edbt-artifact-evaluation
Use when preparing an EDBT database-systems artifact and reproducibility package, covering what evaluators check first for systems papers, a turnkey run path, pinned workloads and environments, DOI-issuing archival for the open-access OpenProceedings record, and the higher stakes for Experiments & Analysis papers.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill edbt-artifact-evaluation --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# EDBT Artifact Evaluation Use this for the artifact and reproducibility package. EDBT's community values re-runnable database-systems work, and the published record is **open access on OpenProceedings**, so a clean, archived package strengthens the paper and its permanent citation. Two things to internalize: an artifact is judged by an evaluator actually *running* it, and the review-time package
What does the edbt-artifact-evaluation skill do?
Use when preparing an EDBT database-systems artifact and reproducibility package, covering what evaluators check first for systems papers, a turnkey run path, pinned workloads and environments, DOI-issuing archival for the open-access OpenProceedings record, and the higher stakes for Experiments & Analysis papers.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill edbt-artifact-evaluation --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.