Skill UI

A pre-writing triage tool designed to stress-test a scientific result's general significance and broad appeal. It helps authors determine if their work meets the general interest criteria of top-tier journals (like Science), guiding decisions on whether to target a broad readership or a specialized field journal.

A comprehensive, final preflight checklist designed for submitting scientific manuscripts to top-tier journals. It ensures every critical element—from statistical rigor, data availability, and ethical compliance to formatting, figures, and references—is fully resolved, preventing editorial rejection or major revisions upon initial submission.

A comprehensive skill designed for authors targeting Science Signaling, a leading journal in cellular signal transduction. This tool provides guidance on the journal's scope, required mechanistic depth, quantitative rigor, house style, and specific evidence standards (e.g., loss/gain-of-function, in vivo evidence). It is crucial for venue selection and restructuring manuscripts to fit the high standards of AAAS Science family publications.

This skill is designed to help researchers assess the suitability and structure of their academic manuscripts for the journal 'Scientific Management Research.' It analyzes the alignment of the topic with core areas like innovation policy, technology management, and regional science. Users can utilize it to understand journal requirements, identify common rejection pitfalls, and receive suggestions for improving the narrative and scope before submission.

This guide provides a comprehensive audit checklist for designing and evaluating sensor-based systems (SenSys). It mandates rigorous, real-world measurements across five core axes: energy efficiency, on-device latency distribution, ground truth accuracy, deployment realism, and embedded AI footprint. It ensures that research results are based on measured hardware performance, not simulations or idealized baselines.

This skill provides comprehensive guidelines for conducting and reporting high-stakes quantitative data analysis in the social sciences. It emphasizes methodological rigor, requiring honest reporting of uncertainty, probing robustness (specs that could break the result), and ensuring full reproducibility. It covers advanced topics like design-based inference, cluster corrections, and handling missing data, ensuring results withstand expert review.

A comprehensive guide on methodological rigor for submitting manuscripts to Social Forces. It covers designing causal inference (panel/DID/IV/RDD), demographic analysis, comparative-historical case selection, and network/computational methods. The focus is on strengthening the design by rigorously defending assumptions and ruling out alternative explanations, ensuring methodological soundness beyond mere association.

This guide provides a comprehensive preflight checklist for submitting academic manuscripts to specialized journals (e.g., Social Forces via ScholarOne). It details critical compliance points such as double-anonymization, adherence to the 10,000-word limit (including references), panel count limits, and mandatory style requirements (Chicago 17th). It is designed to help authors catch common formatting and anonymity failures before official submission.

This tool acts as an orchestrator for academic manuscripts targeting general social-science journals. It guides authors through the entire writing and revision lifecycle, ensuring the paper maintains a general audience focus and adheres to strict structural constraints, such as 10,000-word limits (including references) and 10 figure/table panels. It routes the user to the most necessary next skill, whether for initial topic selection, theoretical positioning, research design, or final rebuttal.

This skill provides comprehensive guidance for authors submitting highly rigorous theoretical computer science manuscripts to top-tier venues like SIAM Journal on Computing (SICOMP). It covers required standards for algorithmic design, computational complexity, formal proofs, house style, and the high bar for theoretical contribution necessary for foundational academic publishing.

A comprehensive guide for designing and auditing high-stakes networking experiments, particularly for top-tier academic submissions like SIGCOMM. It outlines the 'evidence ladder' from microbenchmarks to live deployment, emphasizing the need to select robust baselines, report full performance distributions (percentiles and variance), and accurately map the mechanism's operational break points.

This guide outlines the rigorous standards required for submitting top-tier academic papers, such as those for ACM SIGCOMM. It instructs authors on how to transition from general claims to highly evidence-based arguments by focusing on measured operational pain, defining design principles, and pairing every performance claim with concrete testbed, trace, or deployment evidence. Essential for researchers in networking and systems.