Discover and use data skills to extend Claude's capabilities
665 Data Skills Available
Formats structured data using TOON v2.0 to minimize tokens while preserving readability. Use when outputs include tables, logs, events, or repeated records and token budgets matter. Triggers include "format table", "structured data", "TOON", "minimize tokens", or "large list".
Data analysis and reporting patterns for LogiAccounting Pro. Use when generating reports, analyzing trends, or creating visualizations.
Data analysis with end-state first protocol. Clarify decisions before diving into data. Python/pandas focused.
Database (PostgreSQL) SQL best practices for clean, performant, and maintainable queries. Use when writing or reviewing SQL, schema changes, or database-related guidance.
Generates data-driven reports about the project. Use for initial project reports or session summaries.
A skill to search historical data for price, volume, or event patterns similar to the current context.
Expert knowledge of sequence analysis for longitudinal data, including TraMineR (R) and TanaT (Python) packages. Use when working with state sequences, event sequences, trajectory analysis, distance metrics (optimal matching, Hamming, LCS), clustering, and visualization of sequential data.
Best practices for creating comprehensive Jupyter notebook data analyses with statistical rigor, outlier handling, and publication-quality visualizations
Use when evaluating data for AI projects. Use before project commitment. Produces data quality assessment, gap analysis, and remediation recommendations.
Helper functions for NA/missing value handling in Excel data. Provides Python and VBA implementations following CLAUDE.md NA handling guidelines.
Build monitoring dashboards with Grafana. Covers panel types, queries, variables, alerting, provisioning, and data sources like Prometheus and InfluxDB. Use for infrastructure monitoring, observability, and metrics 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
Perform paired t-tests and repeated-measures ANOVA for biomechanical data analysis with formatted Excel output. Use when analyzing EMG, force, kinematics data with statistical comparisons, creating auto-updating Excel reports, or applying Excel formula automation. Always outputs publication-ready Excel files.
Write data analysis reports where all quantitative information appears in programmatically-generated plots, never in hand-written text tables. Prevents AI from fabricating numbers by ensuring all values come from computed data rendered visually. Use when creating analysis reports, generating summary statistics, or presenting correlation/comparison results.
Guidelines for managing TimescaleDB hypertables, continuous aggregates, and migrations. Use this when creating new tables or modifying time-series data schemas.
A specialized skill for extracting, cleaning, and analyzing structured data from various formats (CSV, JSON, Markdown tables).
MongoDB database exploration for understanding game data, debugging, and investigation. Auto-applies when discussing database structure or debugging data issues.
Data analysis, scientific computing, visualization with pandas, numpy, matplotlib
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
Query Logfire database and generate rich dashboards from results. Use when analyzing telemetry data, creating visualizations, or exploring Logfire records.
Expert system for evaluating machine learning models. Automates the analysis of Confusion Matrices, PR Curves, and MLflow history comparison to provide objective, data-driven recommendations.
Analyze McDougall-style fuel business data (SQLite via Laravel) to answer business questions, build KPIs, propose dashboards, and deliver actionable insights for operations leadership.
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
Calculate and track key performance indicators (KPIs) from pilot data and defined metrics. Use when deriving success metrics, benchmarking performance against objectives, or preparing quantitative reports and dashboards.
Audit pilot data, models, and workflows for bias and inclusivity issues. Use when evaluating fairness across demographic groups, identifying algorithmic biases, and recommending mitigation strategies to ensure equitable outcomes.
Detect and alert on emerging anomalies and risk flags from pilot metrics and data streams. Use when monitoring live data, threshold breaches, or statistical outliers to trigger governance reviews and corrective actions.
Define measurable success metrics, KPIs, and acceptance criteria aligned to pilot objectives. Use when establishing evaluation frameworks, go/no‑go thresholds, or performance benchmarks based on pilot goals and baseline data.
Explore and analyze pilot data sets to uncover patterns, anomalies, and initial insights. Use when performing ad-hoc data investigations, validating data quality, or preparing exploratory visualizations for hypothesis generation.
Usage analytics, performance metrics, audit logging, and data export
Guidance for working with the experiment_data.py data object - hierarchical navigation, chat messages, sentiment analysis, and DataFrame exports
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
This skill should be used when the user asks to "review my week", "analyze my data", "what's working", "check progress", "weekly review", "monthly review", "look at my metrics", "show my trends", or wants to extract signal from tracked data and close the feedback loop.
A skill for analyzing data using Python (pandas) and generating professional visualizations (matplotlib/seaborn).
Pattern for aggregating insights across multiple tasks to enable data-driven evolution.
Coordinates data pipeline tasks (ETL, analytics, feature engineering). Use when implementing data ingestion, transformations, quality checks, or analytics. Applies data-quality-standard.md (95% minimum).