76 件 ・ 関連度順
概要と使いどころ
You are an expert in the Vercel AI SDK, the TypeScript toolkit for building AI-powered applications. You help developers integrate LLMs (OpenAI, Anthropic, Google, Mistral, Ollama) with React Server Components, streaming UI, tool calling, structured output with Zod schemas, RAG pipelines, multi-step agents, and edge-compatible AI features — the standard way to add AI to Next.js, Nuxt, SvelteKit, and any Node.js app.
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。
Run coding tasks via opencode using free cloud models. Use when asked to offload work to opencode.ai or run a free model. Don't use for local models (Ollama, LM Studio), Claude/OpenAI calls, or when Claude should do the work itself.
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。
Build GraphRAG retrieval pipelines on Neo4j using the neo4j-graphrag Python package (v1.22.0+). Covers retriever selection (VectorRetriever, HybridRetriever, VectorCypherRetriever, HybridCypherRetriever, Text2CypherRetriever, ToolsRetriever), external vector DB retrievers (Weaviate, Pinecone, Qdrant), retrieval_query Cypher fragments, query_params, filters, GraphRAG pipeline wiring (GraphRAG + LLM + prompt), all LLM providers (OpenAI, Anthropic, Gemini/VertexAI, Bedrock, Cohere, Mistral, Ollama), embedder setup, index creation, token usage tracking, Cypher 25 SEARCH clause, and LangChain/LlamaIndex integration. Does NOT handle KG construction — use neo4j-document-import-skill. Does NOT handle plain vector search — use neo4j-vector-index-skill. Does NOT handle GDS analytics — use neo4j-gds-skill. Does NOT handle agent memory — use neo4j-agent-memory-skill.
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。
Runs local and self-hosted LLMs with Ollama, LM Studio, MLX, llama.cpp, and Open WebUI. Use when choosing GGUF quants, sizing VRAM, or running models privately.
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。
AIChat is a comprehensive LLM command-line tool written in Rust that combines chat-REPL, shell command generation, RAG, AI tools, and multi-provider support into a single binary. It connects to 20+ LLM providers including OpenAI, Claude, Gemini, and Ollama.
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。
Desktop GUI automation via OpenInterpreter — mouse, keyboard, screenshot, and OCR control for native macOS/Linux applications. Three modes: Library (Claude reasons, OI executes), OS subprocess (full autonomous computer use), and Local agent (Ollama, offline). This skill should be used when interacting with desktop apps that have no CLI or API, automating GUI workflows, reading screen content via OCR, or controlling mouse/keyboard.
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。
Build and query fully local RAG knowledge bases from documents (PDF, MD, code, etc.) using RLAMA and Ollama — no cloud, no data leaving the machine. Triggers on 'local knowledge base', 'search documents', 'document Q&A', 'RAG query', 'ingest files', 'semantic search'.
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。
Run GGUF models directly, load LoRA adapters, benchmark inference speed, and serve models via llama-server using llama.cpp. Includes Qwen 3.5 serve scripts (9B dense + F16, 35B MoE) with asymmetric KV cache and thinking mode. Secondary to Ollama; use when needing direct model control or LoRA hot-loading. Triggers on 'llama.cpp', 'GGUF', 'LoRA adapter', 'benchmark inference', 'llama-server'.
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。
Analyze and tune a running llama.cpp server for local coding agents: propose config (ctx, prompt cache, MTP), benchmark before/after, report deltas. Use to optimize llama-server for Claude Code or Aider. Don't use for vLLM, ollama, or non-llama.cpp.
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。
Use when installing Anthropic's Claude Science on a geo-blocked machine (e.g. China) or running it without a Claude account. Downloads the binary from the unblocked downloads.claude.ai CDN, sets up the claude-science-api-bridge local proxy to route requests to ANY OpenAI- or Anthropic-compatible API (Volcengine, DeepSeek, Kimi, Zhipu, OpenAI, local Ollama/vLLM), and applies a no-login patch so no Claude Pro/Max subscription is required.
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。
FALLBACK ONLY — do not invoke unless you have already ruled out (1) a native API (Gmail API, GitHub API, Slack API …), (2) a CLI (git, gh, aws, npm, curl …), (3) direct file editing, and (4) existing browser automation (Playwright, Puppeteer). Only when all four are unavailable or have already failed should you use this skill. It gives AI agents a cursor and a keyboard on a real desktop — the last mile when the only remaining surface is a GUI. Concretely: use it when an earlier attempt via API, CLI, or direct file edit has failed and the user says things like "open X", "click Send", "type this in Word", "read what is on my screen", "do this in Outlook", "drive the Figma UI", "control my desktop", "automate this workflow", "fill out this form", or "copy text between apps". Works on Windows, macOS, and Linux with any LLM that can call functions (Claude, GPT, Gemini, Llama, Kimi, Ollama) over MCP — stdio for editor hosts (Claude Code, Cursor, Windsurf, Zed) or HTTP for daemons and dashboards.
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。
Set up and run local LLMs with Harbor. Use when the user wants to run models locally, install Harbor, start Open WebUI, llama.cpp, Ollama, vLLM, Docker Model Runner, MLX, or oMLX, pull GGUF or HuggingFace models, add SearXNG web search, Speaches TTS/STT, or Open Terminal code execution, launch Codex/Claude/Grok/OpenCode against a Harbor backend, or troubleshoot GPU, VRAM, and service startup.
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。
Build AI agents with Hugging Face's SmolAgents framework. Use when creating code-executing agents, tool-calling agents, multi-agent systems, agentic RAG, text-to-SQL pipelines, web browsing agents, or any multi-step AI workflows. Covers CodeAgent, ToolCallingAgent, custom tools, MCP integration, memory management, secure code execution (E2B, Docker, Blaxel), and model configuration (HF Inference, LiteLLM, Transformers, Ollama).
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。
Orquestación multimodelo y estrategia de cambio de modelos. Selección de modelos basada en puntuación, delegación entre agentes (Gemini, Codex, Ollama), emparejamiento con advisor, disparadores de escalado, matriz de permisos y optimización de eficiencia de costos.
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。
多模型编排与模型切换策略。基于评分的模型选择、跨 Agent 委派（Gemini、Codex、Ollama）、Advisor 配对、升级触发器、权限矩阵与成本效率优化。
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。
Многомодельная оркестрация и стратегия переключения моделей. Выбор моделей на основе оценки (score), делегирование между агентами (Gemini, Codex, Ollama), связывание с advisor, триггеры эскалации, матрица разрешений и оптимизация затрат.
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。
Use for local LLM fallback, failover, and Ollama health.
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。
Attack Success Rate (360 runs 60 payloads 2 models ~3 reps) Paradigm gemma4-e2b (local, Ollama
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。
Master local LLM inference, model selection, VRAM optimization, and local deployment using Ollama, llama.cpp, vLLM, and LM Studio. Expert in quantization formats (GGUF, EXL2) and local AI privacy.
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。
Master local LLM inference, model selection, VRAM optimization, and local deployment using Ollama, llama.cpp, vLLM, and LM Studio. Expert in quantization formats (GGUF, EXL2) and local AI privacy.
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。
Extract structured domain knowledge from AI models in-session or from local open-source models via Ollama. No API key needed.
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。
Install DSH on a fresh Mac. Runs sovereign-setup-mac.sh, renders .env from secrets backend, applies full sovereign lockdown, probes machine, and pulls right-sized Ollama models — one guided flow that leaves the node hardened and ready for Phase-2 spore.sh activation.
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。
Tell the user (or an agent) exactly what machine they are on — chip, cores, RAM, NPU TOPS, memory bandwidth, security posture, DSH tier, and the right Ollama model to pull. Refreshes the canonical profile at agents/core/.mesh/machine.json on every call. Reads the result via agents.core.machine — zero re-probing in application code.
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。
Extract structured domain knowledge from AI models in-session or from local open-source models via Ollama. No API key needed.
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。