203건 · 관련도순
Evaluate survey data pipelines and research methodology. Analyzes response bias detection (speeders, straight-liners, bots), statistical significance testing (t-test, chi-square, ANOVA with Bonferroni correction), sentiment and theme extraction from open-ended responses.
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Analyzes App Store and Play Store listing optimization -- keyword research, title optimization, screenshot conversion analysis, A/B testing setup, review sentiment analysis, competitor gaps, and localization coverage..
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Pull open [Gorgias](https://composio.dev/toolkits/gorgias) support tickets and triage them by urgency, category, and sentiment
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关于巴西中央银行法规合规的完整指引：《国民货币委员会第 4,893/2021 号决议》（网络安全政策）、《巴西中央银行第 85/2021 号决议》（GRSIC）、巴西开放金融（BCB 第 32/2020 号决议及更新）以及 BACEN 的其他审慎规则。涵盖网络安全政策的起草和审查、事件行动与响应计划（PARI）、信息和通信服务风险管理（GRSIC）、开放金融中的同意与数据共享、API 要求、第三方管理（外包）和 BACEN 制裁。触发词：Bacen、Banco Central、CMN 4.893、Resolução 4.893、segurança cibernética bancária、PARI、GRSIC、Open Finance、Open Banking、compartilhamento de dados financeiros、consentimento Open Finance、API financeira、outsourcing bancário、risco cibernético、incidente cibernético banco、LGPD financeira、fintech compliance、instituição financeira、DICT、Pix segurança。
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A-share short-term trading decision skill for 1-5 day horizon. Use when you need real-data market sentiment, sector rotation, strong stock scanning, capital flow confirmation, date-based short-term signal scoring, prediction logging, and next-day market comparison for CN A-share momentum trading.
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Compare brands and products across social media — share of voice, sentiment, positioning, and audience overlap using Xpoz. Use when asked to "compare brands", "competitive analysis", "share of voice", "brand vs brand", or "competitive intelligence".
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Azure AI Text Analytics SDK for sentiment analysis, entity recognition, key phrases, language detection, PII, and healthcare NLP. Use for natural language processing on text.
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Aplica as cores de marca oficiais e tipografia da Anthropic a qualquer tipo de artefato que possa se beneficiar de um visual e sentimento do padrão Anthropic. Use quando diretrizes de cores de marca, guias de estilo, normas de design visual ou padrões de design corporativo se aplicarem.
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Builds AI-powered trading and financial analysis agents with multi-agent LLM architectures: research pipelines, sentiment signals, portfolio optimization, backtesting, risk guardrails, and market monitoring. Use when designing or implementing an LLM-based trading or market-analysis system.
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Synthesises a batch of customer feedback (survey answers, reviews, ticket and chat comments) into a DRAFT themed report: coded themes with record counts and shares, anonymised verbatim quotes cited to record codes, contradictions and unverified claims, and the follow-up questions to answer next. Produces no sentiment score or percentage positive as fact; ratings appear only as distributions with n. Use when the user asks to "theme this feedback", "what are customers saying", "summarise these survey answers", "analyse these reviews", "find the top complaints in these comments" or "code this voice of the customer data". Do not use for exit interviews, use exit-interview-synthesis instead; for sorting a live queue and drafting replies, use ticket-triage-pack; for project retrospectives, use lessons-learned-synthesis. Drafts for human review; never approves, authorises or signs off.
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Research any open-source repository end to end and answer the core question — SHOULD YOU contribute to it? — with a GO / NO-GO / GO-IF verdict backed by evidence: snapshot, momentum, contribution landscape (PR acceptance rates, outside-contributor merge rates, first-timer outcomes), issue health, governance, community sentiment, and a final go/no-go recommendation. Use when the user asks 'should I contribute to X', wants a before-I-contribute due-diligence check on a project, asks whether a project accepts outside PRs, wants contribution-health numbers like PR merge rates or stale-PR counts, or asks for a deep dive on an open-source codebase's health and dynamics before investing time in it.
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Use when the user asks to "analyze influencer campaign performance", "compare influencers", or "find what content worked"; produces metric scorecards vs target and benchmark, platform/influencer/content rankings, engagement-quality and sentiment reads, conversion-attribution breakdowns, and ranked learnings. Not for dollar-level return math — use roi-calculator. 达人营销效果分析/投放复盘
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Use when the user asks to "triage our comments, DMs, and mentions", "draft replies to this thread", "can we repost this fan post", or "set up inbox SLAs and an escalation path"; produces a ranked triage queue with register detection (sincere / ironic / performative / parasocial, sentiment-inversion table included — "this is so bad" under a comedy register is praise), a commenter taxonomy (troll monitor-only / rager / misguided / unhappy-customer / advocate) with a response-tier ladder and per-channel SLAs, an escalation matrix ending at the crisis path, a moderation ladder plus house rules for owned spaces, and a UGC curation-and-rights mode whose dated permission entries route to the channel registry — every reply is a ranked DRAFT a human posts; nothing is ever auto-sent. Not for launch-window feedback triage — use launch-feedback-synthesizer. 评论私信提及分诊/语域识别/回复草稿/UGC授权
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Use when the user asks to "build our social crisis protocol", "mentions are exploding — what do we do first", or "when do we pause the posting queue"; produces a 1-5 severity ladder with tunable Estimated trigger thresholds (mention-velocity multiples vs the 7-day listening baseline, sentiment flip, journalist/regulator contact, employee-conduct class), the first-mechanical-action rule — pause ALL scheduled posts AND paid amplification, with dated state markers dropped to the channels proposal protocol and reconciled post-incident — a pre-approved holding-statement library with committed update cadences, when-NOT-to-post rules, a spokesperson/approval matrix, and a post-crisis retro template; re-runs the social-quality-auditor pre-publish gate before un-pausing the queue. Not for email deliverability incidents (blocklist, spam-rate spikes) — use deliverability-qa; inside a launch window launch-day-conductor owns incident handling. 社媒危机预案/暂停队列/声明库/发言人矩阵
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Azure AI Text Analytics SDK for sentiment analysis, entity recognition, key phrases, language detection, PII, and healthcare NLP. Use for natural language processing on text.
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Azure AI Text Analytics SDK for sentiment analysis, entity recognition, key phrases, language detection, PII, and healthcare NLP. Use for natural language processing on text.
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Track reviews, ratings, sentiment, and brand mentions across Google Maps, Booking.com, TripAdvisor, Facebook, Instagram, YouTube, and TikTok. Use when user asks to monitor brand reputation, analyze...
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Access real-time and historical stock market data, forex rates, cryptocurrency prices, commodities, economic indicators, and 50+ technical indicators via the Alpha Vantage API. Use when fetching stock prices (OHLCV), company fundamentals (income statement, balance sheet, cash flow), earnings, options data, market news/sentiment, insider transactions, GDP, CPI, treasury yields, gold/silver/oil prices, Bitcoin/crypto prices, forex exchange rates, or calculating technical indicators (SMA, EMA, MACD, RSI, Bollinger Bands). Requires a free API key from alphavantage.co.
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Compare brands and products across social media — share of voice, sentiment, positioning, and audience overlap using Xpoz. Use when asked to "compare brands", "competitive analysis", "share of voice", "brand vs brand", or "competitive intelligence".
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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.
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Azure AI Text Analytics SDK for sentiment analysis, entity recognition, key phrases, language detection, PII, and healthcare NLP. Use for natural language processing on text.
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Azure AI Text Analytics SDK for sentiment analysis, entity recognition, key phrases, language detection, PII, and healthcare NLP. Use for natural language processing on text.
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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 page-cro.
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Azure AI Text Analytics SDK for sentiment analysis, entity recognition, key phrases, language detection, PII, and healthcare NLP. Use for natural language processing on text.
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