A skill your agent uses when deciding whether a project is a strong AAMAS fit, comparing AAMAS with AAAI, IJCAI, NeurIPS, ICML, EC, and the JAAMAS journal, identifying whether the agents are truly…

MITAuto-check passed

Install Aamas Topic Selection

skills CLI
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aamas-topic-selection -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills aamas-topic-selection --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/AAMAS-Skills/skills/aamas-topic-selection .claude/skills/aamas-topic-selection && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
aamas-topic-selection
GitHub stars
1.2k
Token cost
~952 tokens
SKILL.md length
422 words
Files
1
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when deciding whether a project is a strong AAMAS fit, comparing AAMAS with AAAI, IJCAI, NeurIPS, ICML, EC, and the JAAMAS journal, identifying whether the agents are truly…

  • Deciding whether a project is a strong AAMAS fit
  • SKILL.md covers Fit test, Fit signal table, Vignette: where a… and Sharpening moves before…, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Comparing AAMAS with AAAI

What it does

Aamas Topic Selection is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when deciding whether a project is a strong AAMAS fit, comparing AAMAS with AAAI, IJCAI, NeurIPS, ICML, EC, and the JAAMAS journal, identifying whether the agents are truly the research object, naming the interaction primitive (solution concept, mechanism, coordination, negotiation), and sharpening the multiagent framing before writing begins.

Its SKILL.md is about 950 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. | 覆盖主流期刊的… The licence is MIT.

When your agent uses it

  • Deciding whether a project is a strong AAMAS fit
  • Comparing AAMAS with AAAI
  • The JAAMAS journal
  • Identifying whether the agents are truly the research object

Example prompts

  • “/aamas-topic-selection”

What it can do on your machine

Read from SKILL.md and the folder at commit 932eb23. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Aamas Topic Selection loads about 952 tokens when it runs. Until then it costs about 93 tokens; SKILL.md has 422 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~93
When it runs · the whole SKILL.md, loaded when a task matches
~952

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 422 words, ~952 tokens.

Download SKILL.mdSave it as .claude/skills/aamas-topic-selection/SKILL.md (or your agent's skills folder).
name
aamas-topic-selection
description
Use when deciding whether a project is a strong AAMAS fit, comparing AAMAS with AAAI, IJCAI, NeurIPS, ICML, EC, and the JAAMAS journal, identifying whether the agents are truly the research object, naming the interaction primitive (solution concept, mechanism, coordination, negotiation), and sharpening the multiagent framing before writing begins.

AAMAS Topic Selection

Use this before writing. AAMAS is strongest when the agents are the research object - when the result exists because multiple self-interested or cooperating agents interact - not when a single-agent method is dressed in multiagent vocabulary.

Fit test

  • Prefer AAMAS when the contribution advances game-theoretic reasoning, multiagent learning, mechanism design, auctions, negotiation, argumentation, coordination and teamwork, agent-based simulation, or social choice, with the interaction as the object.
  • Route to NeurIPS or ICML if the core is a single-agent or general ML method and the multiagent setting is only a testbed.
  • Route to AAAI or IJCAI if the contribution is broad AI - planning, knowledge representation, reasoning - without an interaction result at its center.
  • Route to EC (Economics and Computation) if the contribution is primarily equilibrium computation, market design, or auction theory with the economics framing dominant.
  • Route to the JAAMAS journal (or its AAMAS presentation track) when the work needs journal-length exposition and a full-length archival treatment.
  • Check early whether the interaction result can be made convincing in an 8-page body.

Fit signal table

Signal in the projectAAMAS reading
A solution concept, mechanism, or coordination result paired with multiagent experimentsCore fit - the house genre
Emergent behavior that only appears because agents co-adaptCore fit
Strong single-agent method benchmarked in a multiagent environmentBetter served at NeurIPS or ICML
Pure market/auction theory with economics as the pointEC or an econ-CS journal
Broad AI reasoning with no interaction at its centerAAAI or IJCAI
Show full SKILL.md (176 more words)Show less

Vignette: where a communication-learning project goes

A project trains agents to communicate and shows higher cooperation in a mixed-motive game. AAMAS reading: strong fit if the analysis is about the interaction - what the emergent protocol signals, whether it is incentive-compatible, how it changes the equilibrium. Strip the incentive and coordination analysis and keep only a reward curve, and the same project reads as a general MARL paper better suited to NeurIPS or ICML; grow it into a full theory of the signaling equilibrium, and EC or JAAMAS becomes the better home.

Sharpening moves before committing

  • Name the interaction primitive: solution concept, mechanism, protocol, negotiation strategy, or coordination guarantee. If none exists, the AAMAS framing does not exist either.
  • Apply the frozen-agent test: if the result survives with the other agents replaced by a static environment, it is single-agent and belongs elsewhere.
  • Confirm the experiments can probe the interaction (deviation tests, held-out opponents), not merely accompany it.
  • Topic emphasis and track structure drift between cycles; scan the current CFP and track list before final routing.

Output format

text
[Fit] strong AAMAS / possible AAMAS / better elsewhere
[Best venue] AAMAS / AAAI / IJCAI / NeurIPS / ICML / EC / JAAMAS / other
[Interaction primitive] <solution concept / mechanism / coordination / negotiation / none>
[Contribution sentence] <one sentence>
[Top rejection risk] <single-agent-in-disguise / concept-unnamed / thin-evaluation / scope>
[Next action] <theory, experiment, framing, or venue switch>

© brycewang-stanford, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in AAMAS-Skills/skills/aamas-topic-selection of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

Compare with similar skills

Aamas Topic Selection next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Aamas Topic Selection compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Aamas Topic Selection this skillbrycewang-stanford/Awesome-Journal-Skills1.2k—~952Automated safety check: PassMIT
Table Fitasgeirtj/system_prompts_leaks69k—~772Automated safety check: PassCC0-1.0
Furniture Fit Checkpascalorg/editor25k—~5.1kAutomated safety check: PassMIT
TopicsZimoLiao/scholaraio577—~294Automated safety check: PassMIT
Topic Modelingbrycewang-stanford/Auto-Empirical-Research-Skills4.5k—~3.7kAutomated safety check: PassCustom licence
Bestblogs Topicginobefun/BestBlogs4k—~670Automated safety check: PassNone

Similar skills

  • Table Fit

    asgeirtj/system_prompts_leaks

    Keep a Markdown table readable in a narrow terminal of about 100 display columns - a wide table or one carrying prose in its cells wraps into unreadable ragged rows.

    69k GitHub stars~772 tokensUpdated yesterday
    Testing & QAAuto-check passed
  • Furniture Fit Check

    pascalorg/editor

    Checks whether a sofa, table, bed or appliance fits in a measured Pascal room and reports only what the evidence supports, or asks for the missing measurements.

    25k GitHub stars~5.1k tokensUpdated today
    Agent WorkflowsAuto-check passed
  • Topics

    ZimoLiao/scholaraio

    A skill your agent uses when the user asks about research themes, topic distribution, BERTopic clustering, topic overview, topic papers, topic merges, or HTML topic visualizations.

    577 GitHub stars~294 tokensUpdated 13 days ago
    Auto-check passed
  • Topic Modeling

    brycewang-stanford/Auto-Empirical-Research-Skills

    Structural topic modeling: STM spec, topic count, coherence-exclusivity.

    4.5k GitHub stars~3.7k tokensUpdated 3 days ago
    AI & LLM EngineeringAuto-check passed
  • Bestblogs Topic

    ginobefun/BestBlogs

    A skill your agent uses when the user asks about a specific topic, subject area, or wants to explore curated topic pages on BestBlogs.

    4k GitHub stars~670 tokensUpdated 3 mo ago
    Auto-check passed
  • Fitness Program

    revfactory/harness-100

    A full pipeline where an agent team collaborates to generate everything from goal-based fitness program design to progress tracking templates.

    1.3k GitHub stars~1.8k tokensUpdated 6 mo ago
    Productivity & AutomationAuto-check passed

More from brycewang-stanford/Awesome-Journal-Skills

All 2,387 skills in this repo
  • Aaag Data Analysis

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when running and reporting the analysis for an Annals of the American Association of Geographers manuscript — spatial statistics and modeling, remote-sensing accuracy, or…

    1.2k GitHub stars~1.3k tokensUpdated 12 days ago
    Auto-check passed
  • Aaag Literature Positioning

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when positioning an Annals of the American Association of Geographers manuscript in the literature — engaging geographic scholarship across the relevant area and the…

    1.2k GitHub stars~1.3k tokensUpdated 12 days ago
    Auto-check passed
  • Aaag Rebuttal

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when responding to an Annals of the American Association of Geographers decision letter (major/minor revision) — building a point-by-point response to the subject editor and…

    1.2k GitHub stars~1.4k tokensUpdated 12 days ago
    Auto-check passed
  • Aaag Research Design

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when defending the research design of an Annals of the American Association of Geographers manuscript — spatial/quantitative analysis and GIScience, remote-sensing and…

    1.2k GitHub stars~1.4k tokensUpdated 12 days ago
    Auto-check passed
  • Aaag Review Process

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when you need to understand how the Annals of the American Association of Geographers evaluates a manuscript — double-anonymous review routed through a subject editor by…

    1.2k GitHub stars~1.3k tokensUpdated 12 days ago
    Auto-check passed
  • Aaag Submission

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when running the final pre-submission preflight for the Annals of the American Association of Geographers via ScholarOne Manuscripts — area/article-type selection…

    1.2k GitHub stars~1.6k tokensUpdated 12 days ago
    Auto-check passed

Questions about Aamas Topic Selection

What does Aamas Topic Selection do?

A skill your agent uses when deciding whether a project is a strong AAMAS fit, comparing AAMAS with AAAI, IJCAI, NeurIPS, ICML, EC, and the JAAMAS journal, identifying whether the agents are truly…. Aamas Topic Selection is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when deciding whether a project is a strong AAMAS fit, comparing AAMAS with AAAI, IJCAI, NeurIPS, ICML, EC, and the JAAMAS journal, identifying whether the agents are truly the research object, naming the interaction primitive (solution concept, mechanism, coordination, negotiation), and sharpening the multiagent framing before writing begins.

When should I use Aamas Topic Selection?

Aamas Topic Selection fits situations like: deciding whether a project is a strong AAMAS fit; comparing AAMAS with AAAI; the JAAMAS journal; identifying whether the agents are truly the research object.

How do I install Aamas Topic Selection in Claude Code?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aamas-topic-selection -a claude-code`. Or copy the skill folder (AAMAS-Skills/skills/aamas-topic-selection in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/aamas-topic-selection in your project. Claude Code loads it when a task matches its description.

How do I install Aamas Topic Selection in Codex?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aamas-topic-selection -a codex`. Or copy the skill folder (AAMAS-Skills/skills/aamas-topic-selection in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/aamas-topic-selection in your project. Codex loads it when a task matches its description.

Can I use Aamas Topic Selection in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aamas-topic-selection -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/aamas-topic-selection, .gemini/skills/aamas-topic-selection, .github/skills/aamas-topic-selection and .opencode/skills/aamas-topic-selection in your project.

What does Aamas Topic Selection need to run?

SKILL.md names no scripts, command-line tools or credentials: Aamas Topic Selection is instructions for the agent only.

Does Aamas Topic Selection access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Aamas Topic Selection safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Aamas Topic Selection use?

Aamas Topic Selection is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Aamas Topic Selection use?

About 952 tokens (SKILL.md is roughly 3.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Aamas Topic Selection?

Skills that share tags, products or a category with Aamas Topic Selection: Table Fit (asgeirtj/system_prompts_leaks, 69k stars), Furniture Fit Check (pascalorg/editor, 25k stars), Topics (ZimoLiao/scholaraio, 577 stars) and Topic Modeling (brycewang-stanford/Auto-Empirical-Research-Skills, 4.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Aamas Topic Selection?

brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,228 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.

Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.