scientific-visualization
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.
chicago-data-portal
This skill should be used when the user asks to "query Chicago data", "find Chicago datasets", "get Chicago crime data", "download Chicago permits", "write a SODA query for Chicago", "search data.cityofchicago.org", or mentions Chicago city data (311, permits, licenses, inspections, crimes, etc.).
civitai-analyst
Generate and execute SQL queries against the civitai_records PostgreSQL database to analyze video performance on Civitai. Use when users ask about: video engagement metrics (likes, hearts, comments), content performance analysis, tag/theme analysis, quality scores, weekly reports, comparing videos, content recommendations, trend analysis, or any Civitai data queries. Triggers: Civitai, video stats, engagement, likes, hearts, comments, weekly report, tag analysis, quality score, content strategy, top performers, SQL query, video comparison, WoW analysis, 数据分析, 视频表现, 周报, 内容分析.
data-analysis-repl
Execute code to analyze data and perform complex calculations.
arcgis-custom-rendering
Create custom layer types with WebGL rendering, custom tile layers, and blend layers. Use for advanced visualizations and custom data sources.
uniform-connectedness
Elementos conectados visualmente se perciben como relacionados. Use cuando diseñe diagramas, flujos, relaciones entre elementos, o conexiones visuales.
d3-layouts-hierarchies
Use when creating tree diagrams, force-directed networks, Voronoi diagrams, or hierarchical layouts. Invoke for org charts, node-link diagrams, treemaps, dendrograms, force simulations, spatial indexing, or network visualizations.
dask
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
python-dataviz
This skill should be used when the user asks to "create a plot", "make a chart", "visualize data", "create a heatmap", "make a scatter plot", "plot time series", "create publication figures", "customize plot styling", "use matplotlib", "use seaborn", or needs guidance on Python data visualization, statistical graphics, or figure export.
data-analytics-foundations
Core data analytics concepts, Excel/Google Sheets fundamentals, and data collection techniques
cook-county-data-portal
This skill should be used when the user asks to "query Cook County data", "find Cook County datasets", "get property assessments", "download parcel data", "search datacatalog.cookcountyil.gov", "get medical examiner data", "find court cases", "query State's Attorney data", or mentions Cook County government data (assessor, treasurer, courts, payroll, medical examiner, etc.).
data-visualization
Master data visualization principles including chart selection, dashboard design, color theory, and data storytelling
tableau-expert
Expert-level Tableau Desktop/Server, calculated fields, LOD expressions, dashboards, data blending, and performance optimization
subquery-patterns-and-union
Use OPAL subquery syntax (@labels) and union operations to combine multiple datasets or time periods. Essential for period-over-period comparisons, multi-dataset analysis, and complex data transformations. Covers @label <- @ syntax, timeshift for temporal shifts, union for combining results, and any_not_null() for collapsing grouped data.
shap
Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model.
arcgis-visualization
Style and render geographic data with renderers, symbols, and visual variables. Use for creating thematic maps, heatmaps, class breaks, unique values, labels, and 3D visualization.
data-visualization-expert
专业数据可视化专家，精通现代图表库、仪表板设计和交互式数据展示。能够将复杂数据转化为直观、美观且富有洞察力的可视化作品。
datacommons-client
Work with Data Commons, a platform providing programmatic access to public statistical data from global sources. Use this skill when working with demographic data, economic indicators, health statistics, environmental data, or any public datasets available through Data Commons. Applicable for querying population statistics, GDP figures, unemployment rates, disease prevalence, geographic entity resolution, and exploring relationships between statistical entities.
extracting-dss-results
Extracts and analyzes HEC-HMS simulation results from DSS files using HmsDss and HmsResults classes. Handles peak flows, hydrographs, volume summaries, and time series data. Leverages ras-commander's RasDss for DSS V6/V7 support. Use when processing HMS results, extracting peak flows, analyzing hydrographs, computing volumes, or exporting time series. Integrates with HEC-RAS for boundary condition workflows. Trigger keywords: DSS file, results, peak flow, hydrograph, time series, volume, extract results, HMS output, analyze results.
