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Zero-shot image classification and image-text 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。

Extract text from PDFs/scans (pymupdf, marker-pdf).

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。

Humanize text: strip AI-isms and add real voice.

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。

Edit text in existing PDFs via natural-language prompts.

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。

OpenAI(api_key='your-api-key') model = OpenAIEmbeddingsModel(model='text-embedding-3-small', openai_

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。

Navigating Sparse Evidence: Agentic Visual RAG via Explicit Context Selection and Consolidation Soochow University ; Baidu Inc.

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Sep 24, 2025 Deep Dive into Context Engineering for Agents Sep 18, 2025 Architectures for Multi-Agen

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Session stores conversation history for a specific session, allowing agents to maintain context without requiring explicit manual memory management.

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 the user references past work or you suspect cross-session context exists.

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。

They re context management, tool design, policy gates, memory strategies and, if you want to run loc

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。

Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use this skill when designing clean architecture for a new microservice, when refactoring a monolith to use bounded contexts, when implementing hexagonal or onion architecture patterns, or when debugging dependency cycles between application layers.

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。

Create detailed implementation plans with bite-sized tasks for engineers with zero codebase context

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 Transformers.js to run state-of-the-art machine learning models directly in JavaScript/TypeScript. Supports NLP (text classification, translation, summarization), computer vision (image classification, object detection), audio (speech recognition, audio classification), and multimodal tasks. Works in browsers and server-side runtimes (Node.js, Bun, Deno) with WebGPU/WASM using pre-trained models from Hugging Face Hub.

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Extract clean Markdown or text from one or more known URLs through Tavily. Use when the user supplies specific pages and needs their content, including query-focused chunks or JavaScript-rendered pages.

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。

Serena MCP for project memory and code navigation. Use when managing Serena memories, navigating symbols, performing intelligent refactoring, or maintaining context/continuity across AI agent sessions.

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。

Transform rough UI requests into structured Stitch prompts with platform, layout, component, and design-system context.

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。

React 19+ with TypeScript — hooks, custom hooks, state management (useState/useReducer/useContext), React Query/SWR, Tailwind CSS, performance. Use when building React components, apps, or optimizing renders.

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Deploy and configure web frameworks on Netlify — build settings and SSR/edge adapters plus local platform emulation and env vars. Use when setting up or fixing a framework deploy (Next.js / Astro / Nuxt / SvelteKit / Remix / React Router / TanStack Start / SolidStart / Gatsby / Angular / Vite / Express / Hydrogen / Hugo / Eleventy / Vue / React), adding SSR or edge functions or middleware wired to Netlify context, fixing SPA redirect and catch-all rules, setting a build command or publish directory, or debugging "why isn't my env var updating" and framework build failures.

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Generate read-only MongoDB queries (find) or aggregation pipelines using natural language, with collection schema context and sample documents. Use this skill whenever the user asks to write, create, or generate MongoDB queries, wants to filter/query/aggregate data in MongoDB, asks "how do I query...", needs help with query syntax, or discusses finding/filtering/grouping MongoDB documents. Also use for translating SQL-like requests to MongoDB syntax. Does NOT handle Atlas Search ($search operator), vector/semantic search ($vectorSearch operator), fuzzy matching, autocomplete indexes, or relevance scoring - use search-and-ai for those. Does NOT analyze or optimize existing queries - use mongodb-query-optimizer for that. Does NOT handle aggregation pipelines that involve write operations. Requires MongoDB MCP server.

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Write, configure, and deploy Netlify serverless functions in TypeScript, JavaScript, or Go. Use this when adding an API endpoint or backend route, adding a contact form handler, wiring auth or Identity signup/login hooks, building streaming or AI-proxy responses, scheduling cron jobs, running long background jobs (batch processing/scraping), reacting to deploy or form events, setting up rate limiting or region/memory config, or reading environment variables and secrets inside a function. Covers file locations, the Request/Context/Response handler shape, path routing, config options, and local testing with netlify dev.

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Recognize when disagreements reveal valuable context, preserve multiple valid approaches instead of forcing premature resolution

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PowerPoint (.pptx) manipulation via MCP server. Use for creating slides, formatting presentations, managing placeholders, adding images, applying templates, or extracting text from .pptx files.

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Use OpenAI, Anthropic, Google Gemini, or OpenRouter models from Netlify Functions or Edge Functions without managing provider API keys or accounts — the gateway injects credentials automatically. Reach for this when you add an AI chatbot or completion endpoint, generate images or text with Gemini/GPT/Claude, summarize form submissions with AI, build an LLM-backed API route, stream a long AI generation, or wire up any server-side AI provider call on Netlify. Covers provider SDK setup, injected env vars, model availability, rate limits, credit costs, streaming for long generations, and local dev with netlify dev or the Vite plugin.

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Build, deploy, and secure Model Context Protocol (MCP) servers on Netlify. Use whenever the task involves creating an MCP server, exposing an app or API to AI agents as MCP tools, letting Claude / Cursor / Claude Code call a custom remote server, or adding MCP tools to an existing Netlify site. Covers the MCP SDK + Streamable HTTP transport on a Netlify Function, authentication (single shared secret vs per-user API keys with Netlify Identity), read/write safety, file uploads, and connecting clients. Use even when the user just says "MCP", "tool server for an agent", or "let an AI use my API".

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。