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어떤 주제/과제든 받아서 스스로 팀을 구성하고 조사·분석·검토·결과도출까지 처리하는 범용 에이전트 팀 오케스트레이터. "팀으로 분석해줘", "에이전트 팀으로 조사해줘", "다각도로 검토해줘", "심층 분석 부탁해", "여러 관점으로 봐줘", "think-team", "think team" 키워드로 트리거. 단순 질문이 아닌 복합적 판단, 조사, 전략 결정이 필요한 모든 상황에서 사용.
Triggered automatically at the start of each new top-level conversation to establish the general principle of "seeking truth from facts", and select downstream skills for subsequent tasks only when clearly applicable. Skip this skill if you are a delegated sub-agent performing a single specific task. English: Trigger at the start of each new top-level conversation to establish the core methodology and select downstream skills only when clearly useful. Skip this skill when you are a delegated sub-agent handling a narrow, concrete task.
Refine, parallelize, and verify a draft task specification into a fully planned implementation-ready task
Systematically fix all failing tests after business logic changes or refactoring
Builds production AI/ML systems — model training, fine-tuning, MLOps pipelines, model serving, evaluation frameworks, RAG optimization, and agent orchestration at scale. Use when the user asks to build, train, or deploy ML models, set up MLOps pipelines, optimize RAG systems, create inference endpoints, or design production AI agents.
Spin up a single agent as an advisor — second opinion on the current task. Use when the user says "advisor", "second opinion", "what does X think", or wants an outside take without delegating the work itself.
What a knowledgeable local with great taste would tell you to walk to from here — fused across editorial, local-language, and crowd layers no single tool ranks together. Trigger phrases: `what should I walk to from here`, `near me with great taste`, `find the 3 places not the 40`, `kissaten near my hotel`, `viewpoint within walking distance`, `blue hour photo spot`, `use wanderlust-goat`, `run wanderlust-goat`.
使用 agency-agents-zh 中文 AI 智能体角色库，为 AI 编程工具提供 215 个即插即用的专家角色
Control Room template for managing Hermes agents from one VPS agent to specialist teams and orchestrated workflows
Design, test, and optimize prompts for LLM interactions. Cover prompt patterns (few-shot, chain-of-thought, ReAct), system prompt design, output formatting, prompt evaluation, and prompt optimization techniques. Triggers on "write prompt", "optimize prompt", "design system prompt", "few-shot examples", "chain of thought", "prompt evaluation", "LLM output formatting", "prompt testing", or "prompt patterns".
LangGraph parallel execution patterns. Use when implementing fan-out/fan-in workflows, map-reduce over tasks, or running independent agents concurrently.
Lead coordinator that orchestrates 5 news scraper agents in parallel to gather headlines from 15 top business news websites