Create or reuse Hugging Face dataset PRs for `harborframework/parity-experiments` and upload Harbor parity/oracle result folders efficiently with sparse checkout, raw git pushes, and Git LFS.
Correlation Analyzer - Auto-activating skill for Data Analytics. Triggers on: correlation analyzer, correlation analyzer Part of the Data Analytics skill category.
Create beautiful data visualizations with mathematical elegance, color theory, and narrative design - the "Data is Beautiful" aesthetic.
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.
Structured hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable hypotheses with predictions, propose mechanisms, and design experiments to test them. Follows scientific method framework. For open-ended ideation use scientific-brainstorming; for automated LLM-driven hypothesis testing on datasets use hypogenic.
MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differential equations, optimization, statistics, or creating scientific visualizations. Also use when the user needs help with MATLAB syntax, functions, or wants to convert between MATLAB and Python code. Scripts can be executed with MATLAB or the open-source GNU Octave interpreter.
Integrate statistical analysis results with biological knowledge from ToolUniverse tools. After computing associations or differential expression, use pathway analysis, literature search, drug-target databases, and variant annotation to interpret findings biologically. Use when statistical results need biological context, when users want to go beyond p-values to understand mechanisms, or when combining data analysis with literature evidence.
End-to-end epidemiological data analysis — from research question to statistical report. Covers study design assessment, dataset discovery and download, data wrangling, confounder adjustment, regression modeling, sensitivity analysis, visualization, and biological interpretation. Integrates ToolUniverse tools for dataset discovery, literature search, and biological context with Python code execution for data analysis. Use whenever users ask to analyze health data, study disease risk factors, assess exposure-outcome relationships, or conduct observational epidemiology. Also use when users want to run regression on clinical/survey data, calculate odds ratios or hazard ratios from a dataset, adjust for confounders, or produce a Table 1. If the task involves downloading a health dataset and running statistical analysis on it, this is the right skill.
Patterns for Databricks Vector Search: create endpoints and indexes, query with filters, manage embeddings. Use when building RAG applications, semantic search, or similarity matching. Covers both storage-optimized and standard endpoints.
Implement Series-style batch indicators with mathematical precision. Use for new StaticSeries implementations or optimization. Series results are the canonical reference—all other styles must match exactly. Focus on cross-cutting requirements and performance optimization decisions.
Generate formatted data reports from SQL query results
Minimalist UX/Interaction Audit Expert that deconstructs complex interactions through cognitive load and operational efficiency lenses. Use this skill when you need to perform a UX walkthrough audit on a Figma prototype or web interface, evaluating usability based on principles like fewer clicks, less UI elements, no hidden logic, and self-explanatory design.
Selects the appropriate quasi-experimental method (DiD, ITS, SC) based on data structure and research questions. Use when the user is unsure which method to apply.
Fits causal models, estimates impacts, and plots results using CausalPy. Use when performing analysis with DiD, ITS, SC, or RD.
Write a complete Numerai experiment report in experiment.md (abstract, methods, results tables, decisions, next steps) and generate/link the standard show_experiment plot(s). Use after running any Numerai research experiments, or when a user asks for a “full report”, “write up”, “experiment.md update”, or “generate the standard plot”.
Fits causal models, estimates impacts, and plots results using CausalPy. Use when performing analysis with DiD, ITS, SC, or RD.
Selects the appropriate quasi-experimental method (DiD, ITS, SC) based on data structure and research questions. Use when the user is unsure which method to apply.
Simple operations on user-provided text files including summarization.
Create charts and visualizations from note data using Chart.js via dataviewjs. Use when user wants bar charts, line graphs, pie charts, or any data visualization. Requires Obsidian Charts plugin.
Anomaly Detector - Auto-activating skill for Data Analytics. Triggers on: anomaly detector, anomaly detector Part of the Data Analytics skill category.
Automate budget vs actual variance analysis in Excel with flagging, commentary, and executive summaries for financial reporting and FP&A teams Activates when you request "excel variance analyzer" functionality.
Create cohort analysis creator operations. Auto-activating skill for Data Analytics. Triggers on: cohort analysis creator, cohort analysis creator Part of the Data Analytics skill category. Use when working with cohort analysis creator functionality. Trigger with phrases like "cohort analysis creator", "cohort creator", "cohort".
