aamas-artifact-evaluation
Use when packaging AAMAS multiagent code, environments, opponent and population sets, random seeds, game definitions, and logs as anonymous supplementary evidence or a public post-acceptance release, even without a separate artifact badge, so that game-theory and MARL reviewers can inspect and re-run the interaction claims.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aamas-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.
# AAMAS Artifact Evaluation Use this for evidence packaging around AAMAS. Because the venue is about interaction, an artifact must make a *multiagent* claim inspectable: the game, the other agents, and the protocol, not just a single trained model. ## Artifact plan - Decide what a reviewer needs to believe the interaction claim: game or environment code, opponent/population definitions, the training regime, seeds, payoff logs, proofs, or qualitative episode traces. - Keep decision-critical evidence in the main paper or appendix; optional bulk runs can live in the supplementary zip. - Anonymize repository history, paths, environment names, license headers, cluster paths, and commit authors for the review version. - Include a minimal reproduction map: environment build, dependencies, hardware, commands, expected outputs, per-run wall-clock, seeds, and known nondeterminism (especially in self-play). - For a deployed or human-subject setting, give enough provenance for credible reproduction without violating data-use terms. - After acceptance, replace anonymous archives with a public, licensed, citable artifact. ## What AAMAS evidence reviewers open first The single fact that shapes pa
- Artifact plan
- What AAMAS evidence reviewers open first
- Worked vignette: packaging a self-play study
- Calibration anchors
- Output format
What does the aamas-artifact-evaluation skill do?
Use when packaging AAMAS multiagent code, environments, opponent and population sets, random seeds, game definitions, and logs as anonymous supplementary evidence or a public post-acceptance release, even without a separate artifact badge, so that game-theory and MARL reviewers can inspect and re-run the interaction claims.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aamas-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.