Skill UI

Provides comprehensive guidelines for creating durable, verifiable evidence objects (artifacts) for theoretical computer science papers. It details best practices for managing proofs, certificates, checker code, and version histories across different publication formats (arXiv, IEEE Xplore) to ensure long-term academic credibility and reproducibility.

This guide outlines the rigorous, multi-stage process for submitting camera-ready versions for a top-tier academic conference like FOCS. It details the critical difference between the official IEEE proceedings and the public arXiv/ECCC full version. Key steps include de-anonymization, maintaining source consistency across both documents, updating author details, and preparing for conference talks and awards eligibility.

A comprehensive guide for authors submitting to top-tier Software Engineering (SE) conferences (like FSE, ICSE). It details how to structure the Related Work section by focusing on the 'delta'—the unique difference—between your work and prior art. It emphasizes covering the full SE literature landscape, maintaining anonymity, and correctly declaring overlaps with concurrent or prior versions.

This guide details the rigorous, journal-style review process for FSE submissions. It covers double-anonymous review, the three-reviewer program committee model, and the significance of Major Revision as a full revise-and-resubmit round. It helps authors understand how to strategically strengthen their work by addressing structural vs. revisable gaps, maximizing their chances of acceptance, and differentiating FSE's process from other conferences.

This guide helps researchers elevate local, sub-field specific findings into global-scale scientific contributions. It teaches how to structure a manuscript by anchoring the work on driver-response literature, speaking across different Earth systems (e.g., terrestrial and marine), and engaging with major synthesis meta-analyses. Use this when your work needs to prove broader applicability beyond its initial data collection site.

This skill generates standardized commit messages adhering to the popular gitmoji convention. By analyzing a git diff, staged files, or a plain description of changes, it selects the single most appropriate emoji to categorize the intent (e.g., feature, bug fix, refactor). It outputs a concise, well-formed, and highly scannable commit message for the user to copy, without running any actual git commands.

This skill guides authors in developing strong, portable, and highly structured theoretical arguments for manuscripts submitted to top journals like Governance. It focuses on moving beyond mere description by identifying causal mechanisms, defining rigorous scope conditions, and establishing testable, comparative concepts. It helps ensure the theory can travel across different cases and contexts.

This guide assists researchers in precisely positioning their Human Resource Management (HRM) manuscripts within specific scholarly conversations. It teaches how to differentiate the work from similar fields (like Personnel Psychology or AMJ) and move beyond general topic reviews, ensuring the contribution is seen as an extension, qualification, or overturning of existing anchor works. Essential for academic writing and journal submission.

This guide teaches how to strategically frame a scholarly contribution beyond a simple literature review. It instructs authors on identifying the core academic 'conversation,' pinpointing the precise tension or gap, and explicitly demonstrating how their theory advances the field. It also helps differentiate the work's scope from similar adjacent journals (e.g., OS, AMJ).

This skill guides users through determining if a proposed organizational or workplace phenomenon is suitable for publication in Human Relations. It teaches how to shift focus from mere 'hot topics' or manager-prescriptive advice to uncovering a deep, theoretically grounded puzzle about social relationships at work. It also helps differentiate the topic's scope from similar journals like AMJ, OS, and JMS.

This guide provides a structured framework for drafting professional rebuttals to academic conference reviews, such as ICASSP. It emphasizes the critical difference between correcting factual errors and addressing legitimate gaps. The focus must be on providing a clean rationale for the technical committee's acceptance, adopting a professional tone suitable for a single-blind review process, and anchoring all claims to the submitted material.

This comprehensive guide outlines the strict requirements and protocols for submitting papers to the IEEE International Conference on Data Mining (ICDM). It details the crucial differences between the Research and Applied tracks, emphasizing the triple-blind anonymity regime. Key points include adhering to the strict 10-page IEEE format (including references and appendices), avoiding identity leaks in the body or metadata, and understanding the single, non-negotiable submission deadline. Failure to follow these guidelines results in automatic rejection.