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 asplos-review-processgit 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/asplos-review-process)<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/asplos-review-process"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/asplos-review-process/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/asplos-review-process"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/asplos-review-process.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 | $0.01512 |
| Opus 5 | $0.00034 | $0.00756 |
| Sonnet 5 | $0.00014 | $0.00302 |
| Haiku 4.5 | $0.00007 | $0.00151 |
Grade A, and why
asplos-review-process 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 today.
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 — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ASPLOS Review Process
ASPLOS 2027 runs a staged pipeline that differs from every sibling venue in two places: an explicit rapid-review screen on the first two pages, and a Major Revision outcome with journal-like mechanics. Everything below is the 2027 cycle as verified 2026-07-08; stage design is re-decided per edition.
Stage map
| Stage | Who reads what | Author leverage |
|---|---|---|
| Rapid review | Committee members read pages 1-2 only, double-blind | Total — you wrote those pages |
| Full review | Full paper, double-blind, multiple reviewers | High before submission, zero during |
| Author response | Reviews + your rebuttal (reading expectation ≈ 800 words) | Moderate — corrections and answers land |
| Decision | Accept / Major Revision / Reject | None |
| Revision re-review | Revised paper + change note, judged as a submission | High — the requirements are written down |
What the rapid review is for — in the CFP's own framing
The 2027 CFP models the screen on early triage at high-impact journals: most submissions may not advance past it, and the point is to concentrate expert reviewer effort on papers where the committee can review with high confidence. Two consequences for authors:
- The screen prioritizes work at the architecture-languages-OS intersection. A paper that reads like a pure single-community result in its first two pages is the archetypal rapid casualty, whatever its page-7 content.
- Rapid rejection is cheap and fast for the PC but carries little diagnostic signal for you beyond "the first two pages did not make the case." Re-aim the framing before re-aiming the venue.
Full review: what systems-intersection reviewers probe
A useful red-team script — have a non-author run it against the submitted PDF:
R1 Is the claimed coupling real? Try to mentally re-implement each half
without the other; if either succeeds, expect a "why not <single venue>?"
R2 Is the baseline the strongest deployed alternative, tuned, on the same
platform? Find one stronger baseline the paper skipped.
R3 Does the evidence class match the claim (silicon vs FPGA vs simulator)?
Flag any latency/energy claim resting on an unvalidated model.
R4 Attribution: is the win traced to the mechanism via ablation, or asserted?
R5 Generality: does anything survive a workload/technology parameter change?
R6 Are the citation and formatting rules met? (Reviewers do notice.)
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.
- today First seen · 129 lines · 69 tokens per session scan A 447e9ed50a22
asplos-review-process is a skill published in the GitHub repository brycewang-stanford/Awesome-Journal-Skills (1,109 stars, last pushed yesterday), licensed MIT. It adds 69 tokens to every session and 1,512 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 2026-09-15.
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