「sentiment」の検索結果

Head-to-Head Stock Comparison — takes two tickers and compares them across valuation, growth, profitability, technical setup, sentiment, risk profile, and analyst consensus with a scored comparison table and overall recommendation.

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Классифицирует пользовательский фидбек (Excel/CSV/текст) по 6 категориям, делает sentiment-анализ, кластеризацию тем, анализ трендов, триангуляцию по источникам, расчёт NPS и извлечение персон. На выходе — Top-10 болей с рекомендациями к действию. User-invoked only — do NOT auto-trigger. Triggers on /pm-feedback, "анализ обратной связи", "разбор отзывов", "анализ NPS", "analyze user feedback", "VOC analysis", "NPS analysis", "review analysis".

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Use Xquik to fetch X (Twitter) data or act through a connected account. It covers search, profiles, followers, replies, threads, timelines, media downloads, bulk exports, trends, monitors, signed webhooks, draws, posts, likes, follows, DMs, and AI analysis of posts (sentiment, brand mentions, news, market signals, viral score, custom labels). Also use for hashtag or @handle tracking when no other network is named, Xquik MCP setup, pricing, and X API comparisons. Skip data from other social networks, code that stays on the official X API (such as tweepy with an X developer bearer token), official X widget implementation, and content drafting or analysis without an API task. Not affiliated with X Corp.

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Leading economic indicators analysis, ISM PMI, yield curve, consumer sentiment UMCSI, jobless claims, building permits, economic turning point detection, recession signal analysis

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Research local markets by combining Google Maps reviews, Xiaohongshu local content, Weibo discussions, and web search. Covers customer sentiment by location, local competition analysis, neighborhood trends, and location-specific brand perception.

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Search tweets, analyze trends, monitor users, and gather social intelligence from Twitter/X through SandBase. Use when asked for Twitter research, social listening, trend analysis, influencer monitoring, sentiment tracking, or competitor social intelligence.

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Search videos, analyze channels, extract captions, read comments, and discover trends on YouTube through SandBase. Use when asked for YouTube research, video discovery, channel analysis, content strategy research, comment sentiment, or video transcript extraction.

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Research products across Amazon, Google Shopping, and Xiaohongshu to understand pricing, reviews, market positioning, and consumer sentiment. Covers competitive product analysis, pricing benchmarks, feature comparison, and customer satisfaction signals.

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Monitor conversations about any topic, brand, or keyword across Twitter, Reddit, Threads, Weibo, and community platforms simultaneously. Aggregates volume, sentiment, key voices, and emerging narratives across the global social web.

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Research any topic across China's major social platforms — Weibo, Douyin, Xiaohongshu, Bilibili, and Zhihu — simultaneously. Aggregates discussion volume, sentiment, key opinion leaders, and platform-specific trends for comprehensive China market intelligence.

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Rapidly assess crisis situations by monitoring Twitter, Reddit, news, and Chinese social platforms simultaneously. Detects escalation velocity, identifies key narratives, tracks official responses, and measures public sentiment shifts during critical events.

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Monitor brand mentions, sentiment, and reputation across Twitter, Reddit, news, and social platforms through SandBase. Use when asked for brand monitoring, reputation tracking, social listening, PR coverage analysis, or competitive brand intelligence.

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Analyze customer reviews for local businesses on Google Maps. Covers review extraction, sentiment patterns, rating distribution, common complaints, and competitor review comparison for local business intelligence and reputation management.

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Use this skill when an agent needs AssemblyAI for speech-to-text or speech-understanding work in media production, including pre-recorded, synchronous short-file, and real-time streaming transcription; speaker diarization or speaker identification; captions and subtitles; timestamps; language detection, code-switching, or transcript translation; audio intelligence such as summaries, chapters, topics, entities, key phrases, sentiment, content moderation, profanity filtering, and PII redaction; webhooks, scaling, rate limits, retention, security, consent, and QA for podcasts, interviews, captions, call recordings, and edit workflows.

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Hoyeon developer community scan workflow for Codex. Use when the user invokes "$hoyeon-dev-scan" or asks for developer reactions, community opinions, or cross-community sentiment on technical topics. This adapter loads the canonical dev-scan skill and follows its Codex runtime surface.

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This skill should be used when the user says "/council", "council", "deliberate", "multi-perspective decision", "트레이드오프 분석", "위원회 소집", "여러 관점으로 검토", or wants deep multi-perspective deliberation with tradeoff mapping. Combines tribunal (structured adversarial review), agent-council (external LLM opinions), dev-scan (community sentiment), and step-back (meta-level review) into a unified decision-making committee. Uses Agent Teams for real peer-to-peer debate with iterative step-back moderation loop.

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Expert in measuring what matters in communities. Covers health metrics, engagement analytics, sentiment analysis, cohort tracking, and reporting. Knows that good data drives good decisions, and bad metrics drive bad behavior. Use when "community metrics, community analytics, measure community, community health, engagement metrics, community reporting, " mentioned.

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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.

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Applies the empiricist, skeptical, and practical reasoning of David Hume, 18th-century Scottish philosopher. Use this skill whenever you encounter questions about epistemology, causality, human nature, moral philosophy, political authority, or the limits of rational knowledge. Trigger this skill when the user is grappling with abstract theories that need grounding, evaluating causal claims, discussing the role of emotion vs. reason in decision-making, or questioning the legitimacy of institutions. Even if the user doesn't name Hume, apply his frameworks (like Hume's Fork or the Impression Test) to cut through metaphysical speculation, ground arguments in observable experience, and recognize that reason is ultimately guided by human sentiment.

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Collecting user feedback via NPS surveys, review analysis, sentiment analysis, feedback classification, and insight extraction reports. Use when establishing feedback loops.

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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.

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Fetch Bilibili (哔哩哔哩) video comments for UP主 self-analysis. Use when the user asks to collect, download, export, or analyze comments on a Bilibili video (BV号 / URL / UID). Produces JSONL + summary.json suitable for further Claude Code analysis (sentiment, keywords, audience trends). Read-only; does not post/edit/delete.

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Activates Warren Buffett's complete investment thinking system. The following scenarios must trigger it: analyzing any stock or company, evaluating investment opportunities, interpreting financial reports/annual reports/shareholder letters, assessing business moats or competitive advantages, evaluating management quality and integrity, making buy/hold/sell decisions, understanding core value investing concepts (compounding/intrinsic value/margin of safety/circle of competence/Mr. Market), analyzing any industry (insurance/banking/consumer/media/energy/railroads/technology), handling capital allocation/buybacks/dividends questions, assessing market sentiment and macro risks, exploring when to sell, analyzing institutional imperative or management behavior. Even if the user does not mention "Buffett," proactively trigger whenever the topic involves investment analysis, business quality assessment, or investment decision-making.

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Expert guide for Affective Computing, emotional AI, and real-time sentiment analysis through native multimodal tokens (voice intonation and facial micro-expressions) / Panduan ahli komputasi afektif, AI emosional, dan analisis sentimen real-time melalui token multimodal native.

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。