- Release NotesSkill for compiling and writing release notes for langchain-azure packages. Use when a new version of a package is being released and the README.md changelog section needs to be updated with a summary of merged PRs.langchain-ai/langchain-azure131
- Api DocsOpenAPI documentation and REST API design patternslangchain-ai/skills-benchmarks107
- Database MigrationsDatabase migration patterns and schema versioninglangchain-ai/skills-benchmarks107
- Deep Agents CoreINVOKE THIS SKILL when building ANY Deep Agents application. Covers create_deep_agent(), harness architecture, SKILL.md format, and configuration options.langchain-ai/skills-benchmarks107
- Deep Agents MemoryINVOKE THIS SKILL when your Deep Agent needs memory, persistence, or filesystem access. Covers StateBackend (ephemeral), StoreBackend (persistent), FilesystemMiddleware, and CompositeBackend for routing.langchain-ai/skills-benchmarks107
- Deep Agents OrchestrationINVOKE THIS SKILL when using subagents, task planning, or human approval in Deep Agents. Covers SubAgentMiddleware, TodoList for planning, and HITL interrupts.langchain-ai/skills-benchmarks107
- Docker PatternsBest practices for Docker containerization and multi-stage buildslangchain-ai/skills-benchmarks107
- Ecosystem PrimerINVOKE 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.langchain-ai/skills-benchmarks107
- Framework SelectionINVOKE THIS SKILL at the START of any LangChain/LangGraph/Deep Agents project, before writing any agent code. Determines which framework layer is right for the task: LangChain, LangGraph, Deep Agents, or a combination. Must be consulted before other agent skills.langchain-ai/skills-benchmarks107
- Langchain DependenciesINVOKE 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.langchain-ai/skills-benchmarks107
- Langchain FundamentalsCreate LangChain agents with create_agent, define tools, and use middleware for human-in-the-loop and error handling.langchain-ai/skills-benchmarks107
- Langchain MiddlewareINVOKE THIS SKILL when you need human-in-the-loop approval, custom middleware, or structured output. Covers HumanInTheLoopMiddleware for human approval of dangerous tool calls, creating custom middleware with hooks, Command resume patterns, and structured output with Pydantic/Zod.langchain-ai/skills-benchmarks107
- Langchain Oss PrimerALWAYS START HERE for any LangChain, Deep Agents, or LangGraph agent building project. Required starting point before choosing other skills or writing any code. Covers framework selection (LangChain vs LangGraph vs Deep Agents), agent archetypes, dependency setup, and which skills to load next based on your decisions.langchain-ai/skills-benchmarks107
- Langchain RagINVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system. Covers document loaders, RecursiveCharacterTextSplitter, embeddings (OpenAI), and vector stores (Chroma, FAISS, Pinecone).langchain-ai/skills-benchmarks107
- Langgraph FundamentalsINVOKE THIS SKILL when writing ANY LangGraph code. Covers StateGraph, state schemas, nodes, edges, Command, Send, invoke, streaming, and error handling.langchain-ai/skills-benchmarks107
- Langgraph Human In The LoopINVOKE THIS SKILL when implementing human-in-the-loop patterns, pausing for approval, or handling errors in LangGraph. Covers interrupt(), Command(resume=...), approval/validation workflows, and the 4-tier error handling strategy.langchain-ai/skills-benchmarks107
- Langgraph PersistenceINVOKE THIS SKILL when your LangGraph needs to persist state, remember conversations, travel through history, or configure subgraph checkpointer scoping. Covers checkpointers, thread_id, time travel, Store, and subgraph persistence modes.langchain-ai/skills-benchmarks107
- Langsmith DatasetINVOKE THIS SKILL when creating evaluation datasets, uploading datasets to LangSmith, or managing existing datasets. Covers dataset types (final_response, single_step, trajectory, RAG), CLI management commands, SDK-based creation, and example management. Uses the langsmith CLI tool.langchain-ai/skills-benchmarks107
- Langsmith EvaluatorINVOKE THIS SKILL when building evaluation pipelines for LangSmith. Covers three core components: (1) Creating Evaluators - LLM-as-Judge, custom code; (2) Defining Run Functions - how to capture outputs and trajectories from your agent; (3) Running Evaluations - locally with evaluate() or auto-run via LangSmith. Uses the langsmith CLI tool.langchain-ai/skills-benchmarks107
- Langsmith TraceINVOKE THIS SKILL when working with LangSmith tracing OR querying traces. Covers adding tracing to applications and querying/exporting trace data. Uses the langsmith CLI tool.langchain-ai/skills-benchmarks107
- React ComponentsModern React component patterns with hooks and TypeScriptlangchain-ai/skills-benchmarks107
- Testing PatternsUnit testing and integration testing best practiceslangchain-ai/skills-benchmarks107
- Linkedin PostWrite a LinkedIn post based on research findings or a given topic. Use this skill when asked to create LinkedIn content, professional posts, or thought leadership pieces.langchain-ai/langgraph-101-ts15
- Twitter PostWrite a Twitter/X post or thread based on research findings or a given topic. Use this skill when asked to create tweets, X posts, or social media threads.langchain-ai/langgraph-101-ts15
- Langsmith Code EvalCreates code-based evaluators for LangSmith-traced agents. Use when building custom evaluation logic, testing tool usage patterns, or scoring agent outputs programmatically. Triggers on requests to evaluate agents, create evaluators, or run experiments against LangSmith datasets.langchain-ai/lca-skills2
- Langsmith FetchFetches LangSmith traces for debugging agent behavior. Use when troubleshooting agent issues, reviewing conversation history, or investigating tool calls.langchain-ai/lca-skills2
- Linkedin PostWrite a LinkedIn post based on research findings or a given topic. Use this skill when asked to create LinkedIn content, professional posts, or thought leadership pieces.langchain-ai/modular-workshops2
- Twitter PostWrite a Twitter/X post or thread based on research findings or a given topic. Use this skill when asked to create tweets, X posts, or social media threads.langchain-ai/modular-workshops2
- Module 1Teaching instructions for Module 1 (LangGraph Deployment Architecture) — use when module_id is module-1langchain-ai/lca-deployment
- Module 1Teaching instructions for Module 1 (LangGraph Deployment Architecture) — use when module_id is module-1langchain-ai/lca-deployment
- Module 1Teaching instructions for Module 1 (LangGraph Deployment Architecture) — use when module_id is module-1langchain-ai/lca-deployment
- Module 1Teaching instructions for Module 1 (LangGraph Deployment Architecture) — use when module_id is module-1langchain-ai/lca-deployment
- Module 1Teaching instructions for Module 1 (LangGraph Deployment Architecture) — use when module_id is module-1langchain-ai/lca-deployment
- Module 2Teaching instructions for Module 2 (Using your deployment) — use when module_id is module-2langchain-ai/lca-deployment
- Module 2Teaching instructions for Module 2 (Using your deployment) — use when module_id is module-2langchain-ai/lca-deployment
- Module 2Teaching instructions for Module 2 (Using your deployment) — use when module_id is module-2langchain-ai/lca-deployment
- Module 2Teaching instructions for Module 2 (Using your deployment) — use when module_id is module-2langchain-ai/lca-deployment
- Module 3Teaching instructions for Module 3 (Dashboard) — use when module_id is module-3langchain-ai/lca-deployment
- Module 3Teaching instructions for Module 3 (Dashboard) — use when module_id is module-3langchain-ai/lca-deployment
- Module 3Teaching instructions for Module 3 (Dashboard) — use when module_id is module-3langchain-ai/lca-deployment
- Module 3Teaching instructions for Module 3 (Dashboard) — use when module_id is module-3langchain-ai/lca-deployment
- Module 4Teaching instructions for Module 4 (Storage) — use when module_id is module-4langchain-ai/lca-deployment
- Module 4Teaching instructions for Module 4 (Storage) — use when module_id is module-4langchain-ai/lca-deployment
- Module 4Teaching instructions for Module 4 (Storage) — use when module_id is module-4langchain-ai/lca-deployment
- Module 4Teaching instructions for Module 4 (Storage) — use when module_id is module-4langchain-ai/lca-deployment
- Module 5Teaching instructions for Module 5 (Authentication and Authorization) — use when module_id is module-5langchain-ai/lca-deployment
- Module 5Teaching instructions for Module 5 (Authentication and Authorization) — use when module_id is module-5langchain-ai/lca-deployment
- Module 5Teaching instructions for Module 5 (Authentication and Authorization) — use when module_id is module-5langchain-ai/lca-deployment
- Module 5Teaching instructions for Module 5 (Authentication and Authorization) — use when module_id is module-5langchain-ai/lca-deployment
- Module 6Teaching instructions for Module 6 (Deepagents CLI) — use when module_id is module-6langchain-ai/lca-deployment
- Module 6Teaching instructions for Module 6 (Deepagents CLI) — use when module_id is module-6langchain-ai/lca-deployment
- Module 6Teaching instructions for Module 6 (Deepagents CLI) — use when module_id is module-6langchain-ai/lca-deployment
- Module 6Teaching instructions for Module 6 (Deepagents CLI) — use when module_id is module-6langchain-ai/lca-deployment