aamas-experiments
Use when designing or auditing AAMAS experiments - self-play and population-based training, opponent selection, equilibrium and regret metrics, game-theoretic simulations, ablations, seeds, hyperparameters, compute, and claim-to-evidence fit - with emphasis on experiments that probe the interaction rather than chase a single-agent leaderboard.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aamas-experiments --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 Experiments Use this before submission when the empirical or simulation story is not yet locked. At AAMAS the experiment exists to test the *interaction* claim, not to top a benchmark. ## Experiment audit - Map each empirical claim to a game, a self-play run, a population sweep, an ablation, or a deviation test. - Choose opponents deliberately: self-play alone rarely suffices; include held
What does the aamas-experiments skill do?
Use when designing or auditing AAMAS experiments - self-play and population-based training, opponent selection, equilibrium and regret metrics, game-theoretic simulations, ablations, seeds, hyperparameters, compute, and claim-to-evidence fit - with emphasis on experiments that probe the interaction rather than chase a single-agent leaderboard.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aamas-experiments --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.