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Found 92 Skills
Build and maintain assistant-ui based React chat apps with reliable setup, runtime selection, LangGraph wiring, tool UI integration, and upgrade workflows. Use when tasks explicitly involve `assistant-ui` dependencies or APIs, including `assistant-ui` CLI commands (`create/init/add/update/upgrade/codemod`), `@assistant-ui/*` providers/runtimes, `AssistantRuntimeProvider`, Thread/Composer primitives, cloud persistence, or tool rendering behavior. Do not use for generic React chat work, backend-only LangGraph tasks, or non-assistant-ui UI work. If the prompt explicitly says without/no/not assistant-ui, do not trigger this skill.
LangGraph workflow patterns including basic graphs, conditional routing, parallel execution, and subgraphs. Use when designing graph structure or workflow flow.
AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.
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.
Build a conversational AI assistant with memory and state. Use when you need a customer support chatbot, helpdesk bot, onboarding assistant, sales qualification bot, FAQ assistant, or any multi-turn conversational AI. Powered by DSPy for response quality and LangGraph for conversation state management.
Detects orphaned code (files/functions that exist but are never imported or called in production), preventing "created but not integrated" failures. Use before marking features complete, before moving ADRs to completed, during code reviews, or as part of quality gates. Triggers on "detect orphaned code", "find dead code", "check for unused modules", "verify integration", or proactively before completion. Works with Python modules, functions, classes, and LangGraph nodes. Catches the ADR-013 failure pattern where code exists and tests pass but is never integrated.
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.
Build multiple AI agents that work together. Use when you need a supervisor agent that delegates to specialists, agent handoff, parallel research agents, support escalation (L1 to L2), content pipeline (writer + editor + fact-checker), or any multi-agent system. Powered by DSPy for optimizable agents and LangGraph for orchestration.
Implementation guide for 17+ agentic AI architectures using LangChain and LangGraph for building sophisticated AI agents
AI agent with retrieval tool for document Q&A using RAG and LangGraph.
Comprehensive Python engineering guidelines for writing production-quality Python code. This skill should be used when writing Python code, performing Python code reviews, working with Python tools (uv, ruff, mypy, pytest), or answering questions about Python best practices and patterns. Applies to CLI tools, AI agents (langgraph), and general Python development.
INVOKE FIRST for any LangChain / LangGraph / Deep Agents agent building project before consulting other skills or writing any agent code. Required starting point for up to date info on framework selection (LangChain vs LangGraph vs Deep Agents vs hybrid composition), agent patterns, install, environment setup, and which skill to load next.