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Found 38 Skills
Полная русскоязычная справка по Ollama Web Search и Web Fetch API: поиск в интернете, получение контента страниц, Python/JS SDK, MCP-сервер, интеграция с OpenClaw. Используй этот скилл при любых вопросах об Ollama web search: как настроить API-ключ, выполнить поиск, получить содержимое страницы, подключить SDK, настроить MCP-сервер, интегрировать с агентами. Также используй при написании кода для Ollama Search: bash-скрипты, Python asyncio, JS/TS клиенты, tool-calling агенты, конфигурация OpenClaw. Триггерится на слова: ollama search, ollama web search, ollama_search, ollama fetch, web_search ollama, ollama api key, ollama MCP, поиск через ollama.
Local RAG system management with RLAMA. Create semantic knowledge bases from local documents (PDF, MD, code, etc.), query them using natural language, and manage document lifecycles. This skill should be used when building local knowledge bases, searching personal documents, or performing document Q&A. Runs 100% locally with Ollama - no cloud, no data leaving your machine.
Build production-ready AI workflows using Firebase Genkit. Use when creating flows, tool-calling agents, RAG pipelines, multi-agent systems, or deploying AI to Firebase/Cloud Run. Supports TypeScript, Go, and Python with Gemini, OpenAI, Anthropic, Ollama, and Vertex AI plugins.
Implement the Syncfusion React Inline AI Assist component. Use this skill to add inline AI suggestions, integrate AI services such as OpenAI, Gemini, Lite-LLM, or Ollama, configure command and response actions, customize toolbars, handle events, and support real-time prompt-response workflows in React.
Implement the Syncfusion Angular AI AssistView component. Use this skill when you need to create conversational AI interfaces, integrate AI services, add chat-like UI, or create intelligent assistant applications. Includes setup, configuration, event handling, AI integrations (OpenAI, Gemini, Ollama), speech features, and customization. Use this skill for all AI AssistView component implementation needs.
Eino component selection, configuration, and usage. Use when a user needs to choose or configure a ChatModel, Embedding, Retriever, Indexer, Tool, Document loader/parser/transformer, Prompt template, or Callback handler. Covers all component interfaces and their implementations in eino-ext including OpenAI, Claude, Gemini, Ollama, Milvus, Elasticsearch, Redis, MCP tools, and more.
This skill should be used when working with DSPy.rb, a Ruby framework for building type-safe, composable LLM applications. Use this when implementing predictable AI features, creating LLM signatures and modules, configuring language model providers (OpenAI, Anthropic, Gemini, Ollama), building agent systems with tools, optimizing prompts, or testing LLM-powered functionality in Ruby applications.
Route AI coding queries to local LLMs in air-gapped networks. Integrates Serena MCP for semantic code understanding. Use when working offline, with local models (Ollama, LM Studio, Jan, OpenWebUI), or in secure/closed environments. Triggers on local LLM, Ollama, LM Studio, Jan, air-gapped, offline AI, Serena, local inference, closed network, model routing, defense network, secure coding.
Guides technology selection and implementation of AI and ML features in .NET 8+ applications using ML.NET, Microsoft.Extensions.AI (MEAI), Microsoft Agent Framework (MAF), GitHub Copilot SDK, ONNX Runtime, and OllamaSharp. Covers the full spectrum from classic ML through modern LLM orchestration to local inference. Use when adding classification, regression, clustering, anomaly detection, recommendation, LLM integration (text generation, summarization, reasoning), RAG pipelines with vector search, agentic workflows with tool calling, Copilot extensions, or custom model inference via ONNX Runtime to a .NET project. DO NOT USE FOR projects targeting .NET Framework (requires .NET 8+), the task is pure data engineering or ETL with no ML/AI component, or the project needs a custom deep learning training loop (use Python with PyTorch/TensorFlow, then export to ONNX for .NET inference).
Use Claude Code's full tool system with any OpenAI-compatible LLM — GPT-4o, DeepSeek, Gemini, Ollama, and 200+ models via environment variable configuration.
LangGraph-based agent framework for consistent tool calling with automatic tool loops. Use when you need reliable multi-step task execution with OpenAI-compatible providers (Z.AI/GLM-5, OpenRouter, Groq, DeepSeek, Ollama).
CRITICAL - Guide for using Claudish CLI ONLY through sub-agents to run Claude Code with any AI model (OpenRouter, Gemini, OpenAI, local models). NEVER run Claudish directly in main context unless user explicitly requests it. Use when user mentions external AI models, Claudish, OpenRouter, Gemini, OpenAI, Ollama, or alternative models. Includes mandatory sub-agent delegation patterns, agent selection guide, file-based instructions, and strict rules to prevent context window pollution.