acmmm-artifact-evaluation
Use when packaging code, models, datasets, or media as ACM MM (ACM Multimedia) artifacts — building the anonymous review package versus the public release, and choosing between the Open Source Software Competition, the Dataset track, the Reproducibility track, and main-track supplementary evidence, each with its own blinding and expectations.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acmmm-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.
# ACM MM Artifact Evaluation Use this to turn an ACM Multimedia project's code, models, media, and data into the *right* artifact for the *right* track. ACM MM has a track economy around artifacts, and the choice determines blinding, format, and what reviewers judge. ## Which track is the artifact? | Artifact is primarily... | Route to | Blinding | Judged on | |---|---|---|---| | A reusable software system/framework | Open Source Software Competition | Single-blind | Adoption, quality, license, docs | | A new dataset/benchmark | Dataset track | Single-blind | Scale, quality, ethics, usefulness | | A reproduction of published results | Reproducibility track | Single-blind | Whether results rebuild; ACM badges | | Supporting evidence for a method paper | Main-track supplement | Double-blind | Whether it backs the paper's claims | The named single-blind tracks exist *because* the artifact's identity cannot be hidden; a main-track method paper's artifact, by contrast, must be **anonymous** through review. ## Two artifacts, two audiences Plan both from the start: - **Anonymous review artifact** — what reviewers see during double-blind review: an anonymized repository, an anonymous data
- Which track is the artifact?
- Two artifacts, two audiences
- Open Source Software Competition
- Dataset track
- Licensing and rights decisions
- Ethics and consent for media artifacts
- Timeline: review artifact, then release
- Output format
What does the acmmm-artifact-evaluation skill do?
Use when packaging code, models, datasets, or media as ACM MM (ACM Multimedia) artifacts — building the anonymous review package versus the public release, and choosing between the Open Source Software Competition, the Dataset track, the Reproducibility track, and main-track supplementary evidence, each with its own blinding and expectations.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acmmm-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.