Skill UI

Structured manuscript and grant review guidance that walks reviewers through methodology, statistics, reporting compliance, and constructive feedback for rigorous scientific evaluation across disciplines.

Analyzes comprehensive fitness logs to track quantitative trends in volume, intensity, and frequency. It tracks progress across multiple disciplines (running, strength) and correlates exercise metrics with vital health indicators like blood pressure and weight, providing personalized, science-backed training and recovery advice.

This technique guides users on how to construct highly specific search queries for academic papers. Instead of relying solely on broad topic keywords, users should prioritize combining concrete numerical identifiers—such as exact sample sizes, population percentages, concentration levels, or specific year ranges—with methodological terms and discipline keywords. Using these numerical anchors significantly increases the uniqueness and precision of the search results, helping to pinpoint the exact study required.

A powerful skill for searching and retrieving comprehensive academic metadata using the OpenAlex API. It provides a unified view of research papers, including full open citation graphs, detailed institutional affiliations, and crucial funding information (e.g., NSF, NIH). Ideal for deep academic research, comparative literature reviews, and identifying research trends across multiple disciplines.

A comprehensive guide covering the canonical rules for Power BI report design. It enforces consistency across design identity, visual hierarchy, color discipline, chart selection, and accessibility. Focuses on structuring reports to answer specific questions and minimizing cognitive load, ensuring data effectiveness over mere aesthetics.

This guide details the rigorous data analysis and reporting standards required for top-tier academic journals, such as AJPS. It focuses intensely on reproducibility, ensuring that all results—from primary findings to exploratory models—are generated by a single, seeded master script. Key requirements include reporting uncertainty intervals, proving robustness, adhering to pre-registration discipline, and accommodating mandatory third-party code verification. Use this when conducting complex empirical research in social sciences or political science, needing to withstand intensive methodolo...

This guide provides comprehensive guidelines for selecting, validating, and defending rigorous research designs for Contemporary Accounting Research (CAR) manuscripts. It covers various approaches—including panel archival, controlled experiments, analytical models, field studies, and surveys—while stressing critical rigor checks like identification strategy, internal validity, and model discipline. It also mandates adherence to ethical review processes and data integrity policies.

This guide outlines the rigorous academic requirements for submissions to the China Sport Science journal. It covers both natural sciences (physiology, biomechanics, exercise medicine) and social sciences (sports sociology, policy, management). Submissions must address core sport science ontology problems with high methodological rigor, ensuring the contribution is central to the field, rather than merely applying other disciplines.

This guide assists researchers in structuring and rigorously developing the economic model or mechanism for academic papers. It provides best practices for moving beyond mere empirical findings, ensuring that every result is tied to a clear, testable economic theory, whether through minimal-model discipline or full general equilibrium analysis. Essential for submissions to top-tier economics journals.

A comprehensive guide on structuring empirical research papers for top-tier conferences, such as FSE. It outlines strict partitioning rules, ensuring that all decision-critical evidence, core arguments, and key findings reside within the primary reviewed body, while supplementary artifacts and appendices provide necessary, but non-judgmental, support. Covers page budget discipline, double-anonymity requirements, and optimizing the paper's flow.

This guide provides expert advice on balancing rigorous theoretical modeling (like DSGE) with empirical data in international macroeconomics. It teaches authors how to appropriately "right-size" theoretical components, ensuring the model is disciplined by data and delivers policy-relevant counterfactuals, which is crucial for publication in top journals like IMFER.

A comprehensive methodological guide for conducting rigorous quantitative research in finance, covering asset pricing, corporate finance, and econometrics. This skill defines the necessary standards for factor construction, portfolio sorting, advanced estimators (Fama-MacBeth, GMM), robust standard error clustering, and multiple-testing discipline. It ensures research designs are academically sound, reproducible, and suitable for top-tier financial journals.