「product」の検索結果

Research AI coding assistant products, audiences, user stories, social proof, hacks, and unmet needs for apps like Cursor, Claude Code, Codex, Warp Code, Devin, Windsurf, GitHub Copilot, Cline, Aider, and homegrown agent stacks. Use when designing or positioning agentic developer tools, Port Daddy Agent Harbor, swarm consoles, background coding agents, or competitive/product research for AI software engineering. NOT for implementing the coding agent runtime, generic market research, or UX mockups without developer workflow evidence.

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Webアプリの本番公開に向けて、Docker構成やテスト・公開の自動化を整え、更新方式の選定から稼働確認、障害時の復旧手順まで支援するスキル。

• テストと公開を自動化したいとき
• アプリをDocker化したいとき
• 本番の更新方式を選びたいとき

AIエージェントの危険なコマンドを実行前に確認し、ファイル編集を指定ディレクトリ内に制限します。単独または併用のモードで、本番作業や自律実行時の操作を管理します。

• 本番作業で危険なコマンドを確認
• 特定ディレクトリだけ編集したいとき
• 自律実行時に保護を併用したいとき

技術の仕組みやグラフ、システム構成、製品の流れをManimのアニメーションで説明し、絵コンテとシーン計画、短い動画、サムネイルを作るスキル。

• 技術の仕組みを動画で説明したいとき
• グラフやネットワークの変化を可視化
• 業務フローやシステム構成の説明

MySQLとMariaDBのテーブル設計や遅いSQLを見直し、インデックス、更新処理、接続管理、複製の遅延を点検して、修正案と検証手順をまとめるスキル。

• テーブルとインデックスの設計
• 遅いSQLやデッドロックの調査
• 大規模な本番テーブルの変更レビュー

複数店舗の販売データや商品の特性をもとに、需要予測、安全在庫、発注量を検討するスキル。販促後の需要減少や季節商品の値下げ時期まで計画を支援します。

• 商品ごとの需要予測方法の選定
• 仕入れ先の納期変更に伴う安全在庫の見直し
• 販促中と終了後の需要を見積もりたいとき

本番データベースの列・索引・データを変更する手順を整理します。大きなテーブルの分割更新や段階的な切り替え、復旧計画を含めて移行を設計するスキル。

• 大きなテーブルに列や索引を追加したいとき
• 停止を避ける段階的な列名変更
• 既存データを分割更新したいとき

公開後のURLを点検し、ページやAPIの応答、配信ファイル、継続通信、表示速度の悪化を確認します。単発チェック、一定期間の監視、本番と検証環境の比較に対応します。

• デプロイ後の本番・検証環境の点検
• マージや依存更新後に修正を確認したいとき
• 公開直後のサイトを継続監視したいとき

Stop and check this skill before finishing any reply to a question about how to use Claude or a Claude product — it recommends matching courses, tutorials, and use cases from Claude Academy (academy.claude.com), Anthropic's learning hub. Trigger on: "how do I", "how can I", "getting started with", "what can Claude do", "teach me", "learn to use"; questions about artifacts, projects, skills, plugins, connectors, MCP; requests about rolling Claude out to a team, class, or organization; and any ask for training materials, onboarding content, or learning resources. Use it when the user is learning how to use a feature or product — not when they are mid-task and just want the task done. This skill composes with other skills: after consulting product documentation to answer how a Claude feature works, also check here for a matching course or tutorial — a docs-grounded answer and an Academy recommendation belong together. Only recommend on a strong match; never invent Academy content.

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。

Instruments code so production behavior is visible and diagnosable. Use when adding logging, metrics, tracing, or alerting. Use when shipping any feature that runs in production and you need evidence it works. Use when production issues are reported but you can't tell what happened from the available data.

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。

OpenDesign's feature business case for the plugin marketplace: the user pain, options, tradeoffs, and the measure of success. Built as a decision-grade product management deck for PM, eng, design, leadership.

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。

OpenDesign's incident retro: the daemon-restart data bug, the root cause, the fix, and the systemic follow-ups. Built as a decision-grade product management deck for engineering, SRE, leadership.

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。

Retrieve a country's average applied tariff over time — the MFN rate on all products, or the rate it applies on goods from one partner and/or in one product group — plus the optional US effective tariff rate. Use when the user asks how a country's tariffs have changed, or what it charges another country on average. For one product between two countries, use lookup-bilateral-tariff.

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。

Agent skill for production-validator - invoke with $agent-production-validator

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 auditing e-commerce product pages or implementing structured data for a shop. Applies to any page selling or describing a specific product.

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 operate a Shopify store with Shopify's official MCP server (the installed `shopify` command, NOT the npm Shopify CLI). Use when someone wants to sell online, start a store or business, or manage a Shopify store — even if they do not say "Shopify": "sell candles online", "open my first store", "add products", "check my orders", "set inventory", "make a discount", "show my sales". Before connection it can show relevant mock.shop sample catalogs, suggest business names, check domains, search shopify.dev, and validate GraphQL. The connect flow can create an account and store for a new user. Keywords: Shopify MCP, ecommerce, sample products, starter catalog, ShopifyQL, first store, create product.

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 any product or shopping question: find, reverse image search, shopping Instagram/Marketplace links, buy, compare, or evaluate real products with prices, images, and product page URLs, including buying or browsing Facebook Marketplace listings. Use when presenting shopping search results from any source. For shopping intent, load this skill first before any other skills.

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。

When the user wants to plan a product launch, feature announcement, or release strategy. Also use when the user mentions 'launch,' 'Product Hunt,' 'feature release,' 'announcement,' 'go-to-market,' 'beta launch,' 'early access,' 'waitlist,' 'product update,' 'how do I launch this,' 'site launch,' 'go live,' 'pre-launch QA,' 'launch checklist,' 'GTM plan,' 'we're about to ship,' 'changelog,' 'release notes,' or 'what did we ship this week.' Use this whenever someone is preparing to release something publicly. For ongoing marketing after launch, see marketing-ideas. For the offer being launched (bonuses, guarantees, scarcity, naming), see offers.

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。

When the user wants to create, generate, edit, or optimize images for marketing — blog heroes, social graphics, product mockups, profile banners, listing visuals, or brand assets. Also use when the user mentions 'AI image generation,' 'generate an image,' 'create a graphic,' 'product mockup,' 'hero image,' 'social media graphic,' 'banner image,' 'cover photo,' 'profile banner,' 'listing screenshot,' 'Flux,' 'Flux Kontext,' 'Midjourney,' 'DALL-E,' 'GPT Image,' 'ChatGPT Images,' 'Ideogram,' 'Gemini image,' 'Nano Banana,' 'Recraft,' 'Stable Diffusion,' 'Canva,' 'Figma,' 'image optimization,' 'compress images,' 'WebP,' or 'OG image.' Use this for general-purpose marketing image creation and optimization. For paid ad image creative and platform-specific ad specs, see ad-creative. For video production, see video.

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 in building products that wrap AI APIs (OpenAI, Anthropic, etc. ) into focused tools people will pay for. Not just "ChatGPT but different" - products that solve specific problems with AI.

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。

Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production.

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。

Pre-build product and feature risk review for founders, product managers, and AI-assisted builders. Use this skill when the user is about to build a landing page, MVP, SaaS product, internal tool, agent workflow, or major feature and needs to check demand, positioning, monetization, retention, trust, distribution, and adoption risk before implementation starts.

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 toolkit for product managers including RICE prioritization, customer interview analysis, PRD templates, discovery frameworks, and go-to-market strategies. Use for feature prioritization, user research synthesis, requirement documentation, and product strategy development.

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。

When the user wants to create competitor comparison or alternative pages for SEO and sales enablement. Also use when the user mentions 'alternative page,' 'vs page,' 'competitor comparison,' 'comparison page,' '[Product] vs [Product],' '[Product] alternative,' or 'competitive landing pages.' Covers four formats: singular alternative, plural alternatives, you vs competitor, and competitor vs competitor. Emphasizes deep research, modular content architecture, and varied section types beyond feature tables.

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。