Data Science & ML Agent Skills

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.

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.

Statistical Results Interpretation

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

Statistical Power Analysis

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

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.

ML & AI Engineering Assistant

Accelerates the development of machine learning models and AI systems through expert guidance on MLOps, RAG architectures, and model deployment.

System Prompt Architect

Transforms high-level requirements into production-ready system prompts for complex single and multi-agent AI systems.

PolicyEngine Data Science

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

AgentDB Memory Patterns

Implements high-performance persistent memory and reinforcement learning patterns for AI agents using AgentDB and ReasoningBank.

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.

AnnData Scientific Data Management

Manages annotated data matrices for single-cell genomics and large-scale biological datasets using the Python AnnData framework.

Exploratory Data Analysis (EDA)

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

ReasoningBank Intelligence

Implements adaptive learning systems for AI agents to recognize patterns, optimize strategies, and improve autonomously over time.

Academic Peer Review

Provides rigorous, PhD-level evaluations of research manuscripts and proposals to enhance academic quality and impact.

Rerank - Search Result Optimization

Enhances search precision by applying cross-encoder models to re-order and refine initial vector search results.

Scientific Research Automation

Automates the end-to-end scientific research lifecycle from initial data analysis and hypothesis generation to the production of publication-ready LaTeX manuscripts.

MCP Vector Search Configuration Guide

Provides comprehensive technical guidance for configuring semantic document search and indexing via the Model Context Protocol.

Swarm Orchestration for Multi-Agent Systems

Orchestrates multi-agent swarms using advanced coordination patterns and dynamic topologies for complex, parallel task execution.

ReasoningBank with AgentDB

Implements high-performance adaptive learning and experience replay for self-improving AI agents using AgentDB.

ReasoningBank Intelligence

Empowers AI agents with adaptive learning and meta-cognitive capabilities to optimize strategies based on past experiences.

Soliton Detection & Agency Bridge

Unifies mathematical topology with computational agency to detect solitons and bootstrap self-aware agentic skills.

Analysis Orchestrator

Configures AI model selection, cost estimates, and batch processing strategies for qualitative research workflows.

Ordered Locale Point-Free Topology

Implements directed point-free topology using frames and preorders satisfying the open cone condition.

Flow Nexus Neural

Trains and deploys complex neural networks across distributed E2B sandbox environments using the Flow Nexus framework.