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-author-responsegit 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-author-response)<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/aamas-author-response"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/aamas-author-response/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-author-response"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/aamas-author-response.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 | $0.00071 | $0.00819 |
| Opus 5.5 | $0.00028 | $0.00328 |
| Sonnet 5.5 | $0.00014 | $0.00164 |
| Haiku 4.5 | $0.00007 | $0.00082 |
Grade A, and why
aamas-author-response 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 — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
- State the decision-critical correction or concession in the first line.
- Point to the exact submitted evidence (section, figure, appendix, or theorem number).
- Explain the strategic or empirical consequence for the reviewer's concern.
- 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.
| Pushback | What it signals | AAMAS-ready fix |
|---|---|---|
| "This is really a single-agent method" | The interaction claim did not land | Point 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 concept | Name it (Nash / correlated / coarse / no-regret) and cite the proof or convergence plot |
| "Baselines are self-play only" | Opponent set looks weak | Anchor 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 rigor | Reference the seeded runs and standard errors; do not promise new experiments as fact |
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 · 72 lines · 71 tokens per session scan A 916769fc07e8
aamas-author-response is a skill published in the GitHub repository brycewang-stanford/Awesome-Journal-Skills (1,320 stars, last pushed 1mo ago), licensed MIT. It adds 71 tokens to every session and 819 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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