Skill UI

This skill guides users on optimizing their GitHub presence for maximum discoverability and professional appeal. It covers best practices for writing compelling README files, structuring comprehensive profile READMEs, and strategically implementing trust badges and marketing elements to enhance project visibility and adoption.

A guide for researchers submitting to conferences like ACM Multimedia, detailing how to achieve robust result reproducibility. It covers the necessary steps—including logging code commits, data versions, media preprocessing parameters, and hardware details—to allow independent reviewers to successfully rebuild the reported findings and achieve official reproducibility badges.

A comprehensive guide for researchers in electronics and signal processing preparing submissions to Acta Electronica Sinica (AES). It outlines best practices for proactively structuring, documenting, and disclosing research artifacts—including code, datasets, and hardware designs—to maximize the paper's credibility and chances of acceptance, even without mandatory journal badges. Covers anonymization, reproducibility standards, and proper disclosure in the manuscript.

This guide outlines the process for converting accepted academic research tools and data into highly polished, reproducible, and reusable packages for the ASE Artifact Evaluation track. Learn how to meet the criteria for earning 'Artifacts Available' (DOI archiving) and 'Artifacts Reusable' badges, ensuring your work is durable and accessible to the wider research community.

A comprehensive guide for authors preparing an artifact appendix (ae.tex) for major conferences like ASPLOS. Learn how to structure your submission to achieve Available, Functional, and Reproducible badges. Covers managing complex dependencies (hardware, software, data), structuring the repository for evaluators, and optimizing collaboration protocols to ensure successful post-acceptance validation.

This guide details the rigorous process for packaging research artifacts for submission to major conferences like USENIX ATC. It outlines the requirements for earning three key badges—Artifacts Available, Functional, and Reproduced—ensuring that submitted work is reproducible, functional, and permanently archived according to industry best practices.

This guide outlines the comprehensive process for submitting and evaluating Computer Aided Verification (CAV) research artifacts. It details the criteria for earning three badges (Available, Functional, Reusable), the two-phase review structure (smoke-test and full review), and best practices for packaging scientific tools, including the use of containers, pinned benchmarks, resource limits, and proof witnesses. This ensures reproducibility and rigor in academic research.

This guide details the process of packaging and evaluating academic artifacts for ACM CCS conferences. It outlines the criteria for earning specific ACM badges (e.g., Functional, Reusable, Results Reproduced) by ensuring that supporting evidence—such as exploits, defenses, and measurement pipelines—is turnkey, reproducible, and rigorously documented for the review committee. It covers best practices for artifact planning, handling sensitive material, and justifying any withheld components.

This guide details the comprehensive workflow for preparing an accepted ACM CCS paper for the final proceedings. It covers critical steps including de-anonymization, applying ACM sigconf templates and rights forms, incorporating shepherd/minor-revision feedback, placing artifact evaluation badges, and coordinating publication disclosure timing. Adherence to these technical and policy checks ensures compliance with ACM standards.

A comprehensive guide for authors submitting academic papers, detailing how to proactively provide reproducible code, datasets, and experimental scripts. This ensures that research results are verifiable and trustworthy, significantly enhancing the credibility of findings in high-tier journals despite the absence of formal artifact evaluation badges.

This guide outlines the process for converting accepted academic papers into optional ACM reproducibility badges. It walks authors through the rigorous evaluation cycle, covering everything from initial opt-in before submission to providing detailed one-page artifact descriptions. The goal is to prove that the research results are available, functionally sound, highly reusable, and accurately reproducible by independent evaluators.

This guide details best practices for enhancing the credibility of academic manuscripts submitted to scholarly journals, particularly addressing code and data availability. It teaches authors how to proactively provide stable links, checksums, comprehensive reproducibility scripts, and clear licensing statements. The focus is on bolstering trustworthiness for single-blind review processes, even when the journal does not mandate formal artifact badges.