acl-review-process

acl-review-process is a skill for Claude Code from brycewang-stanford/Awesome-Journal-Skills. It costs 62 tokens per session (1,317 once invoked), scanned A, original, MIT.

A guide to how papers move through ACL Rolling Review, a review system used by many computational-linguistics conferences. It explains the roles of reviewers, area chairs, senior area chairs, and program chairs, from submission through venue decisions.

In plain words
What is it for?
Use it to reason about ARR cycles, author responses, discussions, meta-reviews, conference commitment, Findings versus main-conference outcomes, and review-related strategy.
Why use it?
It helps authors understand which stage their paper is in, who has decision authority, and how a review package differs from a conference acceptance. It also covers responses, ethics escalation, and resubmission choices.

Skill for Claude Code

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

Part of the ACL-Skills plugin — 12 skills shipped together

Good fit Use it to reason about ARR cycles, author responses, discussions, meta-reviews, conference commitment, Findings versus main-conference outcomes, and review-related strategy.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/brycewang-stanford/awesome-journal-skills/acl-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 · 1,097 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 acl-review-process
Clone the repo
git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills

Made for: Claude Code.

Or install ACL-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 acl-review-process

README.md
[![agentmods](https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/acl-review-process/github.svg)](https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/acl-review-process)
Your own site
<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/acl-review-process"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/acl-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 acl-review-process

Your own site · 80×15
<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/acl-review-process"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/acl-review-process.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 62 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,317 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00062 $0.01317
Opus 5 $0.00031 $0.00659
Sonnet 5 $0.00012 $0.00263
Haiku 4.5 $0.00006 $0.00132

Measured 13d ago against content hash c392947d1494, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

acl-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 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.

ACL-Skills/skills/acl-review-process/SKILL.md · 120 lines

How it starts

The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ACL Review Process

Use this to model where an ACL paper actually is and who decides what next. ACL decoupled reviewing from the conference: ARR produces the review package; the conference consumes it. Confirm current mechanics at aclrollingreview.org/reviewing, since cycle structure has changed repeatedly (most recently to 10-week cycles in 2025).

The pipeline, stage by stage

  1. ARR cycle intake: submission on OpenReview to a dated cycle (e.g., ARR January 2026); checks for format, Limitations, checklist, anonymity.
  2. Review: at least three reviewers score and write reviews.
  3. Author response + discussion: authors reply; reviewers discuss and may update reviews (see acl-author-response).
  4. Meta-review: the action editor / area chair synthesizes reviews into a meta-review with a recommendation. Notably, ARR senior area chairs do not make accept/reject recommendations — that authority sits with the venue.
  5. Commitment: authors choose whether and where to send the finished package — ACL, or another *ACL venue accepting that cycle.
  6. Venue decision: the conference's senior area chairs and program chairs read reviews + meta-review and decide: main conference, Findings, or reject.
  7. Ethics branch: papers flagged during review go to an ethics committee, which can require revisions or recommend rejection on ACL Code of Ethics grounds independent of technical merit.

Who decides what

Actor Controls Cannot do
Reviewer Review text, scores, discussion updates Accept or reject anything
AC / action editor Meta-review, review-issue handling Bind the conference's decision
Author Response, revision, where/whether to commit Change reviews after the cycle closes
Venue SACs + PCs Main/Findings/reject from the ARR package Re-run the reviewing itself
Ethics committee Ethics-based conditions or rejection Judge technical contribution

Outcomes and what they mean

Read the full file on GitHub · 120 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. 13d ago First seen · 120 lines · 62 tokens per session scan A c392947d1494

Subscribe to this mod's changes

acl-review-process is a skill published in the GitHub repository brycewang-stanford/Awesome-Journal-Skills (1,097 stars, last pushed 16d ago), licensed MIT. It adds 62 tokens to every session and 1,317 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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