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 ccs-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/ccs-author-response)<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/ccs-author-response"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/ccs-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/ccs-author-response"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/ccs-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 | $0.00058 | $0.00777 |
| Opus 5 | $0.00029 | $0.00388 |
| Sonnet 5 | $0.00012 | $0.00155 |
| Haiku 4.5 | $0.00006 | $0.00078 |
Grade A, and why
ccs-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 12d 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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CCS Author Response
Use this after CCS reviews are released. Reopen the current HotCRP rebuttal instructions and any length or format limits before drafting, because response mechanics are set per cycle.
Triage
- Answer concerns that affect the decision: threat-model soundness, novelty, correctness, evidence quality, ethics, and disclosure. Skip cosmetic complaints unless space allows.
- Use evidence already in the submission: sections, appendices, measurement tables, and the ethics section. The rebuttal clarifies the submitted paper; it does not add a new paper.
- Keep the reply anonymous. Do not reveal institution, authorship, private URLs, or the identity of a disclosed vendor if that would deanonymize you.
- Correct factual misreadings first, then address the strongest objection to the attacker model or the adaptive evaluation.
- Do not promise experiments you cannot run before camera-ready; promise only edits that add no unsupported claim.
Drafting pattern
- State the decision-critical correction or concession in the first line.
- Point to exact submitted evidence (section, figure, appendix).
- Explain the security consequence — why the attack still holds, or the defense still binds.
- Offer a scoped camera-ready edit only where it clarifies without over-claiming.
Adversarial reviewer pushback patterns
| Pushback | What it signals | CCS-ready fix |
|---|---|---|
| "The attacker assumes too much" | The threat model looks unrealistic | Point to where the capability is justified, or scope the claim to the realistic subset and concede the rest |
| "You never tested an adaptive attacker" | The defense evaluation looks incomplete | Reference the adaptive experiment if present; if absent, concede and commit to a bounded camera-ready addition only if honestly feasible |
| "This is already a known CVE" | A prior-art gap | Distinguish root cause, scope, or impact from the CVE, with the specific technical delta |
| "The ethics of this are unaddressed" | Disclosure or harm concern | State the disclosure timeline, the harm-minimization steps, and the reasoning, quoting the ethics section |
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.
- 12d ago First seen · 68 lines · 58 tokens per session scan A fae2fa8a31f6
ccs-author-response is a skill published in the GitHub repository brycewang-stanford/Awesome-Journal-Skills (1,097 stars, last pushed 16d ago), licensed MIT. It adds 58 tokens to every session and 777 once invoked, about $0.0003 per session on Opus 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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