Skill UI

This guide helps researchers determine if their academic idea constitutes a genuine theoretical problem suitable for a specialized theory journal, rather than an empirical study or a simple literature review. It screens for conceptual advances, teaching users to distinguish between mere topics, data-driven findings, and deep theoretical gaps. Use this when you have an intuition or critique but are unsure of the theoretical depth or appropriate academic venue.

This skill helps users determine which marketing efforts truly drive conversions and revenue. It covers interpreting various attribution models (First-touch, Last-touch, Data-driven) and reconciling conflicting data reported by multiple marketing tools. It also guides users on implementing first-party, self-hosted attribution tracking when they own the site or app.

An autonomous system designed to continuously improve code quality by scanning codebase metrics. It functions as an agent, proposing mechanical code changes, executing them, and committing only if defined metrics improve. It supports multiple modes (Scan, Scaffold, Run) for systematic, data-driven codebase refactoring.