aamas-reproducibility
Use when strengthening AAMAS reproducibility evidence for interaction claims, including proofs and game definitions, opponent and population sets, self-play protocols, random seeds, compute, uncertainty on strategic outcomes, baselines, and consistency between what the paper claims about agents and what the artifact can actually show.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aamas-reproducibility --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 Reproducibility Use this before submission and again before camera-ready. The reproducibility question at AAMAS is not only "can I rerun the model" but "can I reproduce the *interaction* - the same agents, the same game, the same emergent outcome." ## Evidence map - Map each theorem, mechanism property, convergence claim, and empirical interaction claim to a verifiable location in the paper, appendix, supplement, or artifact. - For theory, state the game, the information structure, the solution concept, assumptions, proof dependencies, and failure modes clearly enough for a game theorist. - For experiments, report the environment, number of agents, opponent/population set, training regime, evaluation opponents, metrics, hyperparameter ranges, chosen settings, seeds, repeated runs, compute, and runtime. - For small or noisy strategic differences, add uncertainty: standard errors, confidence intervals, or paired tests over seeds and over opponents. - Explain any missing code or environment honestly, and describe how a reader could reproduce the interaction in principle. - Keep the artifact consistent with the paper; a claim the artifact cannot demonstrate is a review-risk mul
- Evidence map
- Claim-to-evidence audit table
- Vignette: a MARL-plus-convergence paper
- Degrees of reproducibility
- Output format
What does the aamas-reproducibility skill do?
Use when strengthening AAMAS reproducibility evidence for interaction claims, including proofs and game definitions, opponent and population sets, self-play protocols, random seeds, compute, uncertainty on strategic outcomes, baselines, and consistency between what the paper claims about agents and what the artifact can actually show.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aamas-reproducibility --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.