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Found 422 Skills
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.
This skill should be run only when the user explicitly invokes it. Orchestrates end-to-end task implementation — understands the task, assesses complexity, implements directly or via a team of subagents for complex work, and always finishes with a code-polish pass.
BF 워크플로우의 사람-시스템 경계 허브. orchestrate를 모드별로 스폰하고, 에픽 단위 루프를 돌며 사람과 소통하는 유일한 경계이다.
Deploy and orchestrate Vertex AI ADK agents using A2A protocol. Manages AgentCard discovery, task submission, Code Execution Sandbox, and Memory Bank. Use when asked to "deploy ADK agent" or "orchestrate agents". Trigger with phrases like 'deploy', 'infrastructure', or 'CI/CD'.
(Industry standard: Sequential Agent / Agent as a Tool) Primary Use Case: Delegating a well-defined task to a worker agent, verifying its execution, and repeating if necessary. Inner/outer agent delegation pattern. Use when: work needs to be delegated from a strategic controller (Outer Loop) to a tactical executor (Inner Loop) via strategy packets, with verification and correction loops.
Recursive codebase analysis using the RLM paradigm. Use when: analyzing large codebases (100+ files), investigating cross-cutting patterns, recursive decomposition of complex code questions, scanning for issues across entire repos. Triggers: analyze this codebase, how does X work across the codebase, scan all files for Y, recursive analysis, RLM.
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.
Orchestrate multi-agent teams with defined roles, task lifecycles, handoff protocols, and review workflows. Use when: (1) Setting up a team of 2+ agents with different specializations, (2) Defining task routing and lifecycle (inbox → spec → build → review → done), (3) Creating handoff protocols between agents, (4) Establishing review and quality gates, (5) Managing async communication and artifact sharing between agents.
This skill should be used when the user asks to "implement a plan", "execute implementation", "build from plan", "implement feature", or needs to orchestrate execution of an implementation plan with specialized engineering agents.
Multi-agent orchestration patterns. Use when multiple independent tasks can run with different domain expertise or when comprehensive analysis requires multiple perspectives.
Professional prompt engineering, context engineering, and AI agent orchestration for coding agents (Claude Code, Codex, Cursor, Gemini CLI). Use when designing CLAUDE.md/AGENTS.md files, writing skills, planning multi-agent pipelines, optimizing token usage, managing session handoffs, or structuring any prompt for maximum agent performance. Do NOT use for general coding tasks or code review.
Run yourself in a loop with programmatic control via the Agent SDK. Use for long-running tasks like optimization, research, iterative improvement, multi-agent coordination, or any multi-step workflow where you need to repeat, branch, or track progress.