallel AI agent tasks, orchestrating multi-agent workflows across Claude Code / Codex / Cursor / custom agents, isolating agent workspaces via git worktrees, tracking task dependencies across agents, or running autonomous experiments. Triggers on: clawteam, agent swarm, spawn agents, multi-agent team, agent orchestration, parallel agents, agent coordination, swarm intelligence, agent spawn, clawteam spawn, agent worktree, agentic team, ml agent experiments, autonomous agents, agent team.
Use when a single agent demonstrably cannot handle the task and multi-agent coordination is justified.
LangGraph framework for building stateful, multi-agent AI applications with cyclical workflows, human-in-the-loop patterns, and persistent checkpointing.
Create and orchestrate multi-agent clusters to complete complex tasks. Use this skill when users need to break down complex tasks into multiple specialized agents for parallel or serial execution. Applicable scenarios: (1) Complex projects requiring multi-role collaboration (planning, research, coding, writing, design, analysis, review) (2) Need to execute multiple independent sub-tasks in parallel to improve efficiency (3) Need professional division of labor to optimize cost and quality. Keywords: multi-agent, agent cluster, task orchestration, parallel execution, agent team.
Spawn Agentica multi-agent patterns
Coordinates skills, frameworks, and workflows throughout the project lifecycle using pattern-based sequencing, goal decomposition, phase-gate validation, and multi-agent orchestration. Use when starting multi-phase projects, sequencing frameworks, decomposing goals into capability plans, validating phase-gate readiness, coordinating subagents, or designing MCP-based tool orchestration.