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Found 251 Skills
Coordinator workflow for orchestrating dockeragents through fix-review-iterate-present loop. Use when delegating any task that produces code changes. Ensures agents achieve 10/10 quality before presenting to human.
This skill should be used when parallelizing multi-issue sprints using git worktrees and parallel Claude agents. Use when tackling multiple GitHub issues simultaneously, when the user mentions "blitz", "parallel sprint", "worktree workflow", or when handling 3+ independent issues that could be worked on concurrently. Orchestrates the full workflow from issue triage through parallel agent delegation to sequential merge.
Execute tasks from TODO file - Generic task runner [/todo-task-run xxx]
When the user wants to build GTM automation with code, design workflow architectures, use AI agents for GTM tasks, or implement the 'architecture over tools' principle. Also use when the user mentions 'GTM engineering,' 'GTM automation,' 'n8n,' 'Make,' 'Zapier,' 'workflow automation,' 'Clay API,' 'instruction stacks,' 'AI agents for GTM,' or 'revenue automation.' This skill covers technical GTM infrastructure from workflow design through agent orchestration.
Launch an intelligent sub-agent with automatic model selection based on task complexity, specialized agent matching, Zero-shot CoT reasoning, and mandatory self-critique verification
Autonomous multi-agent task orchestration with dependency analysis, parallel tmux/Codex execution, and self-healing heartbeat monitoring. Use for large projects with multiple issues/tasks that need coordinated parallel execution.
Multi-agent orchestration workflow for deep research: Split a research objective into parallel sub-objectives, run sub-processes using Claude Code non-interactive mode (`claude -p`); prioritize installed skills for network access 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 + summary of key conclusions/recommendations". Applicable scenarios: 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".
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"
Expert guidance for building the Arcanea creative agent ecosystem with attention to detail, design excellence, and systematic implementation.
Synthesizes research findings into design decisions via codebase investigation. Use when (1) translating research into implementation approaches, (2) selecting between design alternatives, (3) executing after /research or deep-research, or (4) preparing input for /plan phase.
Generate comprehensive documentation with intelligent orchestration and parallel execution
Guides subagent coordination through implementation workflows. Use when orchestrating multiple agents, managing workflow phases, or determining autonomous execution mode. Defines scale determination, document requirements, and stop points.