moai-lang-r
R 4.4+ development specialist covering tidyverse, ggplot2, Shiny, and data science patterns. Use when developing data analysis pipelines, visualizations, or Shiny applications.
R 4.4+ development specialist covering tidyverse, ggplot2, Shiny, and data science patterns. Use when developing data analysis pipelines, visualizations, or Shiny applications.
Complete USGS gauge data integration workflow from spatial discovery to model validation. Handles gauge finding, data retrieval, matching to HEC-RAS features, boundary condition generation, initial conditions, real-time monitoring, and validation metrics (NSE, KGE). Use when working with USGS data, NWIS gauges, generating boundaries from observed flow, calibrating models, validating with observed data, or setting up operational forecasting.
Reads HEC-DSS files (V6 and V7) for boundary condition extraction using RasDss class. Handles JVM configuration, HEC Monolith download, catalog reading, and time series extraction. Use when working with DSS files, extracting boundary data, reading HEC-HMS output, or integrating DSS workflows. Triggers: DSS, HEC-DSS, boundary condition, time series, JVM, Java, catalog, pathname, HEC-HMS, Monolith, pyjnius, read DSS, extract DSS, DSS boundary.
Extract HEC-RAS hydraulic results from HDF files including water surface elevations (WSE), depths, velocities, and flows for both steady and unsteady simulations. Handles cross section time series, 2D mesh results, maximum envelopes, and dam breach results. Use when you need to extract, analyze, or post-process HEC-RAS simulation outputs, retrieve water levels, query velocity fields, get depth grids, extract flow data, analyze breach hydrographs, or pull hydraulic variables from .hdf result files.
Analyze spatial variability of NOAA Atlas 14 precipitation frequency estimates within HEC-RAS model domains using intelligent extent-based downloading. Helps determine whether uniform rainfall assumptions are appropriate for rain-on-grid modeling by calculating min/max/mean/range statistics within 2D flow areas or project extents. Uses NOAA CONUS NetCDF with HTTP byte-range requests for 99.9% data reduction compared to traditional state-level ZIP downloads. Primary sources: - ras_commander/precip/CLAUDE.md (lines 118-629) - Complete workflows - ras_commander/precip/Atlas14Grid.py - API reference - ras_commander/precip/Atlas14Variance.py - Variance analysis API - examples/725_atlas14_spatial_variance.ipynb - Working demonstration
This skill provides guidance for counting tokens in datasets using specific tokenizers. It should be used when tasks involve tokenizing dataset content, filtering data by domain or category, and aggregating token counts. Common triggers include requests to count tokens in HuggingFace datasets, filter datasets by specific fields, or use particular tokenizers (e.g., Qwen, DeepSeek, GPT).
Guidance for analyzing log files and generating summary reports with counts aggregated across multiple date ranges and severity levels. This skill applies when tasks involve parsing log files by date, counting occurrences by severity (ERROR, WARNING, INFO), and outputting structured CSV summaries across time periods like "today", "last 7 days", or "last 30 days".
KPI framework setup, dashboard design, cohort analysis, and data-driven decision making. Use when analyzing growth metrics, building KPI dashboards, or implementing analytics systems.
Monitor injury news across leagues. Fantasy impact analysis, backup player analysis, return timeline estimates.
Side-by-side stat comparisons with context. Adjust for era, pace of play, league differences. Advanced metrics explained in plain English.
Expert data analyst specializing in business intelligence, data visualization, and statistical analysis. Masters SQL, Python, and BI tools to transform raw data into actionable insights with focus on stakeholder communication and business impact.
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.
Generate HTML analytics dashboard for routing statistics
Learn how to visualize data in a sustainable, accurate, and theme aware way.
Generate data visualizations, plots, and charts. Analyzes data structure to select optimal visualization types. supports bar charts, line graphs, and scatter plots for clarity.
Creates and edits Excel spreadsheets with formulas, formatting, and financial modeling standards. Use when working with .xlsx files, financial models, data analysis, or formula-heavy spreadsheets. Covers formula recalculation, color coding standards, and common pitfalls.
Python best practices, FastAPI, Pandas ve veri bilimi kütüphaneleri kullanımı.
Statistical modeling toolkit. OLS, GLM, logistic, ARIMA, time series, hypothesis tests, diagnostics, AIC/BIC, for rigorous statistical inference and econometric analysis.
Automate comprehensive market research using web data, competitive analysis, and structured synthesis. Use when researching markets, industries, competitors, or target audiences.