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 acmmm-supplementarygit 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/acmmm-supplementary)<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/acmmm-supplementary"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/acmmm-supplementary/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/acmmm-supplementary"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/acmmm-supplementary.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 | $0.00072 | $0.01064 |
| Opus 5.5 | $0.00029 | $0.00426 |
| Sonnet 5.5 | $0.00014 | $0.00213 |
| Haiku 4.5 | $0.00007 | $0.00106 |
Grade A, and why
acmmm-supplementary 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ACM MM Supplementary Material
Use this to plan the ACM Multimedia supplement, which has its own deadline after the paper (in 2026, April 8 versus the April 1 paper deadline). For a multimedia paper the supplement is not an afterthought — it is where the video, audio, and interactive evidence lives.
Body vs. supplement split
The 6–8 page sigconf body carries the argument; the supplement carries what the argument rests on but cannot fit.
| Content | Body | Supplement |
|---|---|---|
| Core claim, main results table, teaser | Yes | — |
| The two or three decisive media examples | Yes (stills/short) | Full clips |
| Extra qualitative media across conditions | — | Yes |
| Full user-study protocol and per-rater data | Summary only | Yes |
| Hyperparameters, extra ablations, proofs | Pointer only | Yes |
| Code / data pointers | Named | Yes |
A reviewer must be able to follow the body without the supplement; the supplement then confirms rather than completes the argument.
Packaging media that actually plays
The single most common ACM MM supplement failure is media a reviewer cannot open.
video: H.264/MP4, standard resolution, plays in a browser/VLC; no exotic codec
audio: WAV or MP3; label each clip with the claim it supports
demo: if interactive, provide a recorded fallback video — do not assume the reviewer runs it
size: keep within the cycle's stated limit; compress rather than omit evidence
index: a short README mapping each file to the paper claim/figure it supports
Anonymity for double-blind tracks
- Strip author names from filenames, EXIF/media metadata, and any on-screen watermark or slate.
- Remove identifying voices/faces of the authors from demo videos where they would reveal identity, or note that they are incidental.
- Route dataset and code links through an anonymous mirror; a personal or lab URL is a leak.
- The Reproducibility, Open Source Software, and Dataset tracks are single-blind and do not need this — but the main track and Brave New Ideas do.
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 · 100 lines · 72 tokens per session scan A a2d0cbc6bd26
acmmm-supplementary is a skill published in the GitHub repository brycewang-stanford/Awesome-Journal-Skills (1,320 stars, last pushed 1mo ago), licensed MIT. It adds 72 tokens to every session and 1,064 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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