Discover and use data skills to extend Claude's capabilities
665 Data Skills Available
Run or debug Stata workflows through the local io.github.tmonk/mcp-stata server. Use when users mention Stata commands, .do files, r()/e() results, dataset inspection, Stata graph exports, or data browsing with sorting/filtering.
Queries data warehouse and answers business questions about data. Handles questions requiring database/warehouse queries including "who uses X", "how many Y", "show me Z", "find customers", "what is the count", data lookups, metrics, trends, or SQL analysis.
Ordo expression syntax quick reference. Includes comparison operators, logical operators, built-in functions, conditional expressions, field access syntax. Use for writing rule conditions, calculating output values, data transformation.
Deep-dive data profiling for a specific table. Use when the user asks to profile a table, wants statistics about a dataset, asks about data quality, or needs to understand a table's structure and content. Requires a table name.
Dataset versioning skill using DVC for tracking data changes, managing data pipelines, and ensuring reproducibility.
Profiles data assets to assess quality dimensions, detect anomalies, and generate comprehensive data quality reports with actionable recommendations.
Deep integration with product analytics platforms for metrics, funnels, retention, and experimentation. Query Amplitude/Mixpanel/Heap data, generate retention curves, calculate conversion metrics, and build dashboard configurations.
Perseus statistical analysis skill for proteomics data analysis and 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
Trace downstream data lineage and impact analysis. Use when the user asks what depends on this data, what breaks if something changes, downstream dependencies, or needs to assess change risk before modifying a table or DAG.
Trace upstream data lineage. Use when the user asks where data comes from, what feeds a table, upstream dependencies, data sources, or needs to understand data origins.
Guide for creating Observable Notebooks 2.0, the open-source notebook system for interactive data visualization and exploration. Use this skill when creating, editing, or building Observable notebooks.
The SampleInfo process is the pipeline entry point that reads sample metadata files, performs statistical analyses, and generates visualization reports.
Flexible marker finding process that wraps Seurat's FindMarkers function for custom group comparisons beyond simple cluster-vs-all analysis. Unlike ClusterMarkers (all-vs-all cluster comparisons), MarkersFinder enables targeted differential expression analysis between specific groups, conditions within cell types, or any custom comparison defined by metadata columns. Automatically performs pathway enrichment analysis on significant markers and generates comprehensive visualizations.
Performs fast Gene Set Enrichment Analysis (GSEA) on single-cell data using fgsea R package. Identifies enriched biological pathways by ranking genes based on differential expression between cell groups. Generates enrichment scores, significance metrics, and publication-ready visualizations.
Generate comprehensive data profiles for DataFrames. Use for EDA, data discovery, and understanding dataset characteristics.
Detect anomalies in data using statistical and ML methods. Z-score, IQR, Isolation Forest, and time-series anomalies.
Interpret YouTube Analytics, TikTok Analytics, and video performance data. Identifies trends, explains metrics, and provides actionable recommendations for growth. Use when analyzing video performance, understanding metrics, or optimizing channel strategy.
Expert data researcher specializing in discovering, collecting, and analyzing diverse data sources. Masters data mining, statistical analysis, and pattern recognition with focus on extracting meaningful insights from complex datasets to support evidence-based decisions.
Expert database optimizer specializing in query optimization, performance tuning, and scalability across multiple database systems. Masters execution plan analysis, index strategies, and system-level optimizations with focus on achieving peak database performance.
Expert data scientist specializing in statistical analysis, machine learning, and business insights. Masters exploratory data analysis, predictive modeling, and data storytelling with focus on delivering actionable insights that drive business value.
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
Ultra-fast data discovery and loading skill for industrial finance datasets. Handles CSV, JSON, DuckDB, Parquet, and Feather with memory-efficient 2-step discovery and loading.
Exploratory data analysis using ydata-profiling. Use when users upload .csv/.xlsx/.json/.parquet files or request "explore data", "analyze dataset", "EDA", "profile data". Generates interactive HTML or JSON reports with statistics, visualizations, correlations, and quality alerts.
Voice, tone, and content guidelines for data/ML dashboards. Covers microcopy, error messages, success states, and data presentation language. Auto-invokes on copy, messaging, content, labels, error messages keywords.
Comprehensive guide for BlazeMeter Test Data Management, including data entities, parameters, generation, orchestration, and management operations. Use when working with test data for (1) Creating and managing data entities and parameters, (2) Generating synthetic test data with seed lists and functions, (3) Using test data in tests (CSV, Data Entities), (4) Managing test data (backup, import/export, sharing), (5) Using Test Data Orchestration and Profiler, (6) Working with Test Data Pro, or any
Automate comprehensive market research using web data, competitive analysis, and structured synthesis. Use when researching markets, industries, competitors, or target audiences.
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
Use xsv for fast CSV data processing with selection, filtering, statistics, joining, sorting, and indexing for high-performance data manipulation.
UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.
Parse FCS (Flow Cytometry Standard) files v2.0-3.1. Extract events as NumPy arrays, read metadata/channels, convert to CSV/DataFrame, for flow cytometry data preprocessing.
Transform raw data from CSVs, Google Sheets, or databases into executive-ready reports with visualizations, key metrics, trend analysis, and actionable recommendations. Creates data-driven narratives for leadership. Use when users need to turn spreadsheets into executive summaries or board reports.
Parse, transform, and analyze CSV files with advanced data manipulation capabilities.
Transform, manipulate, and analyze JSON data structures with advanced operations.
Interactive database query builder for generating optimized SQL and NoSQL queries.
Expert data analysis and manipulation for customer support operations using pandas
Process CSV data files by cleaning, transforming, and analyzing them. Use this when users need to work with CSV files, clean data, or perform basic data analysis tasks.
