Data Skills

Combine heterogeneous data sources into a unified model with conflict resolution, schema alignment, and provenance tracking. Use when merging data from multiple systems, consolidating information, or building comprehensive views.

Forecast future states or outcomes based on current data and trends. Use when estimating future values, projecting trajectories, forecasting outcomes, or anticipating system behavior.

Detects dangerous DDL (Drop/Truncate) and data type anti-patterns.

Julia-based econometric and structural estimation for computationally intensive tasks. Use for structural models, maximum likelihood, GMM, numerical optimization, simulations, and high-performance computing. Covers DataFrames.jl, FixedEffectModels.jl, Optim.jl, and performance optimization.

This skill should be used when the user asks to "process data in Nushell", "use polars", "work with dataframes", "use lazyframes", "analyze CSV data", "transform large datasets", "aggregate data", "join tables", "pivot data", "melt dataframes", or mentions polars, dataframes, lazyframes, or high-performance data manipulation in Nushell.

Performs comprehensive data analysis, visualization, and statistical modeling using Python. Use when analyzing datasets, performing statistical tests, creating visualizations, doing exploratory data analysis, or generating publication-quality analytical reports.

Create interactive metocean visualizations including time series plots, wave roses, scatter plots, geographic maps, and dashboards. Use for data exploration, reporting, and operational monitoring.

Use PROACTIVELY when user asks for ASCII diagrams, text diagrams, or visual representations of systems, workflows, or relationships. Triggers on "ascii diagram", "text diagram", "visualize", "show how X connects/synergizes", "diagram the flow/phases", or "illustrate relationships". Generates terminal-compatible diagrams using box-drawing characters. Supports architecture, before/after, phased migration, data flow, and relationship/synergy diagrams. Not for image generation or graphical output.

Pandas for time series analysis, OrcaFlex results processing, and marine engineering data workflows

Generate interactive validation reports with quality scoring, missing data analysis, and type checking. Combines Pandas validation, Plotly visualization, and YAML configuration for comprehensive data quality reporting.

Activate for marketing analytics, KPI tracking, reporting dashboards, attribution analysis, and performance optimization. Use when analyzing campaign data, creating reports, or measuring marketing ROI.

Comprehensive guide for data preprocessing patterns in ML, covering data cleaning, feature engineering, normalization, and pipeline creation.

Analyze preprocessed data for investigative journalism with full transparency. Use when a journalist has clean, preprocessed data ready for analysis and needs to identify patterns, anomalies, relationships, or statistical findings that support a story. Triggers include requests to analyze data, find patterns, identify outliers, cross-reference records, calculate statistics, or answer specific investigative questions. Complements the structured-data-preprocessing skill. Emphasizes simple, legible

Data import/export and GDPR compliance. Use when working with user data export, import, or privacy features.

Automatically analyzes datasets to perform classification, regression, or clustering. Generates Python training scripts and HTML reports.

Quick data queries and previews. Use when user wants to see contents of a data file, check schema, or do simple filtering on CSV, JSON, or other data files.

Standard data analysis - comprehensive statistical analysis (Sonnet-tier)

Python 생태계(Jupyter, Pandas, Scikit-learn)를 활용하여 데이터에서 심층적인 인사이트를 도출하는 전문 분석 워크플로우입니다.

Expert assistant for monitoring and optimizing performance in the KR92 Bible Voice project. Use when analyzing query performance, optimizing database indexes, reviewing React Query caching, monitoring AI call costs, or identifying N+1 queries. Helps diagnose slow operations across database, frontend, and AI systems.

Create and edit Excel spreadsheets for budgets, expense tracking, event planning, project management, and data analysis. Use for financial and organizational tasks.

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Debug Pandas issues systematically. Use when encountering DataFrame errors, SettingWithCopyWarning, KeyError on column access, merge and join mismatches with unexpected NaN values, memory errors with large DataFrames, dtype conversion issues, index alignment problems, or any data manipulation errors in Python data analysis workflows.

Create Excel files with multiple sheets and cross-sheet formulas including COUNTIFS, VLOOKUP, and MATCH. Keep source data in one sheet and create summary sheets with formulas referencing the source data.

Navigate Supabase database tables, relationships, and query patterns. Schema reference for Empathy Ledger.

Analyze web measurement data with Python/pandas/SQL. Use when user mentions 'analyze data', 'traffic analysis', 'statistics', 'pandas', 'SQL query', or 'plot results'.

Data Scientist Agent. ML 모델 개발, 실험, 분석을 담당합니다.

Systematic exploratory data analysis following best practices. Use when analyzing any dataset to understand structure, identify data quality issues (duplicates, missing values, inconsistencies, outliers), examine distributions, detect correlations, and generate visualizations. Provides comprehensive data profiling with sanity checks before analysis.

Teach Bayesian approaches to meta-analysis including prior specification, MCMC methods, and interpretation of posterior distributions. Use when users want to incorporate prior knowledge, need probabilistic interpretations, or are working with sparse data.

Expert assistant for monitoring and optimizing performance in the KR92 Bible Voice project. Use when analyzing query performance, optimizing database indexes, reviewing React Query caching, monitoring AI call costs, or identifying N+1 queries.

データ分析・可視化・レポート作成。pandas、SQL、BigQuery、スプレッドシート操作、統計分析、グラフ作成。「データ分析」「SQL」「BigQuery」「pandas」「集計」「可視化」「レポート」に関する質問で使用。

Analyzes data with rich metadata recommendations

This skill should be used when performing local data exploration, profiling, quality analysis, or transformation tasks using DuckDB. It handles CSV, Parquet, and JSON files, provides automated data quality reports, supports complex JSON transformations, and generates interactive HTML reports for data analysis.

Standard and NaN-robust statistical functions for data analysis, histograms, and correlation matrices. Triggers: statistics, mean, nanmean, histogram, corrcoef, percentile, std.

Unified stress-test scenario engine for TMNL. Invoke when implementing real-time data streams, payload generators, throughput monitoring, or circuit breaker patterns. Provides EmissionEngine, reservoir sampling, and D3 visualizations.

Collects, analyzes, and reports software metrics for data-driven decision making and continuous improvement

Data cleaning and preprocessing workflow including handling missing values, encoding categorical variables, filtering rows, removing columns, and checking multicollinearity (VIF). Use when preparing data for analysis, cleaning messy datasets, or transforming variables. Triggers: 資料清理, data cleaning, 缺失值, 處理資料, preprocess, missing values, 遺漏值, encoding, 編碼, VIF, multicollinearity, 共線性, filter, 過濾, rename columns.

Result delivery workflow for retrieving analysis results, downloading files from MinIO, and sharing reports with users. Use when user wants to download results, export reports, get analysis outputs, or share data files. Triggers: 下載結果, 取得報告, 傳檔案, share results, download, 輸出, export, 結果在哪, where is result, 報告, report, 圖表, visualization.

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: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas

Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When MiniMax-M2 needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas

Validate data quality in CSV/Excel files for vehicle insurance platform. Use when checking required fields, validating data formats, detecting quality issues, or generating quality reports. Mentions "validate", "check fields", "data quality", "missing values", or "quality score".