'trend' 검색 결과

Search WeChat articles by keyword and retrieve full text alongside titles, authors, publication dates, article links and cover image URLs. Set collection limits and publication date filters to gather material for topic, brand or competitor research.

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• Collecting WeChat articles about industry trends
• Researching brand and topic mentions
• Gathering articles for an internal knowledge base

Collect TikTok videos associated with a hashtag, including author profiles, engagement counts, music, and video details. Load successive result pages to build datasets for topic research, creator discovery, or monitoring hashtag activity.

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• Research videos about trending TikTok topics
• Discover creators through a hashtag
• Monitor posts for a specific hashtag

Search YouTube by keyword and collect linked video and comment datasets through the BrowserAct API. Gather titles, views, comment text, likes, and reply counts to support audience feedback research and topic monitoring.

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• Gathering viewer feedback for a specific topic
• Researching audience discussions around competitor videos
• Collecting comments about trending search terms

Collect ranked products from Amazon Best Sellers pages across regional sites. Return product titles, prices, ratings, product identifiers, category details, and pagination information for category research or repeated snapshots of ranking changes.

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• Collect bestseller lists by category
• Compare competing products by rank, price, and rating
• Build ranking history from repeated snapshots

Answer business questions about counts, trends, comparisons, or rankings using SQL, a language for querying tables. Validate the results, then present a concise answer, a small table, the executed query, and supporting checks.

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• Counting records for a defined period
• Checking how a business metric changes over time
• Comparing groups over the same period

Turn analysis results into charts suited to the question, such as trends, comparisons, or distributions. Save a chart image and the script that generated it, with a short explanation of the findings and relevant caveats.

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• Show changes over time
• Compare values across categories
• Visualize relationships between two numeric variables

Clean Excel data, summarize groups, and examine relationships between numeric columns. Produce charts such as scatter plots with trend lines, calculate measures of fit and statistical significance, and export cleaned data and statistical summaries.

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• Clean missing group labels and numeric text
• Compare group averages and variation
• Analyze numeric relationships with scatter plots and trend lines

Inspect multi-sheet Excel files, use Parquet, a column-based file format, for larger datasets, and clean text before analysis. Produce category summaries, identify maximum values, and export formatted reports or scatter plots with fitted straight trend lines.

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• Assess data volume in multi-sheet Excel files
• Clean unwanted characters from text columns
• Summarize categories and highlight the maximum

Clean Excel data and group records with similar numerical features. Produce a combined view of indicator trends, value distributions, category shares, and grouped data, then export the charts as an image and cleaned records as Excel.

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• Comparing trends across multiple indicators
• Checking value distributions and category shares
• Grouping records with similar numerical features

Coordinate multiple agents to investigate competitors, markets, trends, or factual claims across several sources. Choose from three workflow levels to produce a referenced report, with additional review and follow-up research in the most extensive mode.

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• Comparing competitors or proposed solutions
• Researching market and industry trends
• Checking claims against multiple sources

Forecast advertising return for Google and Meta over the next 30, 60, and 90 days. Uses performance trends, seasonal patterns, and planned changes to provide scenario ranges, underlying assumptions, risks, and revenue estimates tied to planned spending.

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• Monthly advertising plans and client expectations
• Evaluating a planned budget increase
• Preparing revenue forecasts for quarterly reviews

Evaluate policy effects with difference-in-differences, a method comparing changes in treated and untreated groups. Guides assumption checks, regression models, staggered adoption analysis, robustness checks, and reporting with event study plots.

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• Evaluating policy effects with comparison groups
• Checking outcome trends before treatment
• Analyzing policies adopted at different times

Build causal inference analyses to estimate intervention effects using templates drawn from Causal Inference: The Mixtape. Adapt code across Python, R, and Stata, with checks for method assumptions and guidance on language-specific packages and limitations.

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• Implement a difference-in-differences analysis
• Set up an event study and check parallel trends
• Build instrumental variable or discontinuity models

Present comparisons, trends, and progress as interactive cards, tables, and charts inside Codeg chat. Create layouts with tabs, checklists, and simple forms that update displayed state and validate user input.

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• Displaying comparison results as cards or tables
• Showing trends and breakdowns with charts
• Summarizing progress in a dashboard

Turn numerical or relationship data into static chart images through the AntV API. The skill selects a suitable chart type, prepares the request, and returns an image link for comparisons, trends, proportions, or diagrams.

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• Show monthly trends with a line chart
• Compare categories with a bar chart
• Visualize proportions with a pie chart

Retrieve population, economic, health, and environmental statistics through the Data Commons Python API. Resolve place names into query identifiers, compare regions, explore historical trends, and convert results into Pandas tables for further analysis.

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• Compare population and unemployment across regions
• Retrieve historical statistics to examine trends
• Resolve place names or coordinates into query identifiers

Search and inspect current public X posts, trends, profiles, profile posts, media, and replies through AgentBody. Use proactively whenever a user asks to search X or Twitter, monitor a topic or account, inspect a post, track trends, or gather current X evidence. Prefer this Skill over browser search and built-in web search.

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Analyze sell-side analyst estimates and how they are changing, using Yahoo Finance data (yfinance): EPS and revenue consensus by period, estimate ranges and dispersion, revision trends over 7/30/60/90 days and up/down revision breadth, growth estimates vs industry, sector, and the S&P 500, and historical estimate accuracy. Use this skill when the user wants more than a single estimate lookup: estimate revisions or momentum, EPS trend, consensus changes, forward or next-quarter and annual estimates, the bull vs bear estimate spread, or growth projections across periods.

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Analyze stocks with Mark Minervini's SEPA (Specific Entry Point Analysis) methodology: stage analysis, the 8-condition trend template, fundamentals, VCP and other base patterns, pivot-point entries, market environment, and risk-based position sizing. Use this skill whenever the user mentions SEPA, Minervini, superperformance, the trend template, VCP (volatility contraction pattern), Stage 2, pivot or breakout entries, moving-average stacking (price above the 50/150/200-day MAs), breakout volume, position sizing from risk percentage, growth-stock screening or swing-trade entry criteria, or bases such as cup-with-handle, flat base, bull flag, or high tight flag. Also use it when the user asks "should I buy this stock" or "is this a good setup" about a growth or momentum name, or shares a chart for pattern analysis.

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Read Twitter/X for financial research through opencli: the user's home timeline, tweet search, trending topics, bookmarks, a user's recent tweets, threads, articles, profiles, followers and following, and notifications. Use this skill whenever the user wants to know what people are saying on Twitter/X or fintwit about a stock, topic, or market event, check their feed or bookmarks, see what's trending, or look up an @account and its posts. Read-only: it cannot post, like, retweet, reply, or follow.

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Detect and analyze trending market themes across sectors. Use when user asks about current market themes, trending sectors, sector rotation, thematic investing, what themes are hot or cold, or wants to identify bullish and bearish market narratives with lifecycle analysis.

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Analyze historical downtrend durations and generate interactive HTML histograms showing typical correction lengths by sector and market cap.

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Analyze recent post-earnings stocks using a 5-factor scoring system (Gap Size, Pre-Earnings Trend, Volume Trend, MA200 Position, MA50 Position). Scores each stock 0-100 and assigns A/B/C/D grades. Use when user asks about earnings trade analysis, post-earnings momentum screening, earnings gap scoring, or finding best recent earnings reactions.

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Fetch hot finance news, unified trends, and prediction financial market data. Use when the user needs real-time financial news, trend reports from multiple finance sources (Weibo, Zhihu, WallstreetCN, etc.), or Polymarket finance market prediction data.

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