# Aamas Artifact Evaluation

Use when packaging AAMAS multiagent code, environments, opponent and population sets...

- Repository: https://github.com/brycewang-stanford/Awesome-Journal-Skills (1346 stars)
- Category: Engineering
- License: MIT
- Last updated: 2026-09-27
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aamas-artifact-evaluation -g -a claude-code -y`
Codex: `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aamas-artifact-evaluation -g -a codex -y`
Cursor: `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aamas-artifact-evaluation -g -a cursor -y`
Gemini CLI: `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aamas-artifact-evaluation -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add brycewang-stanford/Awesome-Journal-Skills`

## Description

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.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# 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 packaging: a reviewer will re-run a small **game** far sooner than
they will retrain a large policy, so make the strategic core turnkey before polishing anything.

The rest: https://github.com/brycewang-stanford/Awesome-Journal-Skills/blob/HEAD/AAMAS-Skills/skills/aamas-artifact-evaluation/SKILL.md