Skill UI

This comprehensive tool guides researchers in drafting rigorous, point-by-point responses to referee reports (R&R). It ensures that every comment is systematically addressed, classifying fixes and providing structured revisions. Critically, it mandates that all substantive fixes must be backed by real, reproducible re-runs, citing specific numbers generated via an execution bridge to maintain scientific rigor.

This toolkit guides the entire academic publishing lifecycle, acting as a central router across multiple venues. It sequences critical steps—from selecting the ideal target journal (`rt-journal-match`) through data execution, submission readiness checks, simulated referee review, point-by-point rebuttal drafting, and generating the final replication package. It provides a structured, end-to-end process for researchers submitting complex manuscripts.

A comprehensive guide for packaging and evaluating research artifacts for academic conferences like SIGMETRICS. It details the requirements for achieving ACM Badges (Functional, Reusable, Reproduced) by ensuring the packaged simulation can regenerate key figures and results on a clean machine, moving beyond mere tool execution.

Polars is a lightning-fast DataFrame library designed for efficient, memory-efficient data processing in Python and Rust. Built upon Apache Arrow, it supports lazy evaluation and parallel execution, making it ideal for ETL pipelines, large-scale data transformations, and scenarios where standard Pandas performance is insufficient. It excels at handling datasets up to 100GB that fit within available RAM.