asplos-review-process

asplos-review-process is a skill for Claude Code from brycewang-stanford/Awesome-Journal-Skills. It costs 69 tokens per session (1,512 once invoked), scanned A, original, MIT.

A guide to how ASPLOS reviews a paper, including an initial two-page screen, full double-blind review, an author response, and possible Accept, Major Revision, or Reject decisions. Double-blind review means reviewers and authors are kept anonymous to each other.

In plain words
What is it for?
Use it to plan the first two pages, prepare for full review, write the author response, and organize a revision and its change note.
Why use it?
It shows what reviewers read at each stage and where authors can still address problems. It also explains that a Major Revision is reviewed again as a submission rather than treated as an automatic acceptance.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the asplos-skills plugin — 12 skills shipped together

Good fit Use it to plan the first two pages, prepare for full review, write the author response, and organize a revision and its change note.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/brycewang-stanford/awesome-journal-skills/asplos-review-process
About the project

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.

brycewang-stanford/Awesome-Journal-Skills · 1,372 stars · on GitHub · copaper.ai

Install

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.

Any agent
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill asplos-review-process
Clone the repo
git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills

Made for: Claude Code.

Or install asplos-skills, the plugin that ships this one along with the rest of its 12 skills.

Wrote 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.

agentmods badge for asplos-review-process

README.md
[![agentmods](https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/asplos-review-process/github.svg)](https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/asplos-review-process)
Your own site
<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.

agentmods 80×15 button for asplos-review-process

Your own site · 80×15
<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>
Per session 69 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,512 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00069 $0.01512
Opus 5.5 $0.00028 $0.00605
Sonnet 5.5 $0.00014 $0.00302
Haiku 4.5 $0.00007 $0.00151

Measured 1mo ago against content hash 447e9ed50a22, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 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.

ASPLOS-Skills/skills/asplos-review-process/SKILL.md · 129 lines

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.)

Read the full file on GitHub · 129 lines

Changes

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.

  1. 1mo ago First seen · 129 lines · 69 tokens per session scan A 447e9ed50a22

Subscribe to this mod's changes

asplos-review-process is a skill published in the GitHub repository brycewang-stanford/Awesome-Journal-Skills (1,372 stars, last pushed 1mo ago), licensed MIT. It adds 69 tokens to every session and 1,512 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.

Related

asplos-review-process compared with skills from other repositories

asplos-review-process next to 6 skills from other repositories
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asplos-review-processbrycewang-stanford/Awesome-Journal-SkillsSkill1.4k1mo agoMITA69Claude Code
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fin-submit-checkcsmar432/finai-researchSkill1093d agoMITA37Claude Code, Codex
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