Loading...
Loading...
Found 69 Skills
INVOKE THIS SKILL when setting up a new project or when asked about package versions, installation, or dependency management for LangChain, LangGraph, LangSmith, or Deep Agents. Covers required packages, minimum versions, environment requirements, versioning best practices, and common community tool packages for both Python and TypeScript.
Implementation guide for 17+ agentic AI architectures using LangChain and LangGraph for building sophisticated AI agents
Scaffold a minimal local LangGraph agent in Python by following the official quickstart. Use when the user wants to quickly build or try a LangGraph agent locally.
Build AI agents for real-time financial options analysis with LangGraph, ChromaDB RAG, and Polygon.io data
Scaffold a minimal local LangGraph agent in TypeScript by following the official quickstart. Use when the user wants to quickly build or try a LangGraph agent locally.
Guides architectural decisions for LangGraph applications. Use when deciding between LangGraph vs alternatives, choosing state management strategies, designing multi-agent systems, or selecting persistence and streaming approaches.
Use when a developer wants to create a new agent project or get started with AgentCore. Handles framework selection, project scaffolding, first deploy, and first invocation. Triggers on: "build an agent", "create an agent", "get started", "new project", "agentcore create", "which framework", "Strands vs LangGraph", "hello world agent", "first agent", "create MCP server", "host MCP server", "agentcore dev", "dev server", "what port", "local development". Not for adding capabilities to existing projects — use agents-build or agents-connect. Strands vs LangGraph in a migration context routes to agents-build, not here. Connecting to an existing MCP server routes to agents-connect, not here.
Integrate PICA into a LangChain/LangGraph Python application via MCP. Use when adding PICA tools to a LangChain agent, setting up PICA MCP with LangChain, or when the user mentions PICA with LangChain or LangGraph.
AI 개발/활용 도구 생태계(LangChain, LangGraph, CrewAI, 코딩 에이전트 등)를 비교하고 목적에 맞게 선택하는 모듈.
Build AI copilots, chatbots, and agentic UIs in React and Next.js using CopilotKit. Use this skill when the user wants to add an AI assistant, copilot, chat interface, AI-powered textarea, or agentic UI to their app. Covers setup, hooks (useCopilotAction, useCopilotReadable, useCoAgent, useAgent), chat components (CopilotPopup, CopilotSidebar, CopilotChat), generative UI, human-in-the-loop, CoAgents with LangGraph, AG-UI protocol, MCP Apps, and Python SDK integration. Triggers on CopilotKit, copilotkit, useCopilotAction, useCopilotReadable, useCoAgent, useAgent, CopilotRuntime, CopilotChat, CopilotSidebar, CopilotPopup, CopilotTextarea, AG-UI, agentic frontend, in-app AI copilot, AI assistant React, chatbot React, useFrontendTool, useRenderToolCall, useDefaultTool, useCoAgentStateRender, useLangGraphInterrupt, useCopilotChat, useCopilotAdditionalInstructions, useCopilotChatSuggestions, useHumanInTheLoop, CopilotTask, copilot runtime, LangGraphAgent, BasicAgent, BuiltInAgent, CopilotKitRemoteEndpoint, A2UI, MCP Apps, AI textarea, AI form completion, add AI to React app.
Use when adding capabilities to an existing agent project — memory, app integration, VPC, multi-agent, migration, model changes, browser, code interpreter, or resource removal. Triggers on: "add memory", "remember across sessions", "call agent from app", "invoke agent from code", "auth to call agent", "streaming responses", "VPC", "VPC connectivity", "VPC error", "can't reach from VPC", "multi-agent", "A2A", "A2A auth", "orchestrator not delegating", "specialist not called", "migrate Bedrock Agent", "after import", "migration issue", "framework for migration", "change model", "browser tool", "code interpreter", "delete agent", "tear down", "agentcore remove", "cross-account memory", "resource-based policy on memory". Not for connecting to external APIs via Gateway — use agents-connect. Not for scaffolding a new project — use agents-get-started. Not for CLI/dev server errors — use agents-debug. Strands vs LangGraph in a migration context routes here.
Verifies that implemented code is actually integrated into the system and executes at runtime, preventing "done but not integrated" failures. Use when marking features complete, before moving ADRs to completed status, after implementing new modules/nodes/services, or when claiming "feature works". Triggers on "verify implementation", "is this integrated", "check if code is wired", "prove it runs", or before declaring work complete. Works with Python modules, LangGraph nodes, CLI commands, API endpoints, and service classes. Enforces Creation-Connection-Verification (CCV) principle.