Agent skill · Code Review & Quality

sigmetrics-artifact-evaluation

Use when packaging an ACM SIGMETRICS artifact for the ACM Artifact Review and Badging scheme (Artifacts Available, Evaluated Functional and Reusable, Results Reproduced), covering what performance-evaluation evaluators check first (does the simulation regenerate the figures and match the analysis?), DOI-issuing archives, evaluator-proof documentation, and confirming whether an artifact track runs this cycle.

brycew6m878★ · +32/wk · 1 repos on radarProfile →
claude-codeMIT
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigmetrics-artifact-evaluation --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 6 KB
Bundled scripts: none
Path: SIGMETRICS-Skills/skills/sigmetrics-artifact-evaluation/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 909 · +31 this week
Language: Stata
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# SIGMETRICS Artifact Evaluation Use this for artifact/reproducibility packaging. SIGMETRICS sits in the ACM ecosystem and, where an artifact track runs, follows the **ACM Artifact Review and Badging** scheme. Two things to internalize: badges are earned by evaluators actually using your package, and — distinctively for SIGMETRICS — the package usually has to let an evaluator **regenerate the figures from a seeded simulation and see them match the analytic prediction**, not only run a tool. Confirm on the current cycle whether a formal artifact track exists and its timing (**待核实**). ## The ACM badges (verify the current set and names) | Badge | What it certifies | What earns it | |---|---|---| | Artifacts Available | The artifact is permanently, publicly retrievable | Deposit in a DOI-issuing archive (Zenodo, figshare, Software Heritage) | | Artifacts Evaluated - Functional | The artifact runs and does what the paper says | A clean-machine install, a demo run of the simulator, documented expected outputs | | Artifacts Evaluated - Reusable | Others can build on it | The Functional bar plus careful docs, structure, and licensing | | Results Reproduced | An evaluator reproduced the pa

What's inside
Steps it walks through
  1. The ACM badges (verify the current set and names)
  2. What performance-evaluation evaluators open first
  3. Packaging plan
  4. Anonymized review artifact vs. badge artifact
  5. Worked vignette: packaging a scheduling-policy paper
  6. Calibration
  7. Output format
More from Awesome-Journal-Skills
All skills →
About this skill
What does the sigmetrics-artifact-evaluation skill do?

Use when packaging an ACM SIGMETRICS artifact for the ACM Artifact Review and Badging scheme (Artifacts Available, Evaluated Functional and Reusable, Results Reproduced), covering what performance-evaluation evaluators check first (does the simulation regenerate the figures and match the analysis?), DOI-issuing archives, evaluator-proof documentation, and confirming whether an artifact track runs this cycle.

How do I install it?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigmetrics-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.

Keep going