「sentiment」の検索結果

Classify reply sentiment and determine next action

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Detect crisis signals in user content using NLP, mental health sentiment analysis, and safe intervention protocols. Implements suicide ideation detection, automated escalation, and crisis resource integration. Use for mental health apps, recovery platforms, support communities. Activate on "crisis detection", "suicide prevention", "mental health NLP", "intervention protocol". NOT for general sentiment analysis, medical diagnosis, or replacing professional help.

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Recent community and social trend research over the last 30 days. Use when the brief asks what people are saying now, recent sentiment, community reactions, social proof, launch reaction, trend scan, or last-30-days context.

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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," "PMF survey," "product/market fit survey," "customer interview questions," "interview outreach," "Sales Safari," or "find out why customers churn/convert/buy." Use for analyzing existing research assets, mining online sources, AND running primary research (interviews and surveys). For writing copy informed by research, see copywriting. For acting on research to improve pages, see 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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Crypto market leaderboards — ranked aggregate feeds across the whole market: social-hype/sentiment rank, trending / top-search / Binance Alpha / tokenized-stocks rank, smart-money net-inflow rank (which tokens received the most inflow), top meme tokens by breakout score on Pulse launchpad, top trader PnL leaderboard (ALL / KOL). Use whenever the user wants a ranked list of tokens or addresses by some metric — phrases like "trending tokens", "top N by hype", "leaderboard", "rank by X", "biggest inflows", "top traders this week".

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Social media intelligence: financial signal extraction from Twitter/X, Telegram, Discord, and Reddit for sentiment-driven trading strategies.

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市场情绪分析——恐贪指数/Put-Call Ratio/融资融券/北向资金信号解读、社交媒体舆情量化框架

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Behavioral finance applications: theories of overreaction and underreaction, behavioral explanations for momentum and reversal, investor sentiment cycles, cognitive-bias checklists, and debiasing quantitative strategies.

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Event-driven strategy based on sentiment-scored signals from news, announcements, and macro events. The LLM acts as the NLP engine, and event data follows a CSV schema.

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Watches what customers are saying in public and in private, then does something about it. Aggregates Google, Yelp, and Facebook reviews alongside disputes, tickets, and email into themes backed by verbatim quotes; drafts a reply to every review in the owner's own voice for approval; spots customers who have gone quiet or look likely to leave; and drafts win-back offers for the ones worth keeping. With Shopify connected, order and fulfillment patterns become a sentiment signal too. Works from pasted or exported reviews when nothing is connected. Use this whenever the owner asks about reviews, ratings, reputation, complaints, or repeat business — including "what are people saying about us," "did we get any bad reviews," "how do I respond to this one-star," "our rating dropped," "which customers have gone quiet," "who hasn't ordered in a while," "how do I win them back," or "are customers happy."

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Answers one question for an SMB owner — is the growth engine actually working? Pulls sales trend by channel, funnel conversion, campaign return, best and worst performing products, and customer sentiment from whatever is connected, then ends with the three growth actions worth taking this week. The growth-side twin of business-pulse, which covers the finance side. Use this whenever the owner asks how marketing or sales is performing, whether a campaign paid off, where leads are coming from, why the pipeline is stalling, which products are moving, or says anything like "is my marketing working," "growth check," "how's the funnel," or "where should I put my money next month." Reach for it even when the owner names a single channel rather than growth overall.

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Map the people in a deal or account - roles, influence, sentiment, who's missing, and your best access path to the people you haven't reached. Use when the user asks "who are the players at [account]", "who's my way in", "am I single-threaded on [deal]", "map the stakeholders", or "who else should I be talking to".

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Weekly NPS/CSAT theme analysis for {{survey_sheet}}. Reads survey responses from Google Sheets, clusters them into themes with sentiment and detractor drivers, tracks score movement week over week, and posts a summary with representative quotes to {{report_channel}}. Read-only on the sheet and report-only — no writes to any survey system, no respondent contact.

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Daily brand-mention monitoring loop for {{brand_terms}}. Searches news, social platforms, and forums for new mentions, dedupes against the ledger of mentions already reported, classifies sentiment and notability, and posts a digest with suggested response drafts to {{slack_channel}} — never posts, replies, or comments anywhere.

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Expert knowledge for AI intelligence collection — OSINT methodology, entity extraction, knowledge graphs, change detection, and sentiment analysis

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HARD BLOCK — never use for prediction-market/Polymarket UpDown queries; route to okx-dapp-discovery when a named DApp (Polymarket/Aave/Hyperliquid/PancakeSwap/Morpho) appears with a timeframe, or 涨跌/updown for BTC/ETH/SOL/XRP/BNB/DOGE/HYPE. Otherwise, read-only on-chain DEX data, 6 groups: TOKEN (search, hot/热门, liquidity, holders/whale, risk metadata, cluster/持仓集中度, trade history, top traders); MARKET (price/价格, K线/OHLC, index price, wallet PnL/胜率, trade history); SIGNAL (smart money/KOL/whale tracking, buy signals/信号, leaderboard/牛人榜); SOCIAL (news/新闻, sentiment/情绪, token vibe/热度, KOL leaderboard); TRENCHES (pump.fun/meme launches/新盘/扫链, dev reputation, bundle/sniper detection/捆绑狙击者, co-investor — read-only; buy/snipe → okx-dapp-discovery); WS (onchainos ws CLI, or custom WebSocket script/脚本). Also owns Market API payment/x402, quota/额度, and MARKET_API_*_OVER_QUOTA/confirming:true for all 6 groups.

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Access real-time crypto token data, DeFi analytics, wallet intelligence, project research, and blockchain insights through Heurist Mesh agents. Use when the user asks about token trends, DeFi protocols, wallet holdings, project due diligence, Twitter/X crypto sentiment, or deeper market analysis.

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This skill helps users extract structured data from Reddit posts and comments via BrowserAct API. Agent should proactively apply this skill when users express needs like analyzing competitor mentions on Reddit, tracking brand sentiment in Reddit comments, extracting Reddit discussions for market research, finding popular Reddit posts by keywords, monitoring community feedback on specific topics, gathering user reviews from Reddit threads, searching for Reddit posts within a specific date range, sorting Reddit discussions by relevance or hotness, compiling nested Reddit comments for deep analysis, building a structured dataset of Reddit conversations, discovering trending topics in specific subreddits, or monitoring social media activity for specific brands on Reddit.

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。

This skill helps users extract full article contents from WeChat using the BrowserAct API. The Agent should proactively apply this skill when users express needs like finding full WeChat articles for specific keywords, tracking WeChat public accounts for industry trends, extracting WeChat article contents for media research, monitoring public relations on WeChat platforms, collecting competitor updates from WeChat, getting full article body from WeChat links, monitoring brand exposure on WeChat articles, retrieving structured WeChat data for sentiment analysis, summarizing daily news from WeChat, getting author and publication date for WeChat articles, or automating WeChat content extraction without scraping.

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Collects every tweet in an X (Twitter) conversation thread given a conversation id (root tweet id) — the focal tweet plus all replies, sub-replies, and quote chains — and returns normalized per-tweet data with text, author, engagement counts, media, hashtags, mentions, in_reply_to mapping, and cursor for pagination. Use when user mentions Twitter conversation, X conversation thread, conversation_id, thread scraper, scrape Twitter replies, all replies to a tweet, replies under a tweet, sub-replies, nested replies, thread harvester, get replies of a tweet, scrape comments on Twitter, scrape comments on X, full thread extraction, conversation export, conversation tree, reply chain, thread dump, X tweet thread, twitter thread scrape, comment scraping twitter, comment scraping x, focal tweet plus context, root tweet plus replies. Also applies to sentiment analysis on a single viral tweet, controversy mapping, harvesting community Q&A threads, capturing AMA threads, recovering long-running discussions, and any paginated bulk reply collection driven by a conversation id.

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。

This skill helps users automatically extract structured article details and full content from Zhihu via the BrowserAct API. Agent should proactively apply this skill when users express needs like: searching for Zhihu articles on a specific topic, tracking industry trends on Zhihu, monitoring public relations or sentiment on Zhihu, collecting competitor updates, getting the latest reports on specific keywords, monitoring brand exposure in Zhihu media, researching market hot topics, summarizing daily Zhihu industry news, retrieving hot events from the past week, extracting structured data for market research, finding full Zhihu articles for AI agents, extracting full article body from Zhihu links.

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Searches X (Twitter) for tweets by free-form advanced query and returns a normalized tweet list with text, author profile, engagement counts, media, hashtags, mentions, and cursor for pagination. Use when user mentions X search, Twitter search, scrape tweets by keyword, search X by hashtag, search Twitter by hashtag, find tweets about a topic, search tweets by date range, since until search Twitter, advanced Twitter search, tweets with media, tweets with images, tweets with video, top tweets, latest tweets, X latest tab, X top tab, min_faves, min_retweets, min_replies, filter verified Twitter, filter blue verified, from user Twitter, to user Twitter, mentioning user Twitter, geocode Twitter search, near location Twitter, lang code search Twitter, exclude retweets, exclude replies, collect tweets at scale, bulk tweets export, monitor brand mentions on X, monitor brand mentions on Twitter, competitor mention monitoring, KOL tweet harvesting, twitter keyword scraper, tweet keyword scraper, search X by keyword, search twitter, search x.com, x.com search, twitter advanced search, x advanced search, tweet collection by query, scrape twitter search results. Also applies to time-bounded research, sentiment analysis input gathering, hashtag campaign tracking, geo-targeted tweet collection, and any paginated bulk tweet collection driven by a search query.

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This skill helps users automatically extract structured news data from Google News via BrowserAct API. Agent should proactively apply this skill when users express needs like searching for news about a specific topic, tracking industry trends, monitoring public relations or sentiment, collecting competitor updates, getting latest reports on specific keywords, monitoring brand exposure in media, researching market hot topics, summarizing daily industry news, tracking media activities of specific individuals, retrieving hot events from the past 24 hours, extracting structured data for market research, monitoring global breaking news.

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。