「applications」の検索結果

Production-ready patterns for building LLM applications, inspired by [Dify](https://github.com/langgenius/dify) and industry best practices.

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Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern.

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Master comprehensive evaluation strategies for LLM applications, from automated metrics to human evaluation and A/B testing.

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MongoDB, Redis, Cassandra, DynamoDB, and distributed database patterns for scalable applications

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To test local web applications, write native Python Playwright scripts.

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Expert in vector databases, embedding strategies, and semantic search implementation. Masters Pinecone, Weaviate, Qdrant, Milvus, and pgvector for RAG applications, recommendation systems, and similar

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Comprehensive design guide for web and mobile applications. Use when designing new UI components or pages, choosing color palettes and typography, or reviewing code for UX issues.

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Expert in building Retrieval-Augmented Generation systems. Masters embedding models, vector databases, chunking strategies, and retrieval optimization for LLM applications.

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Comprehensive performance optimization guide for React and Next.js applications, maintained by Vercel. Use when writing new React components or Next.js pages, implementing data fetching (client or server-side), or reviewing code for performance issues.

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Use when building React components, optimizing Next.js performance, implementing accessibility, or reviewing frontend code quality for modern web applications.

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You are an AI assistant development expert specializing in creating intelligent conversational interfaces, chatbots, and AI-powered applications. Design comprehensive AI assistant solutions with natur

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Master Go concurrency with goroutines, channels, sync primitives, and context. Use when building concurrent Go applications, implementing worker pools, or debugging race conditions.

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Build efficient, scalable monorepos that enable code sharing, consistent tooling, and atomic changes across multiple packages and applications.

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Production-ready patterns for building LLM applications, inspired by [Dify](https://github.com/langgenius/dify) and industry best practices.

日本語の概要は準備中です。原文の説明を表示しています。

Production-ready GitHub Actions workflow patterns for testing, building, and deploying applications.

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Build CarPlay-enabled apps using the CarPlay framework. Use when creating navigation, audio, communication, EV charging, parking, or food ordering apps for the car display, working with CPTemplateApplicationScene, CPListTemplate, CPMapTemplate, CPNowPlayingTemplate, configuring CarPlay entitlements, or integrating with CarPlay Simulator for testing.

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Build or improve a job seeker's resume.md source file from conversational career input. Use when the user wants to create resume.md, organize new-grad or experienced career history, convert raw experiences into STAR/CAR evidence, add missing metrics, or prepare reusable career evidence for cover letters and job applications. 한국어 요청도 포함합니다 - 이력서 작성, 이력서 정리, 경력기술서, 경력 정리, 커리어 정리, 자소서 소재 정리, 내 경험 정리해줘, 신입 이력서, 경력직 이력서.

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Create distinctive, production-grade frontend interfaces with high design quality. Generates creative, polished code that avoids generic AI aesthetics. Use when the user asks to build web components, pages, artifacts, posters, or applications, or when any design skill requires project context.

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Project scaffolding templates for new applications. Use when creating new projects from scratch. Contains 12 templates for various tech stacks.

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This skill should be used when the user asks to "test for XSS vulnerabilities", "perform cross-site scripting attacks", "identify HTML injection flaws", "exploit client-side injection vulnerabilities", "steal cookies via XSS", or "bypass content security policies". It provides comprehensive techniques for detecting, exploiting, and understanding XSS and HTML injection attack vectors in web applications.

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Expert in building voice AI applications - from real-time voice agents to voice-enabled apps. Covers OpenAI Realtime API, Vapi for voice agents, Deepgram for transcription, ElevenLabs for synthesis, LiveKit for real-time infrastructure, and WebRTC fundamentals. Knows how to build low-latency, production-ready voice experiences. Use when: voice ai, voice agent, speech to text, text to speech, realtime voice.

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Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.

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Expert in designing effective prompts for LLM-powered applications. Masters prompt structure, context management, output formatting, and prompt evaluation. Use when: prompt engineering, system prompt, few-shot, chain of thought, prompt design.

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Expert in building Retrieval-Augmented Generation systems. Masters embedding models, vector databases, chunking strategies, and retrieval optimization for LLM applications. Use when: building RAG, vector search, embeddings, semantic search, document retrieval.

日本語の概要は準備中です。原文の説明を表示しています。