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Found 317 Skills
Use this skill when performing exploratory data analysis, statistical testing, data visualization, or building predictive models. Triggers on EDA, pandas, matplotlib, seaborn, hypothesis testing, A/B test analysis, correlation, regression, feature engineering, and any task requiring data analysis or statistical inference.
Riot 공식 LoL Esports 데이터와 Oracle's Elixir 스타일 historical 데이터로 LCK 경기 결과, 현재 순위, live turning point, 밴픽 matchup/synergy, patch meta, 팀 파워 레이팅을 조회한다.
Read, edit, analyze, and create Microsoft Excel files (.xlsx, .xls, .xlsm, .csv, .tsv). Use when a user asks to: (1) Open/read/inspect an Excel file, (2) Edit or modify spreadsheet data, formulas, or formatting, (3) Analyze spreadsheet data and provide insights, statistics, or trends, (4) Create new Excel files with data, formulas, charts, or formatting, (5) Convert between CSV/TSV and Excel formats, (6) Build financial models or dashboards in Excel.
Corporate event-driven analysis via Longbridge Securities — captures and classifies events that create pricing dislocations: major-shareholder increases/decreases, equity incentives, private placements, rights issues, buybacks, M&A/restructuring, index rebalancing, and management changes. Combines filings, corporate actions, and shareholder data to produce event signals. Triggers: "公司事件", "事件驱动", "大股东增持", "大股东减持", "股权激励", "定增", "配股", "回购", "并购重组", "指数调整", "管理层变更", "公告分析", "公司事件", "事件驅動", "大股東增持", "大股東減持", "股權激勵", "定增", "配股", "回購", "並購重組", "指數調整", "corporate event", "event-driven", "share buyback", "equity incentive", "major shareholder increase", "rights issue", "M&A arbitrage", "index rebalancing", "insider buying", "corporate action analysis".
This skill should be used when analyzing CSV datasets, handling missing values through intelligent imputation, and creating interactive dashboards to visualize data trends. Use this skill for tasks involving data quality assessment, automated missing value detection and filling, statistical analysis, and generating Plotly Dash dashboards for exploratory data analysis.
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for creating new spreadsheets, reading/analyzing data, modifying existing spreadsheets, or recalculating formulas.
Track real-time cryptocurrency prices across exchanges with historical data and alerts. Provides price data infrastructure for dependent skills (portfolio, tax, DeFi, arbitrage). Use when checking crypto prices, monitoring markets, or fetching historical price data. Trigger with phrases like "check price", "BTC price", "crypto prices", "price history", "get quote for", "what's ETH trading at", "show me top coins", or "track my watchlist".
Specialized utility for advanced manipulation, analysis, and creation of spreadsheet files, including (but not limited to) XLSX, XLSM, CSV formats. Core functionalities include formula deployment, complex formatting (including automatic currency formatting for financial tasks), data visualization, and mandatory post-processing recalculation.
Retrieve detailed revenue breakdown by product segment for public companies. Use when analyzing product mix, revenue concentration, segment contribution, or business line performance.
Complete DataForSEO API integration for SEO data and analysis. Use when the user asks for keyword research, search volume, SERP analysis, backlink audits, competitor analysis, rank tracking, domain authority, technical SEO audits, content monitoring, Google Trends, or any SEO-related data queries. Covers all DataForSEO APIs including SERP, Keywords Data, DataForSEO Labs, Backlinks, OnPage, Domain Analytics, Content Analysis, Business Data, Merchant, App Data, and AI Optimization APIs. Outputs CSV files.
Side-by-side stat comparisons with context. Adjust for era, pace of play, league differences. Advanced metrics explained in plain English.
R programming for data analysis, visualization, and statistical workflows. Use when working with R scripts (.R), Quarto documents (.qmd), RMarkdown (.Rmd), or R projects. Covers tidyverse workflows, ggplot2 visualizations, statistical analysis, epidemiological methods, and reproducible research practices.