sigmetrics-related-work
Use when positioning an ACM SIGMETRICS submission against the performance-evaluation literature across SIGMETRICS/POMACS, Performance Evaluation, QUESTA, TON, and the systems/learning/measurement neighbors (NSDI/OSDI, IMC, NeurIPS/ICML), writing delta-first contrast rather than a citation catalog, keeping self-citations double-anonymous, and handling concurrent and prior-version overlap.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigmetrics-related-work --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.
# SIGMETRICS Related Work Use this to audit novelty and eligibility. SIGMETRICS reviewers are close to the performance-evaluation literature and expect to see where your paper sits relative to the nearest prior model, bound, or measurement — stated as a **delta**, not a list. Reopen the current call for the simultaneous-submission and prior-publication rules (a paper under one-shot revision counts
What does the sigmetrics-related-work skill do?
Use when positioning an ACM SIGMETRICS submission against the performance-evaluation literature across SIGMETRICS/POMACS, Performance Evaluation, QUESTA, TON, and the systems/learning/measurement neighbors (NSDI/OSDI, IMC, NeurIPS/ICML), writing delta-first contrast rather than a citation catalog, keeping self-citations double-anonymous, and handling concurrent and prior-version overlap.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigmetrics-related-work --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.