2.2万 件 ・ 関連度順
概要と使いどころ
Build Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code interpreter, file search, web search), integrating MCP servers, managing conversation threads, or implementing streaming responses. Covers function tools, structured outputs, and multi-tool agents.
日本語の概要は準備中です。原文の説明を表示しています。
Initialize or improve AGENTS.md files that define how coding agents operate in a repo. Use when asked to set up or replace an agent init command (Codex, Claude), standardize multi-agent behavior, or audit an existing AGENTS.md for clarity, commands, boundaries, and repo-specific context. For Claude Code, also create CLAUDE.md as a symlink to AGENTS.md.
日本語の概要は準備中です。原文の説明を表示しています。
Guides agents and users to create standards-compliant agent definitions using templates in markdown frontmatter format, ensuring context gathering, clarity, and proper metadata. Forces agents to ask clarifying questions when context is insufficient. Token-efficient documentation required. All content must be in English. Trigger: When creating a new agent definition, setting up project agents, or documenting agent workflows.
日本語の概要は準備中です。原文の説明を表示しています。
Agent assistance skill that provides stuck detection, memory management, and session learning capabilities for AI agents Trigger terms: agent stuck, loop detected, session memory, agent learning, condense memory, stuck detection, agent memory, session learnings, extraction Use when: User reports agent is stuck, looping, or needs memory/learning management
日本語の概要は準備中です。原文の説明を表示しています。
Creates Claude Code agent files (.claude/agents/*.md) with YAML frontmatter, tool permissions, and system prompts. Use when building new agents, configuring agent frontmatter, writing agent system prompts, or setting agent tool permissions.
日本語の概要は準備中です。原文の説明を表示しています。
Generate a fully customized Amazon Connect AI agent PoC bundle (Lambda handlers, OpenAPI spec, AI agent prompt, Contact Flows, CloudFormation/CDK infrastructure, FAQ knowledge base) from a ~15-minute structured interview — or from a requirements doc, a flow sketch, or an existing flow/prompt you want to improve. Use when the user wants to build, scaffold, prototype, or refine an Amazon Connect contact center, an AI voice/chat agent on Amazon Connect, or any contact-center use case that mentions Connect, Lex, Wisdom, Q in Connect, "AI agent domain", or Agentic CX Designer (ACXD, Connect Customer, the Agentic CX block — the ACXD runtime target). Also triggers on "I have a requirements document", "turn this flow sketch into a Contact Flow", or "improve my existing Contact Flow / AI prompt". Produces 6 asset packages on local disk.
日本語の概要は準備中です。原文の説明を表示しています。
Generate a fully customized Amazon Connect AI agent PoC bundle (Lambda handlers, OpenAPI spec, AI agent prompt, Contact Flows, CloudFormation/CDK infrastructure, FAQ knowledge base) from a ~15-minute structured interview — or from a requirements doc, a flow sketch, or an existing flow/prompt you want to improve. Triggers on "amazon connect", "aicc", "contact center AI", "connect ai agent", "connect ai agents domain", "agentic cx designer", "acxd", "connect customer", "agentic cx block", "requirements document", "improve my contact flow", "flow sketch", "\uc544\ub9c8\uc874 \ucee4\ub125\ud2b8", "\ucee8\ud0dd\uc13c\ud130 AI \uc0c1\ub2f4\uc6d0".
日本語の概要は準備中です。原文の説明を表示しています。
How to use the coding agents installed on this machine (claude, codex, droid, grok, vktr, hermes, opencode, copilot, pi) as plain sub-agents in orchestrated workflows: one headless invocation, one prompt in, one result out. Deliberately ignores each CLI's own orchestration features (droid --mission, codex multi_agent, hermes delegation/moa/kanban, grok --agents, opencode personas). The orchestrator is whatever session is running the skill; the CLIs are interchangeable workers. Use when the user asks "which agent should run this", "fan out workers", "run X headless", or when a lifeos skill (overnight, timeboxed-iterating, workgraph, gauntlet, bughunt, dark-factory) needs to launch an agent CLI, or when a worker needs company context it should ask Viktor for (vktr).
日本語の概要は準備中です。原文の説明を表示しています。
Audit and fix agent readiness: the Lighthouse Agentic Browsing fraction, accessibility tree for agents, robots.txt and Content-Signal for AI agents, WAF treatment of agent traffic, llms.txt, Markdown delivery, ai-catalog.json, /.well-known discovery files, and WebMCP tools. Exclude AI citability and brand signals (seo-geo) and commerce protocol depth (seo-ecommerce).
日本語の概要は準備中です。原文の説明を表示しています。
Designs, deploys, and secures Google Cloud Agent Gateway solutions. Use when the user needs to configure multi-agent security, ingress (CLIENT_TO_AGENT), or egress (AGENT_TO_ANYWHERE) patterns involving Model Armor, IAP, and Agent Registry. Don't use for general Cloud Load Balancing or basic VPC setup not related to Agent Gateways.
日本語の概要は準備中です。原文の説明を表示しています。
Design Invocable Apex actions that return deterministic, agent-friendly errors instead of surfacing raw exceptions to the LLM. NOT for authoring the action itself — @InvocableMethod schema, labels, security context — use agentforce/custom-agent-actions-apex. NOT for the Apex tests that force each error branch — use agentforce/agent-action-unit-tests.
日本語の概要は準備中です。原文の説明を表示しています。
Give an AI agent its own real browser over MCP tool calls - launch, navigate, click, fill, screenshot, extract text, run JS - with a kernel-level real-device fingerprint and a persistent profile, so the session stays logged in between runs and pages see one coherent device instead of a headless build. No Playwright or SDK code to write. Use when an agent should operate a site itself, when a computer-use / browser-use setup needs a captured real fingerprint rather than a synthetic one, when agent sessions keep losing their login, or when comparing hosted agent-browser services. Also for 'MCP browser', 'browser MCP server', 'let my agent browse the web', 'agent browser control', 'browser-use MCP', 'computer use browser', 'Browserbase alternative', 'Steel browser alternative', 'headless browser detected'. Node (npx) or Python; Windows x64, macOS Intel + Apple Silicon, Linux x64 / arm64. SDK and REST reference is anti-detect-browser; account isolation is multi-account-isolation.
日本語の概要は準備中です。原文の説明を表示しています。
Guide for defining and using Claude subagents effectively. Use when (1) creating new subagent types, (2) learning how to delegate work to specialized subagents, (3) improving subagent delegation prompts, (4) understanding subagent orchestration patterns, or (5) debugging ineffective subagent usage.
日本語の概要は準備中です。原文の説明を表示しています。
Build GenAI and agentic apps with genai-tk (tclatos/genai-tk), a YAML-driven IoC toolkit over LangChain, DeepAgents, DeerFlow, and Prefect. Use this skill whenever the user mentions genai-tk, genai_tk, `cli init`, `cli agents run`, `LangchainAgent`, `create_harness`, `get_llm`, `global_config()`, `model_id@provider`, `agents:`/`agent_defaults:` profiles, `RetrieverFactory`, `cli workflow`, or BAML extraction. Also trigger for app_conf.yaml, GENAITK_PROFILE, CodeAct, OpenSandbox, decision models, or "the toolkit".
日本語の概要は準備中です。原文の説明を表示しています。
Plataforma autônoma de agentes de IA para construir e implantar agentes contínuos. Use ao criar agentes de workflow visual, implantar agentes autônomos persistentes ou construir sistemas complexos de automação de IA com múltiplas etapas.
日本語の概要は準備中です。原文の説明を表示しています。
Especialista em CrewAI - o principal framework multi-agente baseado em papéis utilizado por 60% das empresas da Fortune 500. Abrange design de agentes com papéis e objetivos, definição de tarefas, orquestração de crew, tipos de processo (sequencial, hierárquico, paralelo), sistemas de memória e flows para workflows complexos. Essencial para construir equipes colaborativas de agentes IA. Use quando: crewai, equipe multi-agente, papéis de agentes, crew de agentes, agentes baseados em papéis.
日本語の概要は準備中です。原文の説明を表示しています。
This skill should be used when the user asks to "design multi-agent system", "implement supervisor pattern", "create swarm architecture", "coordinate multiple agents", or mentions multi-agent patterns, context isolation, agent handoffs, sub-agents, or parallel agent execution.
日本語の概要は準備中です。原文の説明を表示しています。
Use when designing or auditing an agentic AI system holistically. Activates the six-component harness framework (ℛ Reasoning, ℳ Memory, 𝒞 Context, 𝒮 Skills, 𝒪 Orchestration, 𝒢 Governance) from arXiv:2605.26112. Trigger phrases: "design an agent system", "why is my agent unreliable", "harness architecture", "system-level agent design", "beyond model scaling", "agentic infrastructure", "scale my agent system", "agent performance bottleneck".
日本語の概要は準備中です。原文の説明を表示しています。
Generates a complete AGENTS.md at the repository root following the agents.md format: setup, build, test, style, and PR conventions coding agents need. Use when a repo has no AGENTS.md, when onboarding coding agents to a codebase, or when the existing agent instructions are stale.
日本語の概要は準備中です。原文の説明を表示しています。
运用《智能体设计模式》(Antonio Gulli) 的 21 个模式,指导 AI Agent 系统的架构设计与选型。适用于用户在设计 Agent 工作流(选择链式/路由/并行/多Agent编排)、提升 Agent 输出质量与可靠性(反思/异常处理/Guardrails)、做 RAG 技术选型(混合检索/GraphRAG/Agentic RAG)、优化 Agent 成本与延迟(动态模型切换/回退)时使用。
日本語の概要は準備中です。原文の説明を表示しています。
Build container-based Foundry Agents using Azure AI Projects SDK with ImageBasedHostedAgentDefinition. Use when creating hosted agents that run custom code in Azure AI Foundry with your own container images. Triggers: "ImageBasedHostedAgentDefinition", "hosted agent", "container agent", "Foundry ...
日本語の概要は準備中です。原文の説明を表示しています。
AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.
日本語の概要は準備中です。原文の説明を表示しています。
Creates VS Code custom agent files (.agent.md) for specialized AI personas with tools, instructions, and handoffs. Use when scaffolding new custom agents, configuring agent workflows, or setting up agent-to-agent handoffs.
日本語の概要は準備中です。原文の説明を表示しています。
Discover, validate, and invoke .agent.md custom agents. Use when finding agent files in the local Claude or VS Code Insiders directories, checking frontmatter, verifying disable-model-invocation, or determining agentName for runSubagent calls.
日本語の概要は準備中です。原文の説明を表示しています。