3. Data, Science & AI

Creates pre-registration documents to ensure research transparency, reproducibility, and compliance with open science standards before data collection or grant submissions.

Accurately interprets statistical results, effect sizes, and confidence intervals to ensure proper reporting and avoid common misinterpretations in data analysis.

Conducts sensitivity analyses to test robustness of findings under varying assumptions, missing data, and outliers in data analysis.

Calculates and interprets effect sizes to assess practical significance in research, meta-analysis, and statistical reporting.

Conducts statistical subgroup analyses to test moderators, explore heterogeneity, and identify differential effects in meta-analyses and research studies.

Detects AI-generated text patterns in research writing by analyzing grammar, structure, word frequency, and punctuation to ensure natural academic style.

Generates publication-quality data visualizations for research, exploratory analysis, and professional presentations.

Generates and edits images using Google's Gemini 3 Pro Image model for creative content, style transfer, and reference-based transformations.

Enables REPL-driven data visualization and literate programming for Clojure using Kindly conventions, supporting interactive data exploration.

Self-improving AI system that detects user feedback and tool failures to propose rule updates for enhanced performance.

Optimizes LangGraph applications through iterative prompt refinement based on evaluation criteria without altering graph structure.

Comprehensive guide for building AI agents with LangGraph, including architecture planning, workflow design, and advanced feature implementation.

Analyzes Excel files for data quality issues, format inconsistencies, and missing values, generating reports with cleaning recommendations and statistical summaries.

Creates interactive D3.js visualizations including bar, line, scatter, pie charts, and geographic maps for data representation.

Simulates particle systems with physics-based forces including gravity, wind, and turbulence for realistic or artistic motion and animation.

Automates SQL performance optimization by rewriting inefficient queries, creating and testing indexes, and reporting cost reductions with step-by-step measurements.

Generates test parameter bindings for SQL files by analyzing database schema and matching placeholders to column types, producing appropriate test values for IDs, dates, and enums.

Builds production-ready Dagster data pipelines with best practices, testing, and validation for data integration and workflow automation.

Expert guidance for implementing Dagster data orchestration patterns including assets, schedules, ETL workflows, and dbt/dlt integrations.

Creates and initializes a Dagster workspace for unified management of multiple data projects and pipelines.

Provides a comprehensive index of Dagster integrations organized by tags for discovering data engineering and AI tools.

AI-powered learning system utilizing pattern recognition and adaptive user preference modeling with correction feedback for personalized educational experiences.

Provides context management utilities for AI applications, including token estimation, message truncation, automatic compression, and summary generation.

Provides standardized best practices for designing system prompts in AI models, based on templated approaches from Crush.