Anthropic Skills

Code exploration strategies for understanding unfamiliar codebases. Use when exploring unknown code, debugging, or analyzing architecture.

This skill should be used when the user asks to "/gobby metrics", "tool metrics", "usage stats", "performance report". View tool usage metrics, performance statistics, and identify failing tools.

Build, configure, and deploy Lightdash analytics projects. Create dbt models with metrics and dimensions, design charts and dashboards, and manage deployments using the Lightdash CLI.

Pragmatic qualitative analysis for interview data in sociology research. Guides you through systematic coding, interpretation, and synthesis with quality checkpoints. Supports theory-informed (Track A) or data-first (Track B) approaches.

Develop causal diagrams (DAGs) from social-science research questions and literature, then render publication-ready figures using Mermaid, R, or Python.

Deep research skill for systematic exploration. Auto-triggered for research, analysis, investigation tasks. Ensures data accuracy and research depth.

Postgres performance optimization and best practices from Supabase. Use this skill when writing, reviewing, or optimizing Postgres queries, schema designs, or database configurations. Triggers on tasks involving SQL queries, database schema design, indexes, connection pooling, RLS policies, or performance optimization.

Generate AntV Infographic syntax outputs. Use when asked to turn user content into the Infographic DSL (template selection, data structuring, theme), or to output `infographic <template>` plain syntax. The output can be embedded in markdown using ```infographic code blocks.

Basic exploratory data analysis for pandas DataFrames

Build production-grade interactive dashboards with Plotly Dash - enterprise features, callbacks, and scalable deployment

Conversational data analysis using natural language queries on DataFrames. Chat with your data using LLMs to generate insights, create visualizations, and explain code.

Automatic exploratory data analysis and visualization with a single line of code - generates comprehensive charts, detects patterns, and exports to HTML/notebooks

High-performance DataFrame library for fast data processing with lazy evaluation, parallel execution, and memory efficiency

Build interactive data applications and dashboards with pure Python - no frontend experience required

Automated data quality reports with comprehensive variable analysis, missing value detection, correlations, and HTML report generation - formerly pandas-profiling

Publication-quality tables in Python with rich styling, formatting, conditional formatting, and export to HTML/images - inspired by R's gt package

Automated EDA comparison reports with target analysis, feature comparison, and HTML report generation for pandas DataFrames

Extract extreme response values with linked statistics from OrcaFlex

R statistical analysis for publication-ready sociology research. Guides you through phased workflows for DiD, IV, matching, panel methods, and more. Use when doing quantitative analysis in R for academic papers.

Computational text analysis for sociology research using R or Python. Guides you through topic models, sentiment analysis, classification, and embeddings with systematic validation. Supports both traditional (LDA, STM) and neural (BERT, BERTopic) methods.

Stata statistical analysis for publication-ready sociology research. Guides you through phased workflows for DiD, IV, matching, panel methods, and more. Use when doing quantitative analysis in Stata for academic papers.

Post-process OrcaFlex simulation results using OPP (OrcaFlex Post-Process).

Use this skill when the user asks to "create corner plots", "visualize posteriors", "plot chains", "analyze nested sampling output", "plot marginal distributions", "compare prior and posterior", "make triangle plots", or work with posterior samples from PolyChord, MultiNest, UltraNest, Cobaya, or other Bayesian inference tools. Provides complete guidance for creating publication-quality posterior visualizations from nested sampling or MCMC chains.

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

Database expert for query optimization, indexing, schema design, and performance tuning

Python fundamentals, data structures, OOP, and data science libraries (Pandas, NumPy). Use when writing Python code, data manipulation, or algorithm implementation.

ARIMA, SARIMA, Prophet, trend analysis, seasonality detection, anomaly detection, and forecasting methods. Use for time-based predictions, demand forecasting, or temporal pattern analysis.

Product analytics and growth expert. Use when designing event tracking, defining metrics, running A/B tests, or analyzing retention. Covers AARRR framework, funnel analysis, cohort analysis, and experimentation.

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Execute clustering algorithms (K-means, DBSCAN, hierarchical) to identify

Collect comprehensive infrastructure performance metrics across compute, storage, network, containers, load balancers, and databases. Use when monitoring system performance or troubleshooting infrastructure issues. Trigger with phrases like "collect infrastructure metrics", "monitor server performance", or "track system resources".

Automatically detect performance regressions in CI/CD pipelines by comparing metrics against baselines. Use when validating builds or analyzing performance trends. Trigger with phrases like "detect performance regression", "compare performance metrics", or "analyze performance degradation".

Analyze application logs for performance insights and issue detection including slow requests, error patterns, and resource usage. Use when troubleshooting performance issues or debugging errors. Trigger with phrases like "analyze logs", "find slow requests", or "detect error patterns".

Generate plots, charts, and graphs from data with automatic visualization

Build comprehensive 3-5 year financial models projecting revenue, expenses, headcount, cash flow, and runway. Model unit economics, scenario planning, and path to profitability. Generate investor-ready HTML reports with detailed projections and charts.

Aggregate and centralize performance metrics from applications, systems, databases, caches, and services. Use when consolidating monitoring data from multiple sources. Trigger with phrases like "aggregate metrics", "centralize monitoring", or "collect performance data".

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Expert in technical adjustment grid construction for comparable sales analysis including adjustment hierarchy, quantification methods (paired sales, regression, cost, income), and validation techniques. Use when constructing detailed comparable sales grids, quantifying specific adjustments, applying statistical validation, or reconciling adjusted sale prices. Key terms include adjustment grid, paired sales analysis, hedonic regression, gross adjustment limits, net adjustment, sensitivity analysi

dbt (data build tool) patterns for data transformation and analytics engineering. Use when building data models, implementing data quality tests, or managing data transformation pipelines.

Visualize subagent task dependencies using ASCII diagrams before launching agents and create comprehensive HTML summaries after completion.