195 件 ・ 関連度順
概要と使いどころ
Scrape product reviews from G2, Capterra, and Trustpilot using Apify. Single script with platform dispatch. Use when you need to monitor competitor reviews, track product sentiment, or gather customer feedback from review sites.
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 Hacker News stories and comments using the free Algolia API. No Apify token needed. Use when you need to find HN discussions, track mentions, discover Show HN launches, or monitor tech community sentiment.
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。
Tokenize, tag, and analyze natural language text using Apple's NaturalLanguage framework and translate between languages with the Translation framework. Use when adding language identification, sentiment analysis, named entity recognition, part-of-speech tagging, text embeddings, or in-app translation to iOS/macOS/visionOS apps.
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。
Deep competitive intelligence for any market. Analyzes competitors' products, pricing, customer sentiment, GTM strategy, and growth signals using real web data. Produces battle cards, pricing landscape, and feature matrix. Use when the user wants to understand their competitive landscape, analyze competitors, compare products in a market, or research who they're competing against. Triggers for "who are my competitors", "competitive analysis", "competitor research", "battle cards", "pricing comparison", "competitor pricing", "market players", "competitive intelligence", "competitive landscape", "who else is in this space", "competitive moat", or any request to profile, compare, or map competitors in a category. Works standalone — no prior startup-design session needed.
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。
Brand monitoring tool for tracking mentions across social media platforms. Monitor Reddit, Google News, YouTube, and DuckDuckGo for brand mentions. Includes sentiment analysis, trend tracking, crisis detection, and competitor comparison. No API key required for basic monitoring.
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。
Social media campaign analysis and performance tracking that calculates engagement rates, ROI, and cross-platform benchmarks. Use for analyzing social performance, calculating engagement rate, or measuring campaign ROI.
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 conduct, analyze, or synthesize customer research. Use when the user mentions "customer research," "ICP research," "talk to customers," "analyze transcripts," "customer interviews," "survey analysis," "support ticket analysis," "voice of customer," "VOC," "build personas," "customer personas," "jobs to be done," "JTBD," "what do customers say," "what are customers struggling with," "Reddit mining," "G2 reviews," "review mining," "digital watering holes," "community research," "forum research," "competitor reviews," "customer sentiment," or "find out why customers churn/convert/buy." Use for both analyzing existing research assets AND gathering new research from online sources. For writing copy informed by research, see copywriting. For acting on research to improve pages, see cro.
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 reputation programs: reviews, sentiment, brand safety. Crisis → crisis-response; one review → review-response. "get more Google reviews"
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。
Orientação LGPD para operações de tratamento no Brasil. Cobre bases legais (Art. 7º e Art. 11), RIPD, incidentes (Arts. 48-49), direitos dos titulares (Art. 18) e transferências internacionais. Triggers: LGPD, RIPD, ANPD, proteção de dados, dados pessoais, consentimento, encarregado, DPO Brasil, incidente de dados, legítimo interesse.
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。
Daily morning research note for A-share markets. Summarizes overnight developments, pre-market sentiment, trade ideas, and key events for the trading day. Adapted from the original morning-note skill for Chinese market conventions. Triggers on "早报", "晨会纪要", "今日策略", "morning note", "morning meeting", or "daily A-share preview".
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 knowledge for Azure AI Language development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using CLU, custom/health NER, CQA, sentiment/PII APIs, or Language/TA/health containers, and other Azure AI Language related development tasks. Not for Azure AI Search (use azure-cognitive-search), Azure AI Document Intelligence (use azure-document-intelligence), Azure Speech in Foundry Tools (use azure-speech), Azure Translator (use azure-translator).
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。
Mention/keyword sweep on social platforms for [REPLACE: KEYWORDS] — trends, sentiment, top posts
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。
Dung khi can theo doi lien tuc nguoi ta noi gi ve thuong hieu, doi thu va nganh tren mang xa hoi — bo tu khoa giam sat, phan loai sac thai, bao cao tuan va thang, canh bao som, chi so brand health. Kich hoat khi user nhac 'social listening', 'theo doi thuong hieu', 'giam sat mang xa hoi', 'brand monitoring', 'khach dang noi gi ve minh', 'do sentiment', 'co ai nhac ten shop khong', 'canh bao som khung hoang'. Khong dung cho — khung hoang DA XAY RA va can xu ly ngay thi dung skill 66-crisis-playbook; mo xe chien luoc mot doi thu cu the thi dung skill 08-nghien-cuu-doi-thu; doc so lieu ads va web thi dung skill 13-phan-tich-du-lieu.
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 analyze Reddit content using semantic AI search via reddit-insights.com MCP server. Use when you need to: (1) Find user pain points and frustrations for product ideas, (2) Discover niche markets or underserved needs, (3) Research what people really think about products/topics, (4) Find content inspiration from real discussions, (5) Analyze sentiment and trends on Reddit, (6) Validate business ideas with real user feedback. Triggers: reddit search, find pain points, market research, user feedback, what do people think about, reddit trends, niche discovery, product validation.
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。
Research any topic across Reddit, X, and web from the last 30 days. Get current trends, real community sentiment, and actionable insights in 7 minutes vs 2 hours manual 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。
Aggregates transcript and frame data into an interactive web dashboard. Use for content, topic, or sentiment analysis.
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 cryptocurrency market research and analysis using specialized AI agents. Analyzes market data, price trends, news sentiment, technical indicators, macro correlations, and investment opportunities. Use when researching cryptocurrencies, analyzing crypto markets, evaluating digital assets, or investigating blockchain projects like Bitcoin, Ethereum, Solana, 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。
Get insider trading activity (SEC Form 4 filings) for one or more stocks. Use when user asks about insider buying/selling, executive transactions, insider sentiment, or Form 4 activity.
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 research customer pain points, complaints, or sentiment using review platforms like Trustpilot, G2, Capterra, or app stores. Also use when the user mentions "what are users saying", "competitor reviews", "pain points", or "voice of customer 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。
Use Databricks built-in AI Functions (ai_classify, ai_extract, ai_summarize, ai_mask, ai_translate, ai_fix_grammar, ai_gen, ai_analyze_sentiment, ai_similarity, ai_parse_document, ai_prep_search, ai_query, ai_forecast) to add AI capabilities directly to SQL and PySpark pipelines without managing model endpoints. Also covers document parsing and building custom RAG pipelines (parse → prep_search → index → query).
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。
Analyze Reddit threads for sentiment, consensus opinions, top arguments, and discussion patterns. Use this when users want to understand Reddit community opinions, analyze discussions, or gather insights from subreddit conversations.
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。
Analyze meeting transcripts to extract decisions, action items, blockers, sentiment, and generate follow-up emails. Use when user provides meeting notes, transcripts, or recordings and needs structured summaries or action tracking.
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。
Aggregate and analyze customer reviews from G2, Capterra, Trustpilot, App Store, and other platforms. Performs sentiment analysis, identifies pain points, extracts feature feedback, generates marketing claims, and compares competitor reviews. Use when users need review analysis, competitive intelligence, or customer feedback insights.
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。
Synthesize user feedback from multiple channels and identify patterns to inform product decisions. Use when analyzing feedback, prioritizing feature requests, conducting NPS surveys, or understanding user sentiment. Covers feedback collection, categorization, prioritization frameworks, and closing the feedback 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。