edbt-reproducibility
Use when strengthening EDBT reproducibility for a database-systems paper, covering a runnable artifact, pinned environments and workloads, dataset and query-log provenance, claim-to-evidence mapping, honest degrees of reproducibility, and consistency between the paper and the package for the open-access OpenProceedings record.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill edbt-reproducibility --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 Reproducibility Use this before submission and again before camera-ready. EDBT's community has a reproducibility-forward culture, and the published record is **open access on OpenProceedings** — so an inspectable, re-runnable package raises a paper's standing and, for an **Experiments & Analysis** paper, *is* the contribution. The goal is that a competent reader could rebuild your measureme
What does the edbt-reproducibility skill do?
Use when strengthening EDBT reproducibility for a database-systems paper, covering a runnable artifact, pinned environments and workloads, dataset and query-log provenance, claim-to-evidence mapping, honest degrees of reproducibility, and consistency between the paper and the package for the open-access OpenProceedings record.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill edbt-reproducibility --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.