Skill UI

This tool assists researchers in structuring and drafting the critical cover letter for submissions to Physical Review Letters (PRL). The primary goal is to create a concise, editor-facing narrative that explicitly justifies the work's 'importance + broad-interest' criteria, convincing editors of its cross-disciplinary impact.

This skill guides researchers through the rigorous process of determining if a scientific finding meets the 'Importance' and 'Broad Interest' criteria required for top-tier physics journals, such as Physical Review Letters (PRL). It diagnoses venue fit, helping authors frame their work to maximize visibility and impact, without altering the core scientific result. Useful for optimizing manuscript submissions and developing a clear narrative for non-specialist audiences.

This skill helps authors determine the suitability of their research paper (analytical, empirical, or behavioral) for prestigious Operations Management journals like Production and Operations Management (POM). It provides detailed guidance on required scope, methodological rigor (e.g., identification strategies, model assumptions), structural requirements, and common pitfalls to ensure maximum publication potential.

This skill guides the creation of standard, high-quality exhibits for meta-analysis manuscripts, specifically adhering to APA 7th edition standards required by journals like Psychological Bulletin. It generates critical figures such as PRISMA flow diagrams, forest plots, funnel plots, and summary tables, ensuring the final report is self-contained, reproducible, and scientifically rigorous.

A comprehensive guide for academic authors adopting open science standards, based on TOP Guidelines. It outlines best practices for ensuring research reproducibility, covering data citation, data provenance documentation, data sharing via repositories (Dataverse/QDR), and managing restricted-data paths for various evidence types.

This guide helps authors polish the prose, abstract, and introduction of quantitative economics manuscripts for a general-interest Econometric Society readership. It emphasizes structuring the paper to clearly present both a substantive economic question and a quantitative method. It adheres to QE house rules, requiring findings to be communicated through point estimates with standard errors and confidence sets, rather than relying on statistical asterisks.

This tool guides researchers through pressure-testing their economic research ideas against the standards of top-tier, general-interest journals (like QJE). It helps diagnose whether a study's 'big idea' and broad implications are compelling enough, ensuring the focus is on the general lesson rather than just the technical method or narrow finding. Ideal for structuring academic arguments and improving manuscript scope.

This skill polishes scholarly prose, abstracts, and introductions to align with the narrative-driven, ambitious style of the Quarterly Journal of Economics (QJE). It focuses on making the core research contribution immediately legible to a general-interest, non-specialist reader, ensuring the big idea lands fast, even in long-form empirical papers. The skill guides users on structuring the 'introduction arc,' stating findings with concrete numbers, and minimizing technical jargon.

This skill provides a comprehensive framework for assessing whether an economics manuscript is suitable for the Quarterly Journal of Economics (QJE). It guides authors through evaluating the research scope (must be general-interest), evidence quality (requires clean natural experiments or quasi-experimental designs), narrative structure (leading with consequential findings), and adherence to rigorous academic submission standards.

This guide outlines the comprehensive steps required to convert an accepted, anonymous academic paper into its final, published 'camera-ready' version for major conferences (e.g., RecSys). It covers crucial tasks such as restoring author details, affiliations, funding, integrating rebuttal promises, ensuring proper ACM two-column reflow, and managing public code/data repository release.

This comprehensive guide details advanced econometric methodologies required for rigorous causal inference studies. It covers how to defend both the causal identification strategy (DiD, RD, IV) and the quality of variables (handling measurement error, index construction). Learn to meet the stringent standards of top-tier journals by applying techniques like staggered DiD estimators, density testing, and attenuation correction.

This guide helps researchers precisely define the marginal contribution (the 'delta') of their academic work. Instead of writing a general literature tour, it instructs authors to compare their findings directly against 3-5 most proximate prior papers, emphasizing specific advancements in identification or measurement. It is crucial for submissions to high-stakes journals.