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 ase-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/ase-author-response)<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/ase-author-response"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/ase-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/ase-author-response"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/ase-author-response.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00069 | $0.01248 |
| Opus 5.5 | $0.00028 | $0.00499 |
| Sonnet 5.5 | $0.00014 | $0.00250 |
| Haiku 4.5 | $0.00007 | $0.00125 |
Grade A, and why
ase-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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ASE Author Response
Use this after ASE reviews are released. ASE has two distinct speaking turns, and conflating them is a common mistake: a short rebuttal (for papers that survive the early-rejection gate), and — if you receive a Revision — a summary-of-changes accompanying a revised paper that is re-checked against the reviewers' explicitly stated criteria. Both must respect double-anonymity: no author names, institutions, or revealed repository ownership, even to strengthen a point.
Triage (both turns)
- Answer what affects the decision: significance and soundness of the automation, evaluation quality on real subjects, threats to validity, clarity, and the Data Availability / artifact posture.
- Use evidence that already exists or that the revision will concretely add — never a vague promise.
- Correct factual misreadings first; a reviewer who misread your tool's configuration or a table is often persuadable.
- Keep every word anonymous. Do not name your tool's real name, institution, grant, or a private repository.
Turn 1 — the rebuttal (only if you survived early rejection)
If your paper reached the rebuttal stage, at least one reviewer saw value; a uniformly negative set would have been early-rejected. So the rebuttal's job is narrow: move the borderline reviewer.
- Short and decision-focused. One decision-critical point per reviewer beats an exhaustive reply.
- Concede what is true, correct what is misread, and point to exactly where the answer lives in the submitted paper or artifact.
- Do not paste large new results the reviewers cannot verify; if a small, checkable number answers a direct question ("what is the runtime overhead?"), give it.
- Signal what you would do in a revision, because Revision is a live outcome — but do not promise a redesign you cannot deliver in the window.
Turn 2 — the revision summary-of-changes (the distinctive ASE move)
A Revision is criteria-bound: the reviewers wrote concrete, actionable criteria and agreed to accept in principle if they are met. The summary-of-changes is a criterion ledger: for every stated criterion, either meet it and show where, or explain precisely why it is infeasible and what you did instead.
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 · 94 lines · 69 tokens per session scan A 8e586a57cc3e
ase-author-response is a skill published in the GitHub repository brycewang-stanford/Awesome-Journal-Skills (1,289 stars, last pushed 26d ago), licensed MIT. It adds 69 tokens to every session and 1,248 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 2026-09-15.
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