Tooluniverse Image Analysis

MLB data via ESPN public endpoints and the official MLB Stats API — scores, standings, rosters, schedules, game summaries, injuries, leaders, and news, plus an analytics backend: pitch-level velocity/spin/exit-velocity, career splits by stat group, league leaders, and schedules to 1901. Zero config, no API keys. Use when: user asks about MLB scores, standings, team rosters, schedules, game stats, box scores, play-by-play, injuries, transactions, depth charts, team/player statistics, MLB news, pitch speeds/spin/exit velocity, career stats, league leaders, or historical MLB seasons. Don't use when: user asks about minor league baseball, college baseball, or international baseball. For other sports use: nfl-data (NFL), nba-data (NBA), wnba-data (WNBA), nhl-data (NHL), football-data (soccer), tennis-data (tennis), golf-data (golf), cricket-data (cricket), cfb-data (college football), cbb-data (college basketball), fastf1 (F1). For betting odds use polymarket or kalshi. For news use sports-

When the user wants to plan, design, or implement an A/B test or experiment. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "conversion experiment," "statistical significance," or "test this." For tracking implementation, see analytics-tracking.

NHL data via ESPN public endpoints and the official NHL API — scores, standings, rosters, schedules, game summaries, injuries, futures, leaders, and news, plus an analytics backend: play-by-play with on-ice coordinates, cross-league career rows, skater/goalie leaders, and history to 1917. Zero config, no API keys. Use when: user asks about NHL scores, standings, team rosters, schedules, game stats, box scores, play-by-play, injuries, transactions, betting futures, team/player statistics, NHL news, shot locations, career stats, skater/goalie leaders, or historical NHL seasons. Don't use when: user asks about other hockey leagues (AHL, KHL, college hockey). For other sports use: nfl-data (NFL), nba-data (NBA), wnba-data (WNBA), mlb-data (MLB), football-data (soccer), tennis-data (tennis), golf-data (golf), cricket-data (cricket), cfb-data (college football), cbb-data (college basketball), fastf1 (F1). For betting odds use polymarket or kalshi. For news use sports-news.

Data analysis across SQL, visualization, statistics, and reporting. Use when writing SQL queries, building dashboards, performing cohort or funnel analysis, running hypothesis tests, or presenting data-driven recommendations.

Quantitative statistics framework for time-series analysis using Longbridge price data — ADF unit root test (stationarity), cointegration (Engle-Granger / Johansen), GARCH volatility modelling (conditional heteroskedasticity), regression diagnostics (Durbin-Watson / Breusch-Pagan), bootstrap confidence intervals, hypothesis tests (t-test / F-test). Requires statsmodels and scipy. Triggers: "量化统计", "ADF检验", "单位根", "协整检验", "GARCH", "自相关", "异方差", "Bootstrap", "假设检验", "量化統計", "ADF檢驗", "單位根", "協整檢驗", "異方差", "假設檢驗", "quantitative statistics", "ADF test", "unit root", "cointegration", "GARCH", "autocorrelation", "heteroskedasticity", "bootstrap", "hypothesis test", "statsmodels".

This skill should be used when the user asks to "analyze experimental results", "run strict statistical analysis", "compare model performance", "generate scientific figures", "check significance", "do ablation analysis", or mentions interpreting experiment data with rigorous statistics and visualization. It focuses on strict analysis bundles, not Results-section prose.