Skill UI

Provides guidance on organizing and writing focused XUnit unit tests, covering project setup, fact/theory patterns, assertions, mocking, and data-driven testing for reliable .NET test suites.

A comprehensive guide for designing and presenting rigorous experiments and simulations for top-tier journals in Control Theory, Robotics, and Smart Systems. Covers RQ-driven design, establishing fair baselines, providing theoretical proofs of stability/convergence, performing ablation studies, and ensuring statistical significance, helping authors build an undeniable evidence chain for double-blind external review.

This advanced skill provides a rigorous framework for assessing whether an organizational or management research manuscript is suitable for highly selective, theory-driven journals like the Academy of Management Journal (AMJ). It guides authors on necessary theoretical framing, methodological rigor (e.g., endogeneity, causal inference), structural improvements, and common pitfalls to avoid, significantly improving submission quality and maximizing acceptance chances.

This guide helps researchers elevate general empirical ideas (e.g., 'X affects Y') into rigorous, theory-driven accounting contributions. It outlines four sources of academic contribution, identifies key areas (auditing, financial accounting, governance), and teaches how to anchor research in specific accounting mechanisms and China's institutional context, meeting the standards of top-tier accounting journals.

This guide provides a structured methodology for articulating the unique and marginal contribution of a scholarly paper, particularly within macroeconomics. It teaches authors how to bridge the gap between theoretical modeling (quantitative-theory) and data-driven evidence (identified-empirical), ensuring that the novelty and scope are clearly communicated to a broad, general expert audience.

This guide helps authors strategically position their academic work within the existing body of sociological literature. It teaches how to frame a paper not merely as filling a knowledge gap, but as resolving a core theoretical tension or participating in a live, generalist debate. It is essential for improving submissions to highly selective, theory-driven journals like AJS.

A structured guide for academic researchers to scope and sanity-check research ideas for top-tier management journals like the Academy of Management Journal (AMJ). It ensures the topic is theory-driven, empirically feasible, and addresses a theoretical tension, helping authors elevate a vague idea into a publishable, impactful scholarly question.

A comprehensive guide for researchers developing manuscripts in Accounting, Organizations, and Society (AOS). It teaches how to select, deeply inhabit, and generate analysis using established social or organizational theories (e.g., Institutional Theory, Bourdieu, Foucault). The goal is to ensure the theory is the generative engine of the paper, rather than merely decorative framing. This framework guides the transition from description to rigorous, theory-driven contribution.

A comprehensive guide for transforming descriptive or mechanical drafts into highly disciplined, theory-driven, and continuous argumentative prose. It teaches authors how to adopt the 'AOS register'—anchoring every interpretive move to evidence—and master crucial elements like terminology management, self-contained abstracts, and rigorous anonymization for top-tier academic journal submissions.

This guide assists in building robust, mechanism-driven theories for academic manuscripts, particularly in organizational science. It teaches the critical distinction between process theories (explaining how and why things unfold) and variance theories (explaining how much things vary). It emphasizes defining generative mechanisms, specifying boundary conditions, and structuring arguments for both inductive and deductive research designs, ensuring the theory is the core contribution.

This guide details how to move beyond simple mediation analysis to establish robust, theory-driven causal mechanisms. It outlines advanced econometric strategies, such as exclusion methods, pre-specified heterogeneity testing, and temporal analysis, required to distinguish a primary effect from competing channels, meeting high academic standards.

This skill provides a rigorous framework for researchers to evaluate whether their cognitive science project is suitable for high-impact, theory-driven journals. It guides users to elevate their contribution from single-effect reports to multi-experiment programs, formal computational models, and substantial theoretical advances, ensuring the work meets the necessary standard of integrative scope.