Skill UI

A comprehensive guide for preparing replication and transparency packages for World Development manuscripts. It provides checklists and best practices for both quantitative (code reproducibility, data provenance, de-identification) and qualitative (evidence-to-claim trail, methods appendix) research. It addresses ethical constraints and the unique challenges of double-anonymized review.

This comprehensive guide provides authors with structured frameworks for assessing robustness and trustworthiness in World Development manuscripts. It guides users to organize checks by identifying specific threats (e.g., specification dependence, measurement error) in quantitative work, or demonstrating methodological rigor (e.g., triangulation, negative-case analysis) in qualitative work. It ensures findings are thoroughly vetted against alternative explanations.

Build features guided by data insights, A/B testing, and continuous measurement using specialized agents for analysis, implementation, and experimentation. This skill covers exploratory data analysis, hypothesis development, experiment design, feature architecture, analytics instrumentation, and implementation with integrated tracking and monitoring.

A guide to production-ready patterns for dbt (data build tool). It covers essential practices for robust data pipeline development, including model organization (staging, intermediate, marts), implementing advanced testing strategies, ensuring data quality, and optimizing incremental processing for large datasets.

A powerful toolset for automating core PostHog product analytics tasks via Rube MCP. It enables developers and analysts to capture user events, list and filter event data, manage feature flags (creation, retrieval, listing), and inspect user profiles. Ideal for integrating advanced product tracking and A/B testing workflows directly into development pipelines.