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-camera-readygit 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-camera-ready)<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/ccs-camera-ready"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/ccs-camera-ready/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-camera-ready"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/ccs-camera-ready.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 | $0.00067 | $0.00811 |
| Opus 5 | $0.00034 | $0.00405 |
| Sonnet 5 | $0.00013 | $0.00162 |
| Haiku 4.5 | $0.00007 | $0.00081 |
Grade A, and why
ccs-camera-ready 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 13d 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CCS Camera Ready
Use this after acceptance or after clearing a minor revision. Reopen the current CCS camera-ready instructions, the ACM rights form, the registration page, and the notification or shepherd email before advising authors.
Camera-ready audit
- Convert the anonymous submission to the public proceedings version: author names, affiliations, acknowledgements, funding, and artifact links restored.
- Apply the ACM
sigconffinal template and the ACM rights-management block; the DOI, the conference reference string, and the copyright notice come from the ACM eRights system. - Incorporate exactly what the shepherd or the minor-revision decision required, without expanding the contribution beyond what was reviewed.
- Place any artifact-evaluation badges earned (Available, Functional, Reusable, Results Reproduced) as instructed; badge placement is part of the ACM camera-ready workflow.
- Confirm the final title and abstract match the HotCRP-registered title and abstract if the cycle froze them at registration.
- Coordinate disclosure timing: the public proceedings version and any released exploit or advisory should not appear before the agreed vendor-disclosure date.
Badge placement map
| Badge earned in artifact evaluation | Where it goes | What to confirm |
|---|---|---|
| Artifacts Available | First page, with the archival DOI/URL | The archive is public and permanent before camera-ready |
| Artifacts Evaluated - Functional | First page | The committee's functional result is final |
| Artifacts Evaluated - Reusable | First page | Documentation matches the reusable claim |
| Results Reproduced | First page | The reproduced results match the camera-ready numbers |
De-anonymization sweep
- Restore the author block, acknowledgements, grants, and contribution statements the anonymous version stripped.
- Rewrite third-person self-citations into natural first person where it improves clarity.
- Replace anonymized repository placeholders with the public, licensed, archived artifact and test every link from a logged-out browser.
- Re-check that de-anonymizing did not silently reveal an embargoed vendor before its patch.
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.
- 13d ago First seen · 76 lines · 67 tokens per session scan A dd00078914b1
ccs-camera-ready is a skill published in the GitHub repository brycewang-stanford/Awesome-Journal-Skills (1,097 stars, last pushed 16d ago), licensed MIT. It adds 67 tokens to every session and 811 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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