Skill UI

This skill provides a comprehensive fit and structural review tool for manuscripts targeting 'Field Crops Research.' It assesses whether an agronomy or crop-physiology paper meets the journal's high standard: rigorous, adequately replicated, multi-environment field experimentation. It guides authors on key topics like resource-use efficiency, crop modeling validation, and required methodological depth (e.g., mixed models, full metadata reporting).

This skill guides researchers through the entire end-to-end lifecycle of submitting a research paper to a journal. It structures a 12-step pipeline, covering everything from initial topic selection and literature review to experimentation, reproducibility, submission, peer review, revision, and final camera-ready versioning. It acts as a comprehensive project dashboard for managing the entire academic publishing journey.

Provides a comprehensive, end-to-end workflow guide for academic papers submitted to journals. It meticulously covers every stage, from initial topic selection, structured writing, and experimentation, through the submission process, multi-round revisions, acceptance, and final typesetting. This tool helps users manage the entire publication lifecycle and proactively avoid common temporal pitfalls.

This tool guides authors in assessing whether their fluid mechanics manuscript is a suitable fit for the Journal of Fluid Mechanics (JFM). It emphasizes the need for fundamental physical understanding (e.g., new scaling laws, instability mechanisms) over mere demonstration of applied methods or devices. It covers rigorous standards for computation, experimentation, and theoretical analysis, serving as a crucial pre-submission framing and venue-selection resource.

This comprehensive guide outlines best practices for designing rigorous and convincing technical evaluations for networked systems. It structures the process by requiring experiments to answer specific questions, advising authors to climb the evidence ladder from synthetic benchmarks to real-world deployment. Key concepts include reporting tail latencies (p99), establishing strong baselines, and maintaining meticulous provenance records to ensure reproducibility.

A comprehensive guide for authors submitting theoretical computer science papers to SODA. It clarifies the distinction between SODA (theory-led) and ALENEX (experiment-led), advising on when and how to incorporate numerical evidence. The protocol details best practices for honest numerics, including instance generation discipline, claim-class labeling (illustration, evidence, motivation), and proper submission routing to ensure academic rigor.

A comprehensive, end-to-end guide for researchers aiming to publish high-impact manuscripts in top-tier journals like SCI. It meticulously maps the entire journey, from initial topic brainstorming and framework building to rigorous experimentation, submission auditing, revision, and final publication preparation. This skill minimizes common publication pitfalls and guides authors through the entire academic life cycle.

A comprehensive audit checklist for designing and evaluating security experiments, adhering to the highest academic standards (e.g., USENIX Security). It guides users through verifying adaptive attacker models, calculating precision at realistic base rates, ensuring statistical honesty for stochastic results, and maintaining ethical compliance when working with live systems.