发现 documentation llm ai 相关 Skills，比较来源仓库和用途，查看适合你工作流的技能说明。
Agent-to-Agent (A2A) executor implementation patterns for task handling, execution management, and agent coordination. Use when building A2A executors, implementing task handlers, creating agent execution flows...
ElevenLabs Speech-to-Text transcription workflows with Scribe v1 supporting 99 languages, speaker diarization, and Vercel AI SDK integration. Use when implementing audio transcription, building STT features, in...
LlamaIndex implementation patterns with templates, scripts, and examples for building RAG applications. Use when implementing LlamaIndex, building RAG pipelines, creating vector indices, setting up query engine...
End-to-end testing scenarios for Supabase - complete workflow tests from project creation to AI features, validation scripts, and comprehensive test suites. Use when testing Supabase integrations, validating AI...
Provides three production-ready ML training examples (sentiment classification, text generation, RedAI trade classifier) with complete training scripts, deployment configs, and datasets. Use when user needs exa...
Embedding/vector caching for AI cost optimization
Generative UI implementation patterns for AI SDK RSC including server-side streaming components, dynamic UI generation, and client-server coordination. Use when implementing generative UI, building AI SDK RSC,...
Configure ADK bidi-streaming for real-time multimodal interactions. Use when building live voice/video agents, implementing real-time streaming, configuring LiveRequestQueue, setting up audio/video processing,...
Google Cloud Platform configuration templates for BigQuery ML and Vertex AI training with authentication setup, GPU/TPU configs, and cost estimation tools. Use when setting up GCP ML training, configuring BigQu...
Document chunking implementations and benchmarking tools for RAG pipelines including fixed-size, semantic, recursive, and sentence-based strategies. Use when implementing document processing, optimizing chunk s...
Search and retrieval strategies including semantic, hybrid, and reranking for RAG systems. Use when implementing retrieval mechanisms, optimizing search performance, comparing retrieval approaches, or when user...
Cost estimation scripts and tools for calculating GPU hours, training costs, and inference pricing across Modal, Lambda Labs, and RunPod platforms. Use when estimating ML training costs, comparing platform pric...
Validate and debug Vercel AI SDK provider configurations including API keys, environment setup, model compatibility, and rate limiting. Use when encountering provider errors, authentication failures, API key is...
Examples and patterns for integrating FastMCP Cloud servers with Claude Agent SDK using HTTP transport
RAG (Retrieval Augmented Generation) implementation patterns including document chunking, embedding generation, vector database integration, semantic search, and RAG pipelines. Use when building RAG systems, im...
Comprehensive observability setup patterns for Google ADK agents including logging configuration, Cloud Trace integration, BigQuery Agent Analytics, and third-party observability tools (AgentOps, Phoenix, Weave...
AI-powered content and image generation using content-image-generation MCP with Google Imagen 3/4, Veo 2/3, Claude Sonnet, and Gemini 2.0. Use when generating marketing content, creating hero images, building b...
Production-ready database schema patterns for AI applications including chat/conversation schemas, RAG document storage with pgvector, multi-tenant organization models, user management, and AI usage tracking. U...
Training monitoring dashboard setup with TensorBoard and Weights & Biases (WandB) including real-time metrics tracking, experiment comparison, hyperparameter visualization, and integration patterns. Use when se...
OpenRouter framework integration templates for Vercel AI SDK, LangChain, and OpenAI SDK. Use when integrating OpenRouter with frameworks, setting up AI providers, building chat applications, implementing stream...
Production-ready Celery task templates with error handling, retries, rate limiting, time limits, and custom task classes. Use when creating Celery tasks, implementing retry logic, adding rate limiting, setting...
SDK installation and setup patterns for Agent-to-Agent Protocol across Python, TypeScript, Java, C#, and Go. Use when implementing A2A protocol, setting up SDKs, configuring authentication, or when user mention...
Agent-to-Agent (A2A) server configuration patterns for HTTP, STDIO, SSE, and WebSocket transports. Use when building A2A servers, configuring MCP transports, setting up server endpoints, or when user mentions A...
Build production-ready Python CLI tools, utilities, and automation scripts with strict typing, performance optimization, and zero external dependencies (stdlib-only by default). Triggers on "Create a CLI tool f...
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。