Data Science & ML Agent Skills

Sensitivity Analysis

Evaluates the robustness of research findings by testing how results change under different analytical assumptions and data conditions.

Research Randomization Logic

Implements rigorous randomization procedures for experimental research and unbiased participant allocation.

Databricks Model Serving

Deploys and manages production-grade machine learning models on Databricks with support for A/B testing and auto-scaling.

RDKit Cheminformatics Toolkit

Performs advanced molecular analysis, descriptor calculation, and chemical informatics using the RDKit library.

Experiment Design & Research Rigor

Facilitates the creation of methodologically sound research studies following NIH rigor standards and experimental best practices.

Publication Prep Research Assistant

Prepares submission-ready research manuscripts by automating formatting, reporting guideline compliance, and journal selection workflows.

Meta-Analysis Research Assistant

Conducts quantitative synthesis of research data by pooling effect sizes across multiple studies to derive summary conclusions.

Hypothesis Testing Guide

Guides the selection, assumption checking, and interpretation of statistical hypothesis tests for rigorous research data analysis.

Memory Manager for elizaOS

Optimizes AI agent memory usage and manages conversation context through advanced pruning and archiving strategies.

Inclusion Criteria for Research

Applies systematic inclusion and exclusion criteria to automate literature screening and ensure PRISMA compliance.

Research Question Optimizer

Formulates and refines high-quality research questions using the scientifically recognized FINER criteria.

Topological Gesture & Hypergesture Modeler

Models continuous performance curves and high-order musical gestures using topological category theory and Mazzola's Diamond Conjecture.

Statistical Power Analysis

Calculates statistical power and determines required sample sizes for research studies to ensure experimental rigor and reproducibility.

Statistical Results Interpretation

Interprets and reports complex statistical findings with high precision, focusing on effect sizes, confidence intervals, and p-value accuracy.

PolicyEngine US Tax & Benefit Simulation

Models US federal and state tax and benefit systems to perform complex microsimulations and fiscal policy impact analysis.

Gemini Prompt Engineering

Optimizes AI workflows by providing expert guidance and implementation patterns for Google Gemini models.

PolicyEngine Core Microsimulation

Powers tax and benefit microsimulations with a vectorized engine for calculating complex economic policy impacts.

Data Cleaning & Quality Remediation

Performs systematic data quality remediation by detecting duplicates, handling outliers, and standardizing datasets for reliable analysis.

Flow Nexus Neural

Trains and deploys complex neural networks across distributed E2B sandbox environments directly within Claude.

Grok Prompt Engineering

Provides specialized guidance for crafting high-performance prompts for xAI's Grok model using real-time knowledge and conversational styles.

PolicyEngine Data Science

Analyzes survey microdata using weighted pandas DataFrames to calculate inequality, poverty, and distributional metrics.

Guided Investigation Framework

Conducts systematic, multi-phase investigations into complex, open-ended data questions using structured decomposition and incremental synthesis.

Comparative Data Analysis

Performs rigorous, systematic comparisons of data segments, cohorts, and time periods to uncover actionable drivers of difference.

AgentDB Memory Patterns

Manages persistent memory and pattern learning for AI agents using high-performance vector storage and context synthesis.

Parameter-Dependent Systems Analysis

Analyzes and models dynamical systems that vary with external parameters to understand qualitative shifts and stability.

Exploratory Data Analysis (EDA)

Conducts systematic exploratory data analysis to uncover hidden patterns, anomalies, and actionable insights in unfamiliar datasets.

RAG Research & Semantic Search

Optimizes document retrieval and semantic search workflows using RAG best practices, vector databases, and advanced chunking strategies.

Topological Obstruction Learning

Identifies and resolves global consistency obstructions in topological AI systems using Čech cohomology and GF(3) balancing.

Entropy Sequencer

Optimizes interaction sequences using information theory to maximize learning efficiency and minimize surprise.

Epistemic Arbitrage

Exploits knowledge differentials across domains using propagator-based networks and deterministic parallel synthesis.