6.7천건 · 관련도순
Autonomous Agents workflow skill. Use this skill when the user needs Autonomous agents are AI systems that can independently decompose and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
AI Agents Architect workflow skill. Use this skill when the user needs Expert in designing and building autonomous AI agents. Masters tool and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Azure AI Hosted Agents (Python) workflow skill. Use this skill when the user needs Build container-based Foundry Agents with Azure AI Projects SDK (ImageBasedHostedAgentDefinition). Use when creating hosted agents with custom container images in Azure AI Foundry and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Maintaining AGENTS.md workflow skill. Use this skill when the user needs This skill should be used when the user asks to "create AGENTS.md", "update AGENTS.md", "maintain agent docs", "set up CLAUDE.md", or needs to keep agent instructions concise. Enforces research-backed best practices for minimal, high-signal agent documentation and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
AI Agents Architect workflow skill. Use this skill when the user needs Expert in designing and building autonomous AI agents. Masters tool and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
DEPRECATED, renamed to orchestrating-chat-agents. Kept so existing imports of its scripts keep working; every module here loads the same module from orchestrating-chat-agents. Use orchestrating-chat-agents for parallel Claude calls over the API from claude.ai, and dispatching-subagents for fan-out in Claude Code.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Implements agents using Deep Agents. Use when building agents with create_deep_agent, configuring backends, defining subagents, adding middleware, or setting up human-in-the-loop workflows.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when modifying agentic contextual building blocks like skills (SKILL.md), slash commands, agents, hooks, plugins, marketplaces, and instruction files (CLAUDE.md, AGENTS.md, GEMINI.md, QWEN.md, Cursor, Copilot, Cline, or Kiro rules), tool configuration such as an OpenCode `opencode.json`, Muse Code hooks (`.muse/hooks.json`), a Grok Build `.grok/` project layer or a Google Antigravity customization root (`.agents/`, `.agent/`, `_agents/`, `_agent/` — hooks, MCP config, rules, registries and plugins), and committed project memory (`.agents/memory/`). Run skillsaw on the files you touched, apply autofixes, resolve remaining violations with `skillsaw explain` guidance, and re-lint until clean before considering the work complete.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Branch skill for building and improving agents. Use when creating new agents, adapting marketplace agents, validating agent structure, writing system prompts, or improving existing agents. Triggers: 'create agent', 'improve agent', 'validate agent', 'fix agent', 'agent frontmatter', 'system prompt', 'adapt agent', 'customize agent', 'agent examples', 'agent tools'.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
AIコーディングエージェント向けの指示書「AGENTS.md」を作成するスキル。プロジェクトにAIエージェントが作業するための文脈と指示を集約するファイルを作成したい場合に使用します。「AGENTS.mdを作成」「AIエージェント用の指示書を作る」「エージェント向けREADMEを作成」などのリクエストでトリガーします。OpenAI Codex、Claude Code、GitHub Copilot、Cursorなど、複数のAIエージェントで共通利用できるオープンな標準フォーマットです。
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Built by DynG AI for PlatformPilot.ai-style multi-agent systems. Use when designing or reasoning about message-passing agent coordination in ANY language: actor-style mailboxes, select, point-to-point routing, pub/sub, fan-in joins/quorums, ownership handoff, budgets, dead letters, and traces. Trigger words include PlatformPilot, DynG AI, actor model agents, message-passing agents, CSP agents, coordinate agents, multi-agent orchestration, agent runtime, fan-out workers, pub/sub agents, agent barrier, or join.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Deploy, run, list, or tear down the agents in this repo's .managed-agents/ folder on Anthropic Managed Agents. Use when the user says "deploy my agents", "ship this agent to the cloud", "run the deployed agent", or asks about managed-agent deployment.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Run a task iteratively over a user-specified duration by dispatching subagents. The orchestrator stays strictly linear and time-checked, but each iteration fans out MULTIPLE subagents in parallel over independent units (and those subagents may fan out further). Shared state — a compact progress digest and a growing environment cheatsheet — lives on disk and is passed to every subagent BY REFERENCE, killing the per-subagent rediscovery tax. Every subagent first reads an initialiser preamble that points it at that shared state and makes it write findings back, so the cheatsheet populates itself; role prompts are produced ONCE on the filesystem by a single scaffold command and dispatched by path, never re-typed per dispatch. Subagents persist their results to disk and return only a tiny status, so the orchestrator's context stays small and lasts. The orchestrator classifies the goal as FINITE or OPEN-ENDED: finite lists may finish early; open-ended goals use the full duration, never idle, never manufacture busywork. Use when the user gives a task and a duration and wants it ground out iteratively by subagents over that time.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use this skill to maintain an agent log in .agents/log, a decision journal shared by the developer and agents. Trigger when the user explicitly asks to use agent-log or record/update an agent log entry; when planning, implementing, or finalizing a significant feature in a repo with an existing .agents/log; or before non-trivial changes or questions in areas covered by existing entries. Never initialize .agents/log unless the user explicitly asks for an agent log.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design AgentSpeak(L)-style BDI agents with context-guarded plans, selection functions, and intention stacks. Use for interruptible autonomy, agent policy, and multi-agent orchestration in dynamic environments. NOT for simple rule engines, static planners, or centralized workflows.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build AI agents with LangChain v1 and LangGraph in Python. Use this skill whenever the user mentions LangChain, LangGraph, create_agent, init_chat_model, @tool, ToolRuntime, agent middleware, human-in-the-loop, structured output, MCP tools (langchain.mcp, MCPAdapter), RAG, multi-agent handoffs or subagents, checkpointers, Deep Agents (create_deep_agent) or Managed Deep Agents (mda, define_deep_agent). Also trigger for migrating from create_react_agent, LLMChain, AgentExecutor or langchain-mcp-adapters, stream_events, SummarizationMiddleware, and langchain-classic.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when building Hugging Face smolagents, code-executing agents, Python-action agents, Hub-shared tools, or lightweight agent prototypes that need sandboxing and provider flexibility.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Splits one big Claude task or automation into a set of focused AI Matrx agents that work on the person's own AI Matrx tables, then builds and test-runs each one. Use when the person says "split my task into agents", "turn my automation into AI Matrx agents", "make agents for my work", or after their data has moved into AI Matrx.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Agent-to-Agent (A2A) protocol implementation patterns for Google ADK - exposing agents via A2A, consuming external agents, multi-agent communication, and protocol configuration. Use when building multi-agent systems, implementing A2A protocol, exposing agents as services, consuming remote agents, configuring agent cards, or when user mentions A2A, agent-to-agent, multi-agent collaboration, remote agents, or agent orchestration.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
This skill should be used when the user asks about "parallel agents", "background tasks", "run_in_background", "non-blocking agents", "check agent progress", "TaskOutput", "retrieve agent results", or discusses running multiple agents concurrently. Covers patterns for launching agents in background, monitoring progress, and retrieving results.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
기술 문서와 에이전트·기여자용 지침 파일을 작성하고 검토합니다. 설명과 운영 절차, 다국어 버전의 일관성을 확인하고 근거가 충분한 문제를 수정합니다.
서로 독립적인 버그나 테스트 실패를 별도 에이전트에 맡겨 동시에 조사하고 수정합니다. 담당 범위를 정하고 결과 검토, 변경 충돌 확인, 전체 테스트와 통합까지 안내합니다.
한 세션에서 장기 목표를 향해 여러 하위 에이전트의 작업을 조율합니다. 사용자와 대화를 이어가면서 다음 작업에도 도움이 될 환경과 공통 규칙을 개선합니다.
AI 에이전트가 스킬과 규칙을 지키는지 세 단계의 지시 조건으로 검증합니다. 도구 호출 순서를 확인하고 시나리오별 준수율과 호출 시간선을 보고서로 정리합니다.