ljg-qa

ljg-qa is a question-answer extraction skill that transforms articles, papers, and books into structured intellectual scaffolding. Instead of producing summaries or definitions, it extracts the author's core arguments as a chain of incisive questions paired with rigorous answers. Each question cuts to the heart of "why this solution works," "what tradeoffs exist," or "where it breaks down"—never settling for superficial "what is X" queries that readers skip.

The skill enforces a strict four-part answer structure: a one-sentence conclusion, a formalized relationship (using simple symbols like `A = B + C` or `old: X → new: Y` to visualize the idea), reasoning steps that show the logical chain, and explicit boundaries where the claim fails. This "thought geometry" lets readers reconstruct the author's entire reasoning path rather than passively receiving conclusions. Questions are sequenced by argumentative dependency, not document order, so each answer naturally leads to the next question.

Designed for readers who need to internalize complex reasoning—researchers analyzing papers, students engaging with dense texts, or professionals extracting actionable insights from technical content. It outputs to org-mode format with denote-compatible filenames in `~/Documents/notes/`. The skill explicitly rejects FAQ generation, glossary creation, or comprehension quizzes, focusing instead on building intellectual scaffolding that mirrors how the original author constructed their argument.