518 件 ・ 関連度順
概要と使いどころ
Designing ETL/ELT pipelines, visualizing data flows, selecting batch/streaming approaches, and architecting Kafka/Airflow/dbt systems. Use when building data pipelines or managing data quality.
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。
Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
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。
Remix v2 performance, streaming, caching, and server/client boundaries. Use when configuring HTTP caching, server-only modules, hydration safety, or prefetch. Triggers on headers export, Cache-Control, PrefetchPageLinks, Link prefetch, .server.ts, .client.ts, useHydrated, ClientOnly, window.ENV, links preload, useId.
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。
Guides architectural decisions for LangGraph applications. Use when deciding between LangGraph vs alternatives, choosing state management strategies, designing multi-agent systems, or selecting persistence and streaming approaches.
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。
Configure LLM providers, use fallback models, handle streaming, and manage model settings in PydanticAI. Use when selecting models, implementing resilience, or optimizing API calls.
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。
Skill for developing REST API endpoints in internal/server/. Covers routing, request validation, WebSocket streaming, and API conventions.
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。
Expert guide for Ultra-Low Latency Conversational Voice AI (<300ms), WebRTC bidirectional streaming, OpenAI Realtime API, Gemini Multimodal Live Audio, LiveKit Agents, and Semantic VAD / Panduan ahli AI suara percakapan real-time berlatensi ultra-rendah.
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。
Expert guide for Next.js 15 App Router: RSC, Server Actions, Middleware, Parallel/Intercepting Routes, Streaming, and Caching strategies / Panduan ahli untuk Next.js 15 App Router.
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。
Audio/video studio production — multi-track editing, color grading, motion graphics, compositing, live streaming, screen recording, YouTube publishing.
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。
FFmpeg media processing — video/audio conversion, trimming, encoding, filters, streaming. CLI and ffmpeg.wasm patterns.
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。
Integrate MDMA into an application and build features with it — wire up parsing, the runtime store, React rendering, LLM streaming, custom components, prompts, and CI validation. Use this skill when the user asks to add MDMA to an app, build a chat that streams MDMA, author or maintain a custom prompt, validate MDMA documents, register a custom component, or expose MDMA to an agent via MCP. Generates focused, correct wiring that uses the right packages for the job instead of reinventing them.
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。
Intercept and debug Claude Code API requests using mitmproxy. Inspect system prompts, tool definitions, token usage, and streaming responses. Triggers: cc-trace, mitmproxy, API interception, Claude Code debugging, traffic inspection.
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。
Reviews LLM integration, prompt templates, model selection, token/cost budgets, evaluation harnesses, structured outputs, retries, and streaming. Checks trust boundaries and task evidence against the selected provider/model contract rather than prescribing universal model tiers or sampling settings.
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。
Apple FoundationModels framework for on-device LLM — text generation, guided generation with @Generable, tool calling, and snapshot streaming in iOS 26+.
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。
Persist AI chat conversations to Neon Postgres with full support for AI SDK message parts including tools, reasoning, and streaming. Uses UUID v7 for chronologically-sortable IDs.
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。
Comprehensive AI/ML development guide for LangChain, LangGraph, and ML model integration in FastAPI. Use when building LLM applications, agents, RAG systems, sentiment analysis, aspect-based analysis, chain orchestration, prompt engineering, vector stores, embeddings, or integrating ML models with FastAPI endpoints. Covers LangChain patterns, LangGraph state machines, model deployment, API integration, streaming, error handling, and 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。
Live real-time dashboard for monitoring AI agent swarms with smart completion detection, clickable agent detail views, idle time tracking, and activity streaming. Auto-launches a beautiful web UI with capybara-inspired colors.
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 stateful AI agents using the Cloudflare Agents SDK. Load when creating agents with persistent state, scheduling, RPC, MCP servers, email handling, or streaming chat. Covers Agent class, AIChatAgent, state management, and Code Mode for reduced token usage.
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。
Batteries-included agent component for React/Next.js from ui.inference.sh. One component with runtime, tools, streaming, approvals, and widgets built in. Capabilities: drop-in agent, human-in-the-loop, client-side tools, form filling. Use for: building AI chat interfaces, agentic UIs, SaaS copilots, assistants. Triggers: agent component, agent ui, chat agent, shadcn agent, react agent," agentic ui, ai assistant ui, copilot ui, inference ui, human in the loop
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。
Central authority for Claude Agent SDK (TypeScript and Python SDKs). Covers SDK installation, authentication (Anthropic key, Bedrock, Vertex), sessions and resumption, forking sessions, streaming vs single mode, custom tools, permissions (allowedTools, disallowedTools, permissionMode), MCP integration, system prompts (CLAUDE.md, appendSystemPrompt, outputStyle), cost tracking, todo tracking, structured outputs, hosting patterns, plugins, and SDK branding guidelines. Assists with building custom agents, configuring SDK options, and troubleshooting SDK issues. Delegates 100% to docs-management skill for official documentation.
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 conversational AI agents using Vercel AI SDK + OpenRouter. Use when creating Next.js frontends with streaming UI, tool calling, and multi-provider support.
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。
LLM 集成全流程。覆盖 OpenAI / Anthropic / Google / 开源模型接入、Prompt 工程、 Function Calling、Agent 编排、Token 优化、安全防护、生产化部署。 触发关键词：LLM、GPT、Claude、Gemini、Prompt、Function Calling、Tool Use、 Agent、Chain、Structured Output、Streaming、Token、Rate Limit。
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。
Search and read locally-stored Claude documentation covering Claude Code CLI, Claude API (Messages, tool use, vision, streaming, batch), Agent SDK (Python and TypeScript), prompt engineering, and all Anthropic platform docs. Use this skill whenever the user asks about Claude Code features (hooks, MCP servers, skills, plugins, settings, permissions, keybindings, sub-agents), the Anthropic API or any of its SDKs (Python, TypeScript, Go, Java), the Agent SDK (sessions, hooks, custom tools, MCP), model capabilities (context windows, extended thinking, pricing, rate limits, vision), prompt engineering best practices, or troubleshooting any Claude-related error. This skill provides instant access to official documentation files without web searches — always prefer it over web lookups for Claude and Anthropic topics.
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。
Executes Ansible playbooks for server diagnostics and remediation using ansible-runner Python SDK. Supports inventory parsing, vault-encrypted credentials, and real-time task output streaming.
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。