「questions」の検索結果

計画や設計を練り直したいときに、踏み込んだ質問を重ねるインタビューを行うスキル。考えを具体化するための対話を、関連スキルの呼び出しで始めます。

• 質問を通じて計画を練り直したいとき
• インタビューで設計を検討したいとき
• 対話で初期の案を具体化したいとき

一度の対話では収まらない大きな企画や変更を、決めるべき問いと依存関係に整理します。課題管理ツールに判断の記録を残し、実行に移るまでの道筋を明らかにするスキル。

• 複数の対話にまたがる大きな計画
• 未決事項と依存関係の整理
• 共同作業で判断の経緯を共有

ライブラリやフレームワークの設定方法、API仕様、コード例をContext7 MCPで調べ、取得した現行ドキュメントと指定バージョンに基づく回答を支援するスキル。

• フレームワークの導入・設定の確認
• ライブラリのAPIと使い方の調査
• Prismaのクエリ例を調べたいとき

サービスの健全性や遅延、処理量、リソース不足を把握するために、運用上の疑問から指標を選び、GrafanaやSigNoz向けの監視ダッシュボードを作ります。

• Kafkaの監視画面を作りたいとき
• Elasticsearchの状態や性能の監視
• API gatewayの遅延やエラーの監視

調査テーマを複数の問いに分け、ウェブ情報の検索と本文の読み込みを通じて、出典・確信度・情報不足を明記したレポートにまとめるスキル。

• 競合や市場動向を調べたいとき
• 導入前に技術を比較したいとき
• 市場規模や成長予測の調査

画像の内容を質問したり、説明文を作ったりするために、LLaVAの導入と利用を支援します。画像を見ながら続ける対話や、画像付き文書の理解にも使えるスキルです。

• 写真の説明文を作りたいとき
• 画像内の物や場面について質問したいとき
• 画像について話せるチャットの試作

システムの構成やデータの流れを、クリックして詳しく読める立体的なHTMLマップに整理します。同じデータから説明文も生成し、設計上の判断や未解決の質問を管理します。

• システム構成とデータの流れの説明
• 新しい設計をチームで検討したいとき
• レビュー中の未解決の質問の管理

A Frequently Asked Questions (FAQ) page with collapsible accordion sections, search functionality, and category filtering. Use when the brief asks for "FAQ", "help center", "questions", or "support page".

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。

Explain how this assistant works and help users understand computer access, confirmation or login blocks, and Slack errors. Use for capability questions and confusing product limitations; verify the actual state and give a supported next step. Also use for questions about their avatar or profile picture (their icon or the picture at the top) or the color of messages they send (message color, chat bubble color, or text bubble color).

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, write, or manage Meta ads and assets: ad copy, campaigns, spend, reports, audiences, catalogs, product feeds, feed refresh schedules, experiments, and policy. Always load for any request to create or write an ad, or to advertise a product or service, even when no platform is named; this includes sensitive or restricted categories. Always load for any question asking what a Meta, Facebook, or Instagram advertising policy means, allows, prohibits, or requires, including a standalone policy-definition question with no account context. Those questions must use ads_policy_tool, never browser search or memory. Load for a specifically named catalog or feed with an upload or refresh-schedule request; use Ads reads to resolve ownership before writing. Generic unnamed feeds need context. Whether an image, claim or piece of copy may be used in an ad is ALWAYS a Meta Ads task — 'can I use this in an ad', 'is it allowed', 'is this against policy', and any rights, likeness, celebrity, logo or trademark question about advertising with an image, including a follow-up about one just generated. Those are ads-policy questions, not general legal ones. An ad request uses the campaign workflow unless explicitly only an image or organic post.

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。

Fetch up-to-date documentation and code examples for any library, framework, SDK, CLI tool, or cloud service. Use whenever the user asks about a specific library — even well-known ones like React, Next.js, Prisma, Express, Tailwind, Django, or Spring Boot — because training data may not reflect recent API changes or version updates. Always use for: API syntax questions, configuration options, version migration issues, "how do I" questions mentioning a library name, debugging that involves library-specific behavior, setup instructions, and CLI tool usage. Use even when you think you know the answer. Do not rely on training data for API details, signatures, or configuration options — they are frequently out of date. Prefer this over web search for library 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。

Retrieves up-to-date documentation, API references, and code examples for any developer technology. Use this skill whenever the user asks about a specific library, framework, SDK, CLI tool, or cloud service — even for well-known ones like React, Next.js, Prisma, Express, Tailwind, Django, or Spring Boot. Your training data may not reflect recent API changes or version updates. Always use for: API syntax questions, configuration options, version migration issues, "how do I" questions mentioning a library name, debugging that involves library-specific behavior, setup instructions, and CLI tool usage. Use even when you think you know the answer — do not rely on training data for API details, signatures, or configuration options as they are frequently outdated. Always verify against current docs. Prefer this over web search for library documentation and API details.

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。

Prepare for due diligence meetings — management presentations, expert network calls, customer references, and advisor sessions. Generates targeted question lists, benchmarks to reference, and red flags to probe. Use before any diligence meeting or call. Triggers on "prep for management meeting", "diligence call prep", "expert call questions", "customer reference questions", or "meeting prep for [company]".

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。

Maps topics and keywords from user questions to QwenPaw official documentation paths and common source code entry points, reducing blind searching. Intended for the built-in QA Agent to quickly identify which files to read when answering questions about installation, configuration, skills, MCP, multi-agent, memory, CLI, etc.

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。

Generate STAR stories, practice questions, and talking points from a resume. Use when the user mentions interview prep, behavioral questions, STAR method, mock interview, or preparing for an upcoming interview.

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 structured interview plans with competency-based questions and scorecards. Trigger with "interview plan for", "interview questions for", "how should we interview", "scorecard for", or when the user is preparing to interview candidates.

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。

Generate or improve a company-specific data analysis skill by extracting tribal knowledge from analysts. BOOTSTRAP MODE - Triggers: "Create a data context skill", "Set up data analysis for our warehouse", "Help me create a skill for our database", "Generate a data skill for [company]" → Discovers schemas, asks key questions, generates initial skill with reference files ITERATION MODE - Triggers: "Add context about [domain]", "The skill needs more info about [topic]", "Update the data skill with [metrics/tables/terminology]", "Improve the [domain] reference" → Loads existing skill, asks targeted questions, appends/updates reference files Use when data analysts want Claude to understand their company's specific data warehouse, terminology, metrics definitions, and common query 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。

Authoring playbook for building agents that triage and reply to customer messages — support tickets, email inquiries, chat questions, refund requests, or product issues. Use this when the user wants an agent that handles inbound customer questions, drafts replies, escalates hard cases, summarizes tickets, or follows a support playbook.

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。

Produce a rigorous, sector-relative, multi-factor fundamental analysis of a publicly listed company — Indian (NSE/BSE) or US/global. Use when the user asks to analyse, research, evaluate, or value a stock, ticker, or listed company; asks whether a business is fundamentally strong, cheap, or expensive; compares companies or benchmarks one against its sector; or mentions OPM, ROCE, ROE, ROIC, P/E, EV/EBITDA, free cash flow, NIM, GNPA, CASA, promoter holding or pledging. Use it for accounting-quality and forensic questions — "is the profit real", "why is profit rising but cash isn't", auditor qualifications, related-party concerns — which route to the forensic-only mode, and for IPOs and not-yet-listed companies — "should I apply to this IPO", DRHP/RHP or S-1 questions, price band, grey market premium — which route to the IPO mode. Use it even when the request sounds casual ("is Infosys any good?"). Do not use it for personalised investment advice, portfolio allocation, or trading signals.

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 a structured customer interview script with JTBD probing questions, warm-up, core exploration, and wrap-up sections. Follows The Mom Test principles — no leading questions, no pitching, focus on past behavior. Use when preparing for user interviews, creating interview guides, or planning discovery research.

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 a focused N-question study session on a subject — MBE, essay, or flashcards. Tracks performance and updates the study plan. Use when the user says "run me 10 questions on [subject]", "do a session on [subject]", "let's do 5 cards on [subject]", or wants to drill a fixed number of questions and have the plan adapt.

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。

Amazon Alexa for Shopping Q&A automation: submits questions to Amazon's Alexa/Rufus AI shopping assistant and collects response text; supports optional keyword search context (navigate to search results page before asking for category-specific answers). Use when user mentions Amazon Alexa, Rufus, Amazon shopping assistant, Amazon AI chat, ask Amazon, Amazon Q&A, automate Alexa questions, Rufus chatbot, Amazon assistant automation, collect Alexa responses, bulk question submission to Amazon, keyword search context, category research. Also applies to extracting Amazon product recommendations from conversational AI, automating repeated queries to Amazon's AI shopping feature, collecting Alexa shopping responses at scale, or market research within a specific product category.

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。

Answer questions about the AI SDK and help build AI-powered features. Use when developers: (1) Ask about AI SDK functions like generateText, streamText, ToolLoopAgent, embed, or tools, (2) Want to build AI agents, chatbots, RAG systems, or text generation features, (3) Have questions about AI providers (OpenAI, Anthropic, Google, etc.), streaming, tool calling, structured output, or embeddings, (4) Use React hooks like useChat or useCompletion. Triggers on: "AI SDK", "Vercel AI SDK", "generateText", "streamText", "add AI to my app", "build an agent", "tool calling", "structured output", "useChat".

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 web animations that feel natural and purposeful. Use this skill proactively whenever the user asks questions about animations, motion, easing, timing, duration, springs, transitions, or animation performance. This includes questions about how to animate specific UI elements, which easing to use, animation best practices, or accessibility considerations for motion. Triggers on: easing, ease-out, ease-in, ease-in-out, cubic-bezier, bounce, spring physics, keyframes, transform, opacity, fade, slide, scale, hover effects, microinteractions, Framer Motion, React Spring, GSAP, CSS transitions, entrance/exit animations, page transitions, stagger, will-change, GPU acceleration, prefers-reduced-motion, modal/dropdown/tooltip/popover/drawer animations, gesture animations, drag interactions, button press feel, feels janky, make it smooth.

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。