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Aamas Review Process

CommunityPopular
brycewang-stanford
aamas-review-process

Use when explaining or planning around AAMAS peer review, covering OpenReview review release, the double-blind rebuttal on preliminary reviews, area-chair discussion, the mixed game-theory, MARL, and systems reviewer pool, the public posting of reviews and decisions, and how acceptance criteria weigh the interaction contribution.

Overview

Publisherbrycewang-stanford
RepositoryAwesome-Journal-Skills
Skill nameaamas-review-process
Stars
1.2K
Forks
159
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by brycewang-stanford on GitHub. Read the source before you install it.

Installation

Install the Aamas Review Process AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/AAMAS-Skills/skills/aamas-review-process
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git /tmp/Awesome-Journal-Skills
mkdir -p .claude/skills
cp -r /tmp/Awesome-Journal-Skills/AAMAS-Skills/skills/aamas-review-process .claude/skills/aamas-review-process
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Aamas Review Process in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Aamas Review Process on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Aamas Review Process is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

AAMAS Review Process

Use this to reason about review-stage strategy. Reopen the current CFP, OpenReview group, author and reviewer instructions, and the code of conduct before making process claims; AAMAS review specifics move between editions.

Process model

  • AAMAS runs submission and review on OpenReview under the IFAAMAS namespace in recent cycles.
  • Reviewers evaluate technical correctness, the significance of the interaction contribution, the reality and rigor of the multiagent evaluation, clarity, reproducibility, and fit with agents-and-multiagent-systems scope.
  • A rebuttal lets authors respond to preliminary reviews before the final decision; area chairs then synthesize.
  • Accepted papers and their reviews are published, so the review record is durable and public.
  • The most useful rebuttal gives the area chair a clean rationale for acceptance, not a point-by-point defense of every comment.

Who reviews here

  • The pool mixes game theorists, multiagent-RL researchers, mechanism-design and social-choice specialists, and systems-minded reviewers; expect at least one to read the game definition and solution concept line by line.
  • Because AAMAS is specialized, a paper is likely to meet a reviewer who works on exactly its subarea, so a vague equilibrium claim or an under-specified opponent set gets caught rather than skimmed.
  • Borderline interaction papers usually fail on one of three edges: the result turns out to be single-agent in disguise, the solution concept is never pinned down, or the multiagent evaluation is thin (self-play only, no seeds, no held-out opponents).

Scoring leverage table

Review dimensionWhat raises itWhat sinks it
CorrectnessA stated game, a named solution concept, and a body-level proof sketchHidden information structure; an equilibrium asserted but never defined
SignificanceA finding that only exists because agents interactAn incremental single-agent gain wearing a multiagent label
Empirical supportExperiments that probe strategy: held-out opponents, deviation testsSelf-play-only curves disconnected from the claim
ClarityOne notation source and a legible game descriptionNotation and payoff conventions that shift between sections

Stage-by-stage realism

  • Initial reviews: triage by what the area chair would weigh, not by reviewer tone.
  • Rebuttal: windows are short; an early, precise reply anchored in submitted evidence beats a late exhaustive one.
  • Decision: the area chair synthesizes, and one unanswered correctness or interaction-reality objection outweighs several resolved clarity complaints.
  • Public record: assume the reviews and your rebuttal will be visible with the paper, and keep the exchange professional and concrete.

Output format

text
[Current stage] submitted / reviews / rebuttal / decision / camera-ready
[Decision actors] <reviewers / area chair / program chairs>
[Likely leverage] <correctness / interaction-reality / significance / experiments / clarity>
[Forbidden moves] <identity leak / new results / revised-paper upload if disallowed>
[Next response move] <one action>

Frequently asked questions

What does the Aamas Review Process AI skill do?

Use when explaining or planning around AAMAS peer review, covering OpenReview review release, the double-blind rebuttal on preliminary reviews, area-chair discussion, the mixed game-theory, MARL, and systems reviewer pool, the public posting of reviews and decisions, and how acceptance criteria weigh the interaction contribution.

Why use Aamas Review Process on TypingMind?

Because you install it once and use it with any model. Aamas Review Process is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Aamas Review Process in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/AAMAS-Skills/skills/aamas-review-process. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Aamas Review Process?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Aamas Review Process?

As many as you like. As long as a model supports skills, you can use Aamas Review Process with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Aamas Review Process AI skill free?

Yes. It is published on GitHub by brycewang-stanford under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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