Awesome Journal Skills is a collection of agent skill packs tailored to hundreds of academic journals across fields including economics, social science, medicine, science, and engineering. Researchers use the packs for tasks such as choosing topics, designing empirical strategies, preparing tables and figures, submitting papers, and responding to reviewers. The catalogue entries are the project's journal-specific skills and related plugins.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aamas-writing-stylegit clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-SkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/aamas-writing-style)<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/aamas-writing-style"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/aamas-writing-style/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/aamas-writing-style"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/aamas-writing-style.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00068 | $0.00777 |
| Opus 5.5 | $0.00027 | $0.00311 |
| Sonnet 5.5 | $0.00014 | $0.00155 |
| Haiku 4.5 | $0.00007 | $0.00078 |
Grade A, and why
aamas-writing-style scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AAMAS Writing Style
Use this when revising the main paper. AAMAS papers need a compact statement of why an interaction result matters and enough detail for a game theorist and an empiricist to both validate it.
Revision rules
- Put the interaction contribution on the first page: the multiagent problem, why single-agent or centralized fixes fail, the mechanism or learning rule, the strategic property, and the evidence.
- Name the solution concept or incentive property (Nash, correlated, coarse-correlated, no-regret, dominant-strategy truthful, Pareto); an unnamed "equilibrium" is a review flag.
- Make the game legible: agents, actions, information structure, and payoffs stated once and clearly.
- Pair every major claim with a proof sketch, a self-play or population experiment, or a deployment result.
- Use the 8-page body for the core argument and push long proofs, extra opponents, and extended ablations to the appendix (references are unlimited, so cite generously).
- Keep double-blind wording in self-citations, prior-system references, acknowledgements, and artifact descriptions.
Interaction-first discipline
- State early why the result is genuinely multiagent - what breaks if the other agents are frozen into a static environment. If nothing breaks, the AAMAS framing does not hold.
- Give each theorem a body-level proof sketch; the appendix proof supports the sketch but never replaces it.
- Keep the game's information structure visible; who knows what and when is where multiagent proofs live or die.
- Separate a proved strategic property from an observed one; mixing "is truthful" and "appears cooperative" in one paragraph is a credibility leak here.
Sentence-level rewrites
| Draft pattern | AAMAS-safe rewrite |
|---|---|
| "Our agents outperform the baselines..." | "reduce social cost by X (SE Y) over Z seeds against held-out opponents" |
| "The agents reach equilibrium..." | "converge to a coarse-correlated equilibrium (Def. 2) under Assumptions 1-3" |
| "The mechanism is fair and efficient..." | "is dominant-strategy truthful (Thm. 1) with efficiency loss bounded by ... (Thm. 2)" |
| "In a multiagent setting..." | Name the game, the number of agents, and the information structure |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 66 lines · 68 tokens per session scan A 4b988ee4f66b
aamas-writing-style is a skill published in the GitHub repository brycewang-stanford/Awesome-Journal-Skills (1,320 stars, last pushed 1mo ago), licensed MIT. It adds 68 tokens to every session and 777 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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