Skill UI

A comprehensive guide for authors submitting research on software testing, analysis, verification, and fuzzing to ISSTA. It provides strategic advice on framing the paper, establishing necessary evidence (e.g., fault models, benchmarks, real-world data), and ensuring the contribution aligns precisely with the requirements of top-tier CS conferences.

A comprehensive guide for researchers to determine if their work represents a genuine cross-modal or media-systems contribution suitable for ACM Multimedia (ACM MM). It helps route projects by testing for cross-modality, media system advances, or human-centric results, distinguishing between pure CV, NLP, or system-heavy claims.

A rigorous guide for academic researchers on establishing and testing the role of information mechanisms in accounting literature. It outlines how to shift focus from general pricing or financing channels to specific information channels—such as reducing information asymmetry, improving disclosure quality, or constraining earnings management. Provides advanced methodologies, including direct measurement of information variables and cross-sectional cutoff analysis.

This comprehensive guide details the methodological requirements for building a robust robustness section in accounting and empirical research manuscripts. It covers four critical pillars: substituting accounting measures, controlling for institutional/governance variables, executing placebo tests, and advanced endogeneity follow-ups. It helps authors ensure their primary findings withstand stringent academic scrutiny.

This guide provides a rigorous framework for strengthening economic manuscripts submitted to top journals, such as AEJ: Micro. It details how to systematically test the robustness of main results through theoretical extensions (e.g., relaxing assumptions, perturbations) and applied/experimental methods (e.g., sensitivity analyses, placebo tests). Learn how to identify extensions that truly 'earn their place' and significantly enhance the overall academic contribution of your work.

This skill acts as a workflow router, guiding researchers through the entire manuscript lifecycle for submissions to American Economic Journal: Microeconomics (AEJ: Micro). It does not write the paper, but diagnoses the current bottleneck—whether it's topic selection, model refinement, empirical testing, or rebuttal strategy—and specifies which specialized aejmic-* sub-skill to invoke next, ensuring the paper aligns with the specific requirements of AEJ: Micro. Triggered when users are unsure what step to take next, or when revising based on reviewer comments.

This guide outlines how to structure a rigorous robustness program for economic policy manuscripts. It emphasizes defending the overall policy takeaway, rather than merely reporting coefficient significance. Users learn to address common econometric threats—such as specification changes, pre-trends, multiple testing, and selection on unobservables—using advanced techniques (e.g., Wild-cluster bootstrap, Oster bounds) to ensure the policy conclusion is stable and credible.

This skill guides researchers in pressure-testing the significance and general appeal of a historical project before committing extensive archival time. It helps determine if a topic matters to the broader historical discipline, rather than being merely local or subfield-specific, aligning the work with the standards of flagship academic journals.

Provides a structured guide for positioning academic manuscripts within ongoing theoretical debates. It teaches authors how to move beyond simple 'gap-spotting' by identifying tensions, challenging assumptions (problematization), or testing boundaries between established theories. Essential for improving the theoretical rigor and argumentation of submissions to top-tier management journals.

This skill guides the stress-testing of theoretical manuscripts by focusing purely on logical coherence. It helps authors develop robust arguments by verifying proposition chains, running counterfactual thought experiments, addressing rival theories, and identifying disconfirming cases. It ensures the internal consistency and rigor of a theory, independent of empirical data analysis.

This guide assists researchers in structuring and presenting academic evidence for top-tier journals like ASQ. It provides best practices for both qualitative (establishing transparent data-to-theory links, coding transparency) and quantitative (ensuring robust mechanism testing and alternative explanation checks) analyses. It ensures all theoretical claims are auditable and fully supported by the raw data.

This skill guides scholars in rigorously evaluating whether a sociology project or paper is suitable for the American Sociological Review (ASR). It focuses on testing the work's broad significance, theoretical payoff across subfields, and structural fit, distinguishing between full articles and focused comments/replies. Use this before significant research investment.