Browse 138,453 skills across 70 categories. Mirrored from majiayu000/claude-skill-registry.
Install and configure LangChain SDK/CLI authentication. Use when setting up a new LangChain integration, configuring API...
使用 LangChain 中的聊天模型集成指南，包括 OpenAI、Anthropic、Google、Azure 和 Bedrock
使用 LangChain 中的文档加载器集成指南，用于处理 PDF、网页、文本文件和 API
使用 LangChain 中的嵌入模型集成指南，包括 OpenAI、Azure 和本地嵌入
使用 LangChain 中的文本分割器集成指南，包括递归、字符和语义分割器
LangChain 工具集成使用指南，包括预构建工具包、Tavily、Wikipedia 和自定义工具
LangChain 向量存储集成使用指南，包括 Chroma、Pinecone、FAISS 和内存向量存储
Builds LLM-powered applications with LangChain.js for chat, agents, and RAG. Use when creating AI applications with chai...
Configure LangChain local development workflow with hot reload and testing. Use when setting up development environment,...
INVOKE THIS SKILL when you need human-in-the-loop approval, custom middleware, or structured output. Covers HumanInTheLo...
Initialize and use LangChain chat models - includes provider selection (OpenAI, Anthropic, Google), model configuration,...
Work with multimodal inputs/outputs in LangChain - includes images, audio, video, content blocks, and vision capabilitie...
Set up comprehensive observability for LangChain integrations. Use when implementing monitoring, setting up dashboards,...
Comprehensive guide for building production-grade LLM applications using LangChain's chains, agents, memory systems, RAG...
LangChain is a framework for building applications powered by LLMs. It helps manage the complexity of prompt chaining, m...
Execute LangChain production deployment checklist. Use when preparing for production launch, validating deployment readi...
INVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system. Covers document loaders, RecursiveChara...
Build Retrieval Augmented Generation (RAG) systems with LangChain - includes embeddings, vector stores, retrievers, docu...
LangChain ReAct agent implementation with tool binding for reasoning and action loops
Document Q&A with RAG using Supabase pgvector store.
AI agent with retrieval tool for document Q&A using RAG and LangGraph.
Apply production-ready LangChain SDK patterns for chains, agents, and memory. Use when implementing LangChain integratio...
Stream outputs from LangChain agents and models - includes stream modes, token streaming, progress updates, and real-tim...
使用 Zod 模式、类型安全响应和自动验证从 LangChain 代理和模型获取结构化的验证输出
聊天模型如何调用工具 - 包括 bindTools、工具选择策略、并行工具调用和工具消息处理
LangChain framework utilities for chains, agents, and RAG
在 LangChain 中定义和使用工具 - 包括工具装饰器、自定义工具、内置工具和工具模式
LangChain tool creation and integration utilities for agent systems
Provides patterns to build declarative AI Services with LangChain4j for LLM integration, chatbot development, AI agent i...
Build declarative AI Services with LangChain4j using interface-based patterns, annotations, memory management, tools int...
Provides LangChain4j patterns for implementing MCP (Model Context Protocol) servers, creating Java AI tools, exposing to...
Model Context Protocol (MCP) server implementation patterns with LangChain4j. Use when building MCP servers to extend AI...
Implement Retrieval-Augmented Generation (RAG) systems with LangChain4j. Build document ingestion pipelines, embedding s...
Provides Retrieval-Augmented Generation (RAG) implementation patterns with LangChain4j for Java. Generates document inge...
Provides integration patterns for LangChain4j with Spring Boot. Configures AI model beans, sets up chat memory with Spri...
Integration patterns for LangChain4j with Spring Boot. Auto-configuration, dependency injection, and Spring ecosystem in...
Testing strategies for LangChain4j-powered applications. Mock LLM responses, test retrieval chains, and validate AI work...
Provides unit test, integration test, and mock AI patterns for LangChain4j applications. Creates mock LLM responses, tes...
Provides and generates LangChain4j tool and function calling patterns: annotates methods as tools with @Tool, configures...
Tool and function calling patterns with LangChain4j. Define tools, handle function calls, and integrate with LLM agents....
Provides configuration patterns for LangChain4J vector stores in RAG applications. Use when building semantic search, in...
Configure LangChain4J vector stores for RAG applications. Use when building semantic search, integrating vector database...
LangChain.js - TypeScript framework for building LLM-powered applications with agents, chains, RAG, tools, memory, and i...
Complete guide for building agents and workflows in LangConfig. Use when users need help configuring nodes, connecting a...
Layer 5: SDE-Based Learning Analysis via Langevin Dynamics
A powerful Python-based visual framework for building and deploying AI-powered agents and workflows with Model Context P...
Comprehensive assistance with langflow
Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets...
Debug AI traces, find exceptions, analyze sessions, and manage prompts via Langfuse MCP. Use when debugging AI pipelines...
Precisely filter and query Langfuse traces/observations using advanced filter operators for debugging and optimization w...
Monitor and optimize LLM costs using Langfuse analytics and dashboards. Use when tracking LLM spending, identifying cost...
Automates Langfuse Cloud dashboard interactions using Playwright MCP. Captures screenshots for documentation, extracts m...
Collect Langfuse debug evidence for support tickets and troubleshooting. Use when encountering persistent issues, prepar...
Extracts traces, observations, and metrics from Langfuse Cloud (EU) API for debugging, telemetry analysis, and regulator...
Analyzes user feedback from Langfuse annotation queues and generates surgical recommendations for template.yaml, style.y...
Create a minimal working Langfuse trace example. Use when starting a new Langfuse integration, testing your setup, or le...
Install and configure Langfuse SDK authentication for LLM observability. Use when setting up a new Langfuse integration,...
Replaces Phoenix observability with Langfuse Cloud (EU) traceability for pharmaceutical test generation. Adds @observe d...
LLM observability platform for tracing, evaluation, prompt management, and cost tracking. Use when setting up Langfuse,...
LLM observability with Langfuse — query traces, generations, costs, metrics, and debug LLM pipelines via the REST API
LLM observability with self-hosted Langfuse 3.x - tracing, evaluation, monitoring, prompt management, and cost tracking
Set up comprehensive observability for Langfuse with metrics, dashboards, and alerts. Use when implementing monitoring f...
Analyzes writing-ecosystem traces to fix style.yaml, template.yaml, and tools.yaml based on quality issues found in prod...
MANDATORY skill when KeyError or schema errors occur. Fetch actual prompt schemas instead of guessing. Use for debugging...
Comprehensive prompt iteration workflow for debugging and improving Langfuse prompts. Analyzes codebase usage, sets up r...
Implement Langfuse rate limiting, batching, and backoff patterns. Use when handling rate limit errors, optimizing trace...
Langfuse SDK best practices, patterns, and idiomatic usage. Use when learning Langfuse SDK patterns, implementing proper...
Integrate Langfuse observability with AWS Strands Agents for comprehensive tracing, monitoring, and debugging of AI agen...
Configure Langfuse webhooks and event callbacks for real-time notifications. Use when setting up trace notifications, co...
Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph co...
LangGraph skill for building stateful agent graphs, subgraphs, checkpoints, conditional flows, parallel execution, strea...
Expert in LangGraph, the production-grade framework for building stateful, multi-actor AI applications. Use when buildin...