What problem does it solve? Turning research hypotheses into rigorous, publication-ready academic arguments is slow and error-prone: claims often lack evidence chains, introductions miss the research-gap narrative, and IMRaD sections leak content across boundaries. This Skill converts hypotheses and extracted evidence into structured argument chains and paper section drafts with built-in quality gates. ## Core Features & Use Cases - Toulmin Argument Chains: Builds complete six-element arguments (claim, data, warrant, backing, qualifier, rebuttal) for each core hypothesis, with strict rules against fabricated evidence. - CARS Introduction Drafting: Generates introductions following Swales' Create-a-Research-Space three-move model, plus Hyland discipline-appropriate rhetoric strategies. - IMRaD Validation & Quality Gates: Checks section structure integrity, classifies citation functions (support/contrast/gap/method), and applies a six-axis literature review quality score with anti-inflation rules. - Use Case: Given two hypotheses about eye-tracking biomarkers for ADHD plus supporting papers, produce an arguments.json with full Toulmin structures, a CARS-based introduction draft, and an IMRaD validation report flagging any cross-section content violations. ## Quick Start Ask the agent to expand your hypotheses and extracted evidence into a structured academic argument with Toulmin chains, a CARS introduction draft, and an IMRaD validation report.
