Skill UI

This comprehensive preflight checklist is designed for authors submitting to the Journal of Communication (JoC). It details critical requirements for successful submission, including maintaining double-anonymity, adhering to APA 7th edition formatting, using the correct file type (Word .docx), and including a Data Availability Statement. Use this guide to perform a final quality check and avoid common desk-reject issues.

A comprehensive pre-submission guide designed for authors targeting the Journal of Law and Economics (JLE). It helps determine if a manuscript—combining legal/regulatory questions with empirical or applied economic analysis—meets JLE's high standards for method, evidence, and structure. It covers identification strategies (e.g., DiD, IV), data quality, and common reasons for desk rejection.

This guide details the optimal structure for writing a high-quality literature review, especially for quantitative economics journals. It advises users to avoid chronological descriptions and instead organize the review around the core method lineage (how a quantity is measured, forecasted, or decomposed) and the specific application gap in China's data context. This ensures the literature review logically and powerfully leads to the paper's unique contribution.

A comprehensive guide for structuring the empirical section of high-level machine learning papers (e.g., KDD). It details the 'four-axis evidence plan'—Quality, Scale, Efficiency, and Mechanism—and emphasizes critical data hygiene practices. Learn how to prevent temporal leakage, structure ablations in a matrix format, and design post-launch measurements to ensure academic rigor and reproducibility.

A comprehensive, step-by-step preflight checklist designed for authors submitting manuscripts to top-tier scientific journals. It ensures thorough validation across all required components, including the mechanistic narrative, structural data integrity, statistical rigor (QSA), figure quality, and proper data/code deposition (DOIs). It serves as the ultimate gatekeeping mechanism before final submission.

This skill provides robust functionality to resolve free-text scientific labels into standard ontology term IDs (CURIEs) and validate existing identifiers against authoritative databases. It is essential for metadata curation, ensuring that submitted biological data (e.g., tissue types, diseases, assays) uses current, correct, and non-obsolete identifiers, thereby maintaining high data quality for large-scale scientific datasets.

This comprehensive preflight checklist is designed for authors preparing manuscripts for top academic journals. It guides users through crucial submission requirements, including double-blind anonymization, adherence to strict length norms (under 50 pages), structuring the contribution case, and ensuring compliance with modern transparency policies regarding data, code, and AI usage. Use it to maximize submission quality and minimize desk rejection risk.

A comprehensive, final quality control checklist designed for submitting manuscripts to PNAS Nexus. It serves as a master gatekeeper, ensuring compliance across fit, open access licensing (APC/CC BY), structural integrity, statistical rigor, data deposition (DOI/accession numbers), and required metadata. It helps writers confirm nothing is missing before final submission.

This router guides the entire workflow for developing a high-quality academic manuscript targeting the Review of Accounting Studies (RAST). It helps users determine the next necessary step—be it theory development, data analysis, refining contributions, or preparing for submission and rebuttal—ensuring methodological rigor and structural completeness throughout the writing process.

This router guides authors through the complex, multi-stage process of preparing a manuscript for a top-tier finance journal like the Review of Finance (RoF). It diagnoses current bottlenecks—whether related to contribution framing, data analysis, or rebuttal strategy—and systematically recommends the next specialized skill to ensure a complete and high-quality submission.

Provides comprehensive guidelines for designing high-impact scientific figures for major academic journals. It covers technical aspects like optimal sizing, font legibility, and colorblind safety, while also enforcing strict data visualization practices (e.g., using dot plots over bars, defining 'n', ensuring data integrity). Use this as a final quality check before submission to guarantee scientific rigor and maximize publication chances.

This skill helps researchers evaluate whether their manuscript aligns with the scope and practical orientation of specific academic journals. It provides structural advice, outlines key evidence requirements (e.g., patent quality, data analysis), identifies common rejection pitfalls, and guides the user through official submission checks for highly specialized journals.