Anthropic Skills

Generates architecture, database, and system diagrams using Mermaid syntax. Creates visual representations of system architecture, database schemas, component relationships, and data flows.

JSON querying tools and patterns using DuckDB and jaq for data extraction and transformation. Load when querying JSON data or writing data pipelines.

Universal multi-perspective analyzer for any topic, file, idea, or decision. Extract key points, find gaps/risks, identify improvements with actionable plans.

Generate phase portraits for 2D dynamical systems. Use when visualizing vector fields, nullclines, and trajectories.

Guide for creating data visualizations in Shopify Apps using the Polaris Viz library. Use this skill when building charts, graphs, dashboards, or any data visualization components that need to integrate with the Shopify Admin aesthetic. Covers BarChart, LineChart, DonutChart, SparkLineChart, and theming.

Analyze OpenCode conversation history to identify themes and patterns in user messages. Use when asked to analyze conversations, find themes, review how a user steers agents, or extract insights from session history.

Create mermaid diagrams for blog posts using the blog's sky/zinc color theme. Use when adding flowcharts, sequence diagrams, or other mermaid visualizations to blog content.

Use the Mixpanel MCP server for analytics. Triggers on mentions of Mixpanel MCP tools, MCP resources, analytics queries via MCP, segmentation, funnels, retention, cohort_comparison, product_health_dashboard, ask_mixpanel, diagnose_metric_drop, guided_analysis, fetch_events, or SQL queries on local DuckDB data.

Generates professional infographics with 20 layout types and 17 visual styles. Analyzes content, recommends layout×style combinations, and generates publication-ready infographics. Use when user asks to create "infographic", "信息图", "visual summary", or "可视化".

Expert guidance for data analysis, visualization, and Jupyter Notebook development with pandas, matplotlib, seaborn, and numpy.

Guidelines for data analysis and Jupyter Notebook development with pandas, matplotlib, seaborn, and numpy.

Best practices for Matplotlib data visualization, plotting, and creating publication-quality figures in Python

Best practices for Pandas data manipulation, analysis, and DataFrame operations in Python

Implement analytics, data analysis, and visualization best practices using Python, Jupyter, and modern data tools.

Data analysis best practices with pandas, numpy, matplotlib, seaborn, and Jupyter notebooks.

Deep analysis of ClickHouse server logs, debug traces, and low-level diagnostics. Use for investigating server log messages and trace analysis.

Real-time monitoring of ClickHouse metrics, events, and asynchronous metrics. Use for load average, connections, queue monitoring, and resource saturation.

Diagnose ClickHouse RAM usage, OOM errors, memory pressure, and allocation patterns. Use for memory-related issues and out-of-memory errors.

Diagnose ClickHouse INSERT performance, batch sizing, part creation patterns, and ingestion bottlenecks. Use for slow inserts and data pipeline issues.

Diagnose ClickHouse disk usage, compression efficiency, part sizes, and storage bottlenecks. Use for disk space issues and slow IO.

Diagnose ClickHouse SELECT query performance, analyze query patterns, identify slow queries, and find optimization opportunities. Use for query latency and timeout issues.

Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug develo

Statistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and inference. Best for econometrics, time series, rigorous inference with coefficient tables. For guided statistical test selection with APA reporting use statistical-analysis.

Interactive visualization library. Use when you need hover info, zoom, pan, or web-embeddable charts. Best for dashboards, exploratory analysis, and presentations. For static publication figures use matplotlib or scientific-visualization.

Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between dat

Use this skill for processing and analyzing large tabular datasets (billions of rows) that exceed available RAM. Vaex excels at out-of-core DataFrame operations, lazy evaluation, fast aggregations, efficient visualization of big data, and machine learning on large datasets. Apply when users need to work with large CSV/HDF5/Arrow/Parquet files, perform fast statistics on massive datasets, create visualizations of big data, or build ML pipelines that do not fit in memory.

Meta-skill for publication-ready figures. Use when creating journal submission figures requiring multi-panel layouts, significance annotations, error bars, colorblind-safe palettes, and specific journal formatting (Nature, Science, Cell). Orchestrates matplotlib/seaborn/plotly with publication styles. For quick exploration use seaborn or plotly directly.

Unified markdown and OpenCode component specialist providing document quality enforcement (structure, style), content optimization for AI assistants, complete component creation workflows (skills, agents, commands with scaffolding, validation, packaging), ASCII flowchart creation for visualizing complex workflows, and install guide creation for MCP servers, plugins, and tools.

This skill should be used when running Phase 4 of the /ds workflow to review methodology, data quality, and statistical validity. Provides structured review checklists, confidence scoring, and issue identification for data analysis validation.

Data science and analytics expertise for statistical analysis, machine learning pipelines, data governance, business intelligence, predictive modeling, and analytics strategy. Use when building ML models, analyzing data, creating dashboards, or designing data architectures.

Design effective KPI dashboards with metrics selection, visualization best practices, and real-time monitoring patterns. Use when building business dashboards, selecting metrics, or designing data visualization layouts.

Create publication-quality architecture diagrams using Nano Banana Pro AI or Mermaid. Specialized in system architecture, C4 diagrams, data flow, sequence diagrams, and software design visualizations for project planning.

Build comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.

Master dbt (data build tool) for analytics engineering with model organization, testing, documentation, and incremental strategies. Use when building data transformations, creating data models, or implementing analytics engineering best practices.

R programming for data analysis, visualization, and statistical workflows. Use when working with R scripts (.R), Quarto documents (.qmd), RMarkdown (.Rmd), or R projects. Covers tidyverse workflows, ggplot2 visualizations, statistical analysis, epidemiological methods, and reproducible research practices.

Calculates technical mapping statistics for any aligned BAM file (ChIP or ATAC). It assesses the performance of the aligner itself by generating metrics on read depth, mapping quality, error rates, and read group data using samtools and Picard.Use this skill to check "how well the reads mapped" or to validate BAM formatting/sorting before further processing. Do NOT use this skill for biological signal validation (like checking for peaks or open chromatin) or for filtering/removing reads.

Weighted pandas DataFrames for survey microdata analysis - inequality, poverty, and distributional calculations

Create publication-quality data visualizations. Use when: (1) Presenting results, (2) Exploratory data analysis, (3) Manuscript preparation, (4) Grant proposals, (5) Presentations.

Calculate and interpret effect sizes for statistical analyses. Use when: (1) Reporting research results to show practical significance, (2) Meta-analysis to combine study results, (3) Grant writing to justify expected effects, (4) Interpreting published studies beyond p-values, (5) Sample size planning for power analysis.

Deep EDN template analyzer for Logseq database graphs. Analyzes template structure, counts classes/properties, finds orphaned items, checks quality, and compares variants. Use when analyzing template files, finding issues, or comparing different template versions.