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Found 91 Skills
Interactive agent picker for composing and dispatching parallel teams
Use when planning or executing multi-wave parallel work on any project. Covers the execution framework, task registry, write-scope ownership, handoff rules, merge gates, and how to split safe parallel subagent work without collisions.
Use when acting as Grug - talks to user, writes short caveman specs into beads, reviews Grunk work for complexity and obvious mistakes.
Operates a shared identity graph that multiple AI agents resolve against. Ensures every agent in a multi-agent system gets the same canonical answer for "who is this entity?" - deterministically, even under concurrent writes.
Expert in Oh My Codex (OMX) - workflow layer for OpenAI Codex CLI with agents, skills, and team coordination
AI Agent Orchestration Dashboard for managing AI agents, tasks, and multi-agent collaboration via OpenClaw Gateway
Run a second round on a contested question by circulating each subagent's independent proposal to the other authors and asking for structured pros and cons, then synthesize. Use this skill whenever you have multiple independent proposals or opinions on a contested decision — architecture tradeoffs, code review disagreements, design choices, competing root-cause theories — and want sharper analysis than you'd produce by synthesizing alone. Pairs naturally with the council and research skills; reach for it liberally whenever proposals diverge.
Use beads (bd) for persistent task tracking in coding projects. A git-backed issue tracker designed for AI agents with dependency graphs, hierarchical tasks, and multi-agent coordination.
Guide for working in parallel with other agents. Use when another agent is already working in the same directory, or when you need to work on multiple features simultaneously. Covers git worktrees as the recommended approach.
BF 워크플로우의 사람-시스템 경계 허브. orchestrate를 모드별로 스폰하고, 에픽 단위 루프를 돌며 사람과 소통하는 유일한 경계이다.
Full lifecycle orchestrator - spec/impl/test. Spawn-wait-close pipeline with inline discuss subagent, shared explore cache, fast-advance, and consensus severity routing.
Use when one agent is implementing code and another agent must review the resulting changes, compare the summary against the actual files, decide whether to fix now or move on, and write the next tightly scoped prompt with context handoff guidance.