skill-name
What this skill does. Use when user mentions "keyword1", "keyword2", or "keyword3". Keep under 1,024 characters and include specific trigger keywords.
What this skill does. Use when user mentions "keyword1", "keyword2", or "keyword3". Keep under 1,024 characters and include specific trigger keywords.
Generate images using Nano Banana Pro (Gemini 3 Pro Preview). Use when creating app icons, logos, UI graphics, marketing banners, social media images, illustrations, diagrams, or any visual assets. Triggers include phrases like 'generate an image', 'create a graphic', 'make an icon', 'design a logo', 'create a banner', or any request needing visual content.
Create D3.js charts and interactive data visualizations. Use when building bar charts, line charts, scatter plots, pie charts, force-directed graphs, geographic maps, or any custom data visualization.
Generate and edit images using Google's Gemini API (gemini-3-pro-image-preview model). Use when users request (1) Generating images from text prompts, (2) Editing existing images with AI instructions, (3) Creating images with specific styles or templates, (4) Generating multiple variations of images, (5) Creating images with reference images for style consistency, (6) Any image generation task mentioning Gemini, Google AI, or requiring professional image output. Supports aspect ratios (1:1, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9), 7 style templates (3 glass styles, 4 other creative styles), reference images (up to 14), and batch processing.
Generate images using Gemini 3 Pro Image (Nano Banana Pro). Use this skill when the user asks to create, generate, or make an image, picture, illustration, artwork, mockup, or visual. Also use for image editing, transformation, or style transfer when a reference image is provided.
Use when analyzing, researching, investigating, exploring, auditing code, reviewing architecture, planning implementation, or when prompt contains Russian words like проанализировать, исследовать, изучить, составить план, провести аудит, выявить проблемы - routes to appropriate superpowers workflow
PolicyEngine aggregation patterns - using adds attribute and add() function for summing variables across entities
Probability, distributions, hypothesis testing, and statistical inference. Use for A/B testing, experimental design, or statistical validation.
Guide selection and interpretation of statistical hypothesis tests. Use when: (1) Choosing appropriate test for research data, (2) Checking assumptions before analysis, (3) Interpreting test results correctly, (4) Reporting statistical findings, (5) Troubleshooting assumption violations.
Create evidence synthesis matrices for systematic reviews. Use when: (1) Organizing extracted data, (2) Comparing study characteristics, (3) Identifying patterns across studies, (4) Preparing synthesis for manuscripts.
Conduct subgroup analyses to examine effect moderation. Use when: (1) Testing pre-specified moderators, (2) Exploring heterogeneity, (3) Identifying differential effects, (4) Meta-analysis synthesis.
Interpret statistical results correctly and comprehensively. Use when: (1) Writing results sections, (2) Discussing findings, (3) Avoiding common misinterpretations, (4) Reporting effect sizes and confidence intervals.
Analyze policy impacts for congressional districts and representatives' constituents. Use when the user mentions a specific district (NY-17, CA-52), a representative's name, or asks about geographic policy impacts at district level. Provides HuggingFace district datasets.
Conduct sensitivity analyses to test robustness of findings. Use when: (1) Testing assumption violations, (2) Meta-analysis robustness, (3) Handling missing data, (4) Examining outliers.
Create publication-quality data visualizations. Use when: (1) Presenting results, (2) Exploratory data analysis, (3) Manuscript preparation, (4) Grant proposals, (5) Presentations.
Generate plots, charts, and graphs from data with automatic visualization type selection. Use when requesting "visualization", "plot", "chart", or "graph".
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.
Identify anomalies and outliers in datasets using machine learning algorithms. Use when analyzing data for unusual patterns, outliers, or unexpected deviations from normal behavior. Trigger with phrases like "detect anomalies", "find outliers", or "identify unusual patterns".
Conduct quantitative synthesis through meta-analysis. Use when: (1) Combining effect sizes across studies, (2) Systematic review synthesis, (3) Calculating summary effects, (4) Assessing heterogeneity.
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.
Python fundamentals, data structures, OOP, and data science libraries (Pandas, NumPy). Use when writing Python code, data manipulation, or algorithm implementation.
Generate a comprehensive community health report from synced Discord messages
Use when you need to archive historical database records to reduce primary database size. This skill automates moving old data to archive tables or cold storage (S3, Azure Blob, GCS). Trigger with phrases like "archive old database records", "implement data retention policy", "move historical data to cold storage", or "reduce database size with archival".