Skill UI

A comprehensive guide designed to help authors assess the suitability of their manuscript for Limnology and Oceanography. It focuses on evaluating whether the work provides rigorous process insight by coupling physical, chemical, and biological processes in aquatic systems, going beyond mere descriptive surveys. This tool covers scope, required quantitative evidence, biogeochemistry, and journal-specific house style.

This skill is a comprehensive guide for researchers to determine if their Information Systems (IS) research manuscript meets the high academic standards of MIS Quarterly (MISQ). It evaluates the theoretical contribution, methodological rigor (behavioral, design-science, economics), and overall fit, providing crucial guidance on re-framing the work or suggesting alternative academic venues before submission.

This guide provides a structured methodology for authors to articulate the core contribution of their Information Systems (IS) research for top-tier academic journals, such as MIS Quarterly. It ensures that the paper explicitly states the new knowledge produced (e.g., behavioral mechanisms, design principles, economic effects), justifies the manuscript's length, and rigorously connects theoretical advances with practical and societal implications, thereby avoiding claims of being merely 'incremental' or 'technical' exercises.

A comprehensive guide for academic researchers preparing submissions for top-tier Information Systems journals like MIS Quarterly. It helps validate if a research idea is genuinely IT-centric, assigns it to one of the four core IS traditions (Behavioral, Design Science, Economics, Organizational), and selects the optimal manuscript genre to ensure scope and fit for publication.

This workflow serves as a comprehensive router for authors preparing manuscripts for the MIS Quarterly (MISQ). It guides researchers through the entire academic writing lifecycle, ensuring systematic development from initial topic selection and identifying the core IS research tradition (behavioral, design science, economics, or organizational). It maps out the necessary sequence of steps, including theory development, literature positioning, methodology, data analysis, contribution framing, and final submission readiness.

This comprehensive guide instructs researchers on how to design rigorous and credible evaluations for Machine Learning systems. It covers critical areas such as workload selection, baseline comparison discipline, reporting four key coordinates (throughput, latency tails, memory, cost), structuring ablations, and generating scaling evidence. It ensures measurements meet academic benchmarking standards.

This guide helps researchers determine if their project genuinely involves machine learning and computer system co-design. It outlines criteria, such as the "co-design test," and provides a routing table to decide whether the work belongs at MLSys compared to general systems conferences (OSDI, SOSP) or pure ML venues (ICML, NeurIPS).

This comprehensive guide provides best practices and an audit checklist for designing robust, real-world experiments in mobile and wireless communication systems. It emphasizes moving beyond simulations, detailing necessary RF setups, quantifiable energy metrics, and reporting statistical distributions to ensure high academic credibility.

This guide provides a comprehensive project management workflow for academic submissions to the MobiSys conference. It outlines the critical path, from initial system design and on-device measurement to final paper submission and artifact preparation. The workflow helps users plan backward from the single, crucial December deadline, managing device experiment lead time and mitigating common academic failure modes.

This advanced skill extends standard morph-ppt capabilities by enabling the seamless integration of 3D models (.glb) and advanced visual design elements. It features a robust, intelligent model discovery flow that proactively helps users find compatible 3D assets based on their topic (e.g., product, nature, concept). The system guides the user through searching multiple sources (Sketchfab API, Poly Pizza, Khronos assets) to ensure the final presentation is visually rich, professional, and technically sound.

This guide provides an expert methodology for designing and auditing Natural Language Processing (NLP) experiments for top-tier academic submissions. It instructs researchers on how to map meta-review claims to measurable evidence, ensure budget-fair comparisons, and systematically address potential reviewer probes (scope, fairness, contamination, etc.) to maximize publication rigor.

A comprehensive audit tool designed to ensure academic paper compliance before submitting to major AI conferences like NeurIPS. It systematically checks adherence to the CFP, double-blind anonymity across all assets (PDF, code, data, supplement), correct track selection, and avoids common desk-rejection pitfalls, ensuring the submission is ready for OpenReview.