Skill UI

A specialized guide for polishing academic manuscripts, particularly in econometrics and theoretical sciences. It enforces a terse, formal, and highly structured writing style, ensuring all definitions, assumptions, and theorems are numbered and displayed correctly. Ideal for turning narrative drafts into submissions suitable for top-tier academic journals.

A structured guide for authors on how to frame the central findings of an Econometric Theory (ET) paper. It ensures that the contribution is clearly articulated by defining the underlying problem, stating the main theorem and its scope, identifying the generality delta, and discussing practical implications, meeting the rigorous standards of top academic journals.

This comprehensive guide outlines the strict requirements for preparing replication and data packages for submission to The Econometrics Journal (EctJ). It covers everything from README structure and detailed code inclusion to ensuring Monte Carlo determinism and managing restricted data, ensuring the method's credibility for reviewers.

This guide provides stringent best practices for authors submitting papers to top database systems conferences (like EDBT). It emphasizes leading with a concrete data-management contribution, ensuring mechanisms are reproducible in prose, and pairing every claim with rigorous, real-world evidence. It also dictates how to manage scope and adhere to publishing constraints.

This guide provides a structured framework for authors to sharpen the narrative of their academic contribution, particularly for high-impact journals. It teaches the 'two-layer positioning': creating a broad-interest hook for general readers, and defining a precise marginal delta against 3-5 specific, current frontier papers. It transforms vague related-work sections into compelling, verifiable arguments.

A specialized skill for positioning computer graphics manuscripts for the Eurographics conference. It guides authors on framing their contribution, structuring technical evidence, and aligning the work with specialized European graphics research themes (e.g., rendering, visualization, geometry processing) to maximize acceptance chances and ensure precise scholarly focus.

A comprehensive guide for structuring the related work section in interdisciplinary HRI papers. It teaches authors how to simultaneously situate their research across multiple literatures—including robotics, HCI, psychology, and design—while employing a 'delta-first' argument to clearly articulate novelty and maintaining double-blind review compliance.

This skill guides researchers through the rigorous process of stress-testing research questions for top-tier Human Resource Management (HRM) journals. It emphasizes that a viable topic must pass two critical gates: 1) Scholarly Advance (contributing theory, empirical, or methodologically), and 2) Practical Significance (offering clear implications for workforce policy or HRM practice). It helps researchers refine their focus to ensure the work is systemic and actionable, rather than merely descriptive.

This comprehensive guide details the stringent process of preparing an accepted scholarly paper for publication in LIPIcs proceedings. It covers mandatory steps including converting to the specific `lipics-v2021` class, systematic de-anonymization (restoring authors, ORCIDs, and acknowledgements), completing rich metadata (ACM CCS, keywords, funding), and reconciling the final body text with the public full version. Essential reading for ensuring smooth production.

This guide outlines the standards for ensuring the verifiability and rigor of theoretical computer science papers, particularly for venues like ICDT. It mandates complete proofs, precise pinning of models and assumptions, explicit matching of upper and lower bounds, and strict internal consistency across all claims and full versions. Use this checklist before submission to elevate academic quality.

This guide outlines best practices for structuring academic papers submitted via OpenReview, particularly for venues like ICLR. It advises authors on where to place different types of evidence—such as core claims, full derivations, code, and large datasets—to ensure the central argument remains visible while maintaining academic rigor. It covers strategies for managing annexes, maintaining anonymity, and updating revisions.

This guide helps software engineering researchers determine the most appropriate academic conference or journal venue for their work. It provides comprehensive fit tests based on contribution type, empirical evidence maturity, and potential impact on industry practice. Authors learn to evaluate their research against criteria like novelty, rigor, and real-world relevance, ensuring proper routing to specialized tracks (e.g., ISSTA, ASE, ICSE).