Skill UI

This skill provides a structured workflow for developing and modifying content management systems (CMS), applicable to platforms like WordPress, Shopify, and Drupal. It covers crucial architectural seams, including theme and template design, plugin/module development, content modeling, media asset pipelines, and static export processes, ensuring changes maintain structural integrity.

A comprehensive guide to establishing credible causal identification strategies for economic empirical research. It covers advanced quasi-experimental methods such as Difference-in-Differences (DID), Instrumental Variables (IV), and Regression Discontinuity (RDD), alongside structural modeling. The core principle emphasizes the necessity of explicitly stating, empirically defending, and testing all identification assumptions to meet the rigorous standards of top-tier academic economics journals.

This guide helps users transform weak research ideas, correlations, or policy descriptions into strong, internationally generalizable, and causally identifiable research questions suitable for top-tier academic journals. It emphasizes establishing exogenous variation, clear underlying mechanisms, and structural modeling potential to elevate research quality.

This guide provides rigorous methodological standards for authors submitting economic papers to the China Economic Quarterly (CEQ). It emphasizes aligning research with international top-field standards, requiring clean causal identification, structural modeling, and advanced econometric techniques (e.g., modern DID, IV, RDD). Use this to strengthen your paper's technical rigor and ensure its contribution is methodologically sound for top-tier Chinese journals.

This detailed guide helps authors assess the scientific rigor and scope fit for manuscripts targeting Composites Part B: Engineering. It covers advanced domains like composite mechanics, manufacturing processes, multiscale modeling, and multifunctional materials. It emphasizes that a strong contribution must demonstrate a clear, mechanism-driven advance from material science to structural application, supported by rigorous, quantitative experimental evidence and model validation.

This skill is a comprehensive guide for authors targeting top-tier academic journals, such as Econometrica. It provides a rigorous checklist covering the required depth of econometric theory, the novelty of identification results, structural modeling requirements, and the necessary formal structure (proofs, asymptotics, supplementary materials). Use this tool to re-frame and vet manuscripts against the highest academic standards.

A comprehensive guide detailing advanced econometric methods for establishing causal relationships in policy evaluations. It covers techniques such as Difference-in-Differences (DID), Instrumental Variables (IV), Regression Discontinuity Design (RDD), and structural modeling. The core focus is bridging the gap between econometric rigor and policy legibility, ensuring that the causal mechanism is explicit in the main text while maintaining formal defense in the appendix.

A comprehensive guide for economists on refining theoretical models and structures for publication in high-impact journals. It provides rigorous best practices for developing pure economic theory, executing structural quantitative modeling, and ensuring models effectively interpret empirical estimates, focusing on generalizability and interpretability.

This skill provides a comprehensive fit and structural review tool for manuscripts targeting 'Field Crops Research.' It assesses whether an agronomy or crop-physiology paper meets the journal's high standard: rigorous, adequately replicated, multi-environment field experimentation. It guides authors on key topics like resource-use efficiency, crop modeling validation, and required methodological depth (e.g., mixed models, full metadata reporting).

A comprehensive guide for executing and reporting robust statistical analyses for manuscripts in Global Change Biology (GCB). This skill ensures the analysis meets the high standards of reproducibility required for publicly archived data (DOI). It covers advanced methods including mixed/hierarchical modeling, time-series and spatial analysis, meta-analysis, and rigorous uncertainty quantification (parameter, structural, and scenario). It emphasizes statistical rigor over result fabrication, guiding the use of appropriate inferential machinery based on data structure.

This guide provides comprehensive guidelines for advanced statistical and qualitative data analysis in Human Resource Management (HRM) research. It details the rigorous application of methods like Multilevel Modeling (HLM), Structural Equation Modeling (SEM), mediation testing, and fixed-effects models. It emphasizes methodological rigor, transparency, addressing endogeneity, and reporting effect sizes to ensure publication-quality empirical findings.

A comprehensive model detailing the rigorous, multi-stage peer review cycle for top-tier security conferences like IEEE S&P. It covers every phase, from initial submission and first-round screening to the three-way decision (Accept/Revise/Reject), ethical committee review, and post-acceptance shepherding. Ideal for authors needing to understand the structural constraints and adversarial nature of academic publishing.