Skill UI

A comprehensive guide for authors submitting technical papers, detailing methods to ensure that all reported claims, figures, and benchmark numbers can be independently regenerated. This involves creating VM-ready, self-contained artifacts, mapping every claim to a specific script, and defining clear reproducibility levels (Turnkey, Scripted) to satisfy conference requirements.

A comprehensive methodological guide for designing rigorous academic studies in accounting. It details advanced econometric techniques—including Difference-in-Differences (DiD), Instrumental Variables (IV), Regression Discontinuity Design (RDD), and experimental setups—to establish credible causal identification. Use this guide when your research challenge is solving endogeneity or isolating a specific economic channel from complex, non-random variables.

This guide helps scholars rigorously defend the methodological design of academic papers, particularly in International Relations and Comparative Politics. It covers advanced techniques such as process tracing, case selection logic, quantitative cross-national panel data analysis (DID, IV, RDD), and experimental design. Its core purpose is to strengthen causal claims by explicitly addressing selection bias, defining scope conditions, and ruling out major rival explanations.

This guide provides a structured framework for presenting complex empirical results in academic manuscripts, particularly for international marketing journals. It details the essential 'spine exhibits' (conceptual models, invariance tables, cross-national patterns) and teaches techniques like the 'claim test' and 'triage' to ensure arguments are clear, rigorous, and adhere to strict page limits.

Provides a comprehensive, step-by-step workflow for conducting rigorous literature reviews across academic, biomedical, and technical domains. It guides users through defining research questions (PICO), developing systematic search protocols, evidence logging, source screening, structured data extraction, and synthesizing findings to build high-quality, reproducible review reports.

This core skill is designed for academic publishing, combining deep AI research with structured, professional writing. It guides the creation of manuscripts using IMRAD structure and handles complex citation styles (APA, AMA, etc.). Crucially, it mandates the generation of graphical abstracts and rich technical schematics to ensure the highest level of visual rigor for research papers.