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Create and manage Netlify deploys — Git continuous deployment, CLI manual/anonymous deploys, Deploy to Netlify buttons, drag-and-drop, and per-context netlify.toml build settings. Use when linking a repo, deploying from the CLI, setting up Deploy Previews or branch deploys, configuring deploy contexts, adding skew protection, fixing a failed or secrets-flagged deploy, or wiring build hooks and Deploy to Netlify buttons.

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。

Microsoft docs lookup, code samples, and SDK reference for Azure, .NET, Microsoft 365, Windows, and Power Platform via Microsoft Learn MCP. Use for API reference or official MS documentation retrieval.

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。

NVIDIA NeMo Retriever deployment and usage guidance for local retrieval services, corpus ingestion, and grounded question-answering 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。

Picks the right Netlify protection layer for a deployed site and disambiguates the three unrelated things people call "auth". Use when a developer wants to password-protect a site or previews, restrict a project to their team, make a project public/private, set team visibility defaults, require SSO to view a site, or debug SSO-session symptoms like being logged out mid-session / getting 401s on an SSO-protected site / token expiry or refresh. Routes app-user login ("who is this user in my app") to the netlify-identity skill and dashboard/team SSO SSO elsewhere; this skill only chooses the perimeter layer for site/preview access.

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。

Draft, prepare, publish, and verify personal or project LinkedIn posts through the user's signed-in Chrome session, including audience review, public-safe media uploads, links, action-time confirmation, and post-publication checks.

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 asks how to build with OpenAI products or APIs, asks about Codex itself or choosing Codex surfaces, needs up-to-date official documentation with citations, help choosing the latest model for a use case, latest/current/default-model prompting guidance, or model upgrade and prompt-upgrade guidance; use OpenAI docs MCP tools for non-Codex docs questions, use the Codex manual helper first for broad Codex self-knowledge, and restrict fallback browsing to official OpenAI domains.

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 this skill alongside figma-use when the task involves translating an application page, view, or multi-section layout into Figma. Triggers: 'write to Figma', 'create in Figma from code', 'push page to Figma', 'take this app/page and build it in Figma', 'create a screen', 'build a landing page in Figma', 'update the Figma screen to match code', 'convert this modal/dialog/drawer/panel to Figma'. This is the preferred workflow skill whenever the user wants to build or update a full page, modal, dialog, drawer, sidebar, panel, or any composed multi-section view in Figma from code or a description. Discovers design system components, variables, and styles from Code Connect files, existing screens, and library search, then imports them and assembles views incrementally section-by-section using design system tokens instead of hardcoded values.

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。

Design and implement context-fit frontend interfaces with deliberate art direction, accessible interaction, responsive behavior, complete states, and rendered verification. Use when creating or substantially reworking pages, components, product workspaces, dashboards, marketing sites, editorial surfaces, commerce flows, or justified immersive experiences.

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。

Pick the right serving container for a SageMaker model deployment and find its current image URI. Use this skill whenever about to deploy a model to a SageMaker endpoint and an image URI needs to be chosen — including when the user says "deploy this LLM", "host this HuggingFace model", "serve this fine-tuned model", "deploy this embedding model", "host a reranker", "serve a sentence-transformers model", or when about to hardcode any container URI in deployment code. HuggingFace-curated Deep Learning Containers are ALWAYS preferred: HuggingFace vLLM (LLMs and generative rerankers), HuggingFace vLLM-Omni (multimodal), TEI (embeddings/cross-encoder rerankers), HF Inference Toolkit (other transformers). Generic images (AWS vLLM, DJL-LMI, SGLang) are used only when no HuggingFace image is compatible — never merely because they carry a newer version. Never hardcode a container URI from memory and never default to TGI. Prevents stale-image failures and wrong-region URIs.

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。

SwiftUI ↔ Figma translation. Use whenever the user mentions Swift, SwiftUI, iOS, iPhone, or iPad — in EITHER direction — translating a Figma design into SwiftUI (design → code), or pushing SwiftUI views / screens / tokens back into a Figma file (code → design). Triggers on phrases like 'implement this Figma design in SwiftUI', 'build this screen in Swift', 'push this SwiftUI view to Figma', 'mirror my Swift code in a Figma file', or whenever a Figma URL appears alongside `.swift` files / an `.xcodeproj`. Routes to a direction-specific reference doc; loads alongside `figma-use` for the code → design path.

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。

Automate doc generation with JSDoc/TSDoc, linters, and pre-commit hooks. Use when setting up markdownlint, configuring doc linting pipelines, integrating JSDoc/TSDoc, or building automated documentation 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。

Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Covers polished document output, tracked changes, comments, image updates, XML-level repairs, and safe conversion 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。

NVIDIA DeepStream SDK development guidance for Python pyservicemaker pipelines, video analytics, TensorRT integration, and streaming inference 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。

Git operations, shell scripting, CI/CD pipelines, and terminal automation. Use for conventional commits, PowerShell/Bash scripting, configuring GitHub Actions, or automating development tooling 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。

Evaluate and improve AI-generated output with explicit rubrics, reflection loops, and stop conditions. Use when building self-critique workflows, evaluator-optimizer pipelines, or acceptance gates for code, docs, analysis, or plans.

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。

Ensure .NET/C# code follows maintainable, modern best practices. Use when reviewing or improving C# code, solution structure, async patterns, dependency injection, or testability.

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 en revue de code (PR reviews, patterns, anti-patterns, security, performance, readability)

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 en ClickHouse (columnar OLAP, MergeTree, materialized views, real-time analytics)

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。

Architecte Agent IA — Conçoit et déploie des agents IA (Hermes, Claude Code, n8n, NVIDIA NIM). Expert en architecture multi-agents, orchestration, et intégration de workflows IA.

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。

Business & Monétisation IA — Expert en monétisation d'agents IA, vente de workflows, pricing DZD, acquisition clients algériens. Stratégie freelance → consultant → agence.

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 en Airtable (bases, views, automations, scripts, interfaces, extensions)

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 en Airtable avancé (bases, views, automations, scripts, integrations, 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。

Expert en ASO (keywords, screenshots, reviews, A/B testing, featured)

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。

AI Workflow Automation IA — Expert en automatisation de workflows IA (n8n AI nodes, LangChain, Dify, Flowise, pipelines custom)

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。