framework-selection
by langchain-ai
Framework selection guide for LangChain, LangGraph, and Deep Agents layered architecture. Layered frameworks where LangChain provides foundation primitives, LangGraph adds orchestration and control flow, and Deep Agents adds planning, memory, file management, and skill delegation Decision table guides framework choice based on task complexity: LangChain for single-purpose agents, LangGraph for custom control flow and loops, Deep Agents for multi-step planning and persistent sessions Deep...
npx skills add https://github.com/langchain-ai/langchain-skills --skill framework-selectionMore skills from langchain-ai
deepagents-thread-inspector
langchain-ai
Inspect and explain conversations in the local Deep Agents Code SQLite session store. Use as a fallback when LangSmith trace tooling is unavailable, for…
deepagents-python-quickstart
langchain-ai
Scaffold a minimal local Deep Agent in Python by following the official quickstart, using provider-native web search instead of Tavily. Use when the user wants…
deepagents-typescript-quickstart
langchain-ai
Scaffold a minimal local Deep Agent in TypeScript by following the official quickstart, using provider-native web search instead of Tavily. Use when the user…
eval-engineering
langchain-ai
Iteratively inspect an agent repository and optional user-provided traces, interview the user, and create, run, and audit Harbor evals one at a time. Use for…
LangChain RAG Pipeline
langchain-ai
INVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system. Covers document loaders, RecursiveCharacterTextSplitter, embeddings (OpenAI),…
LangChain Structured Output & HITL
langchain-ai
langchain-structured-output-&-hitl — an installable skill for AI agents, published by langchain-ai/langchain-skills.
LangSmith Datasets
langchain-ai
INVOKE THIS SKILL when creating evaluation datasets from trace OR uploading datasets to LangSmith OR querying datasets. Covers dataset types (final_response,…
langsmith-evaluator
langchain-ai
INVOKE THIS SKILL when building evaluation pipelines for LangSmith. Covers three core components: (1) Creating Evaluators - LLM-as-Judge, custom code; (2)…