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Aamas Author Response

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brycewang-stanford
aamas-author-response

Use when drafting an AAMAS rebuttal to preliminary OpenReview reviews, covering the double-blind constraint, the no-new-results and no-revised-paper norms, how to answer game-theory, MARL, and systems reviewers at once, and how to give the area chair a clean acceptance rationale within a short response window.

Overview

Publisherbrycewang-stanford
RepositoryAwesome-Journal-Skills
Skill nameaamas-author-response
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 Author Response 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-author-response
  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-author-response .claude/skills/aamas-author-response
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Aamas Author Response 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 Author Response 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 Author Response 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 Author Response

Use this after AAMAS preliminary reviews are released. Reopen the current OpenReview instructions and the rebuttal-window rules before drafting; response mechanics are cycle-specific and AAMAS reviews and decisions become public afterward.

Triage

  • Answer only what can move the decision: correctness of the game model or proofs, the reality of the interaction claim, baseline/opponent fairness, reproducibility, and scope.
  • Use evidence already in the submission: sections, appendices, the supplement, theorem statements, learning curves, and opponent-set definitions. AAMAS rebuttals do not add new results and typically do not upload a revised paper.
  • Keep the reply anonymous: no institution, no named system, no private URLs or repository owners.
  • Correct outright factual errors first, then address requests for missing comparisons, ablations, equilibrium analysis, or seeds.

Drafting pattern

  1. State the decision-critical correction or concession in the first line.
  2. Point to the exact submitted evidence (section, figure, appendix, or theorem number).
  3. Explain the strategic or empirical consequence for the reviewer's concern.
  4. Promise a camera-ready wording fix only if it adds no unsupported new claim.

Multi-reviewer pushback patterns

AAMAS pools game theorists, MARL researchers, and systems-minded reviewers on one paper, so a single rebuttal often answers three different lenses at once.

PushbackWhat it signalsAAMAS-ready fix
"This is really a single-agent method"The interaction claim did not landPoint to where the result depends on other agents co-adapting; cite the ablation that freezes them
"Which equilibrium do you converge to?"A game theorist read the solution conceptName it (Nash / correlated / coarse / no-regret) and cite the proof or convergence plot
"Baselines are self-play only"Opponent set looks weakAnchor to the held-out opponents or population in the appendix, or concede a camera-ready addition
"Seeds and variance are missing"An empirical reviewer checked rigorReference the seeded runs and standard errors; do not promise new experiments as fact

Response micro-example

Reviewer objection: the cooperation result may be an artifact of a single random seed. Reply skeleton:

  1. Note that Figure 3 already aggregates 30 seeds with standard errors.
  2. Quote the exact aggregate so the reviewer need not re-open the PDF.
  3. Point to Appendix C for the per-seed spread and the opponent set used.
  4. Offer one camera-ready sentence stating the seed count in the caption.

Discussion-window calibration

  • One decision-critical point per reviewer beats an exhaustive reply; the area chair reads for whether the central interaction or correctness objection was actually resolved.
  • Never paste a fresh proof or a new game variant into the response box; sketch the argument and anchor it in submitted material.
  • Reply early - AAMAS rebuttal windows are short and reviewers who engage once rarely return.
  • Remember the reviews and your response may become public with the paper; write as if they will.

Output format

text
[Priority issue] <reviewer concern>
[Decision dimension] correctness / interaction-reality / significance / reproducibility / scope
[Draft response] <AAMAS-ready anonymous text>
[Evidence anchor] <section/appendix/figure/theorem>
[Forbidden content removed] <identity leaks, new results, revised-paper promises>

Frequently asked questions

What does the Aamas Author Response AI skill do?

Use when drafting an AAMAS rebuttal to preliminary OpenReview reviews, covering the double-blind constraint, the no-new-results and no-revised-paper norms, how to answer game-theory, MARL, and systems reviewers at once, and how to give the area chair a clean acceptance rationale within a short response window.

Why use Aamas Author Response on TypingMind?

Because you install it once and use it with any model. Aamas Author Response 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 Author Response 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-author-response. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Aamas Author Response?

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 Author Response?

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

Is the Aamas Author Response 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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