Agent skill

Aistats Review Process

by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills

A skill your agent uses when explaining or planning around AISTATS peer review, OpenReview review release, author-reviewer discussion, reviewer volunteer expectations, reviewer confidentiality…

MITAuto-check passedResearch & Science

Install Aistats Review Process

skills CLI
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aistats-review-process -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills aistats-review-process --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/AISTATS-Skills/skills/aistats-review-process .claude/skills/aistats-review-process && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
aistats-review-process
GitHub stars
1.2k
Token cost
~867 tokens
SKILL.md length
360 words
Files
1
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when explaining or planning around AISTATS peer review, OpenReview review release, author-reviewer discussion, reviewer volunteer expectations, reviewer confidentiality…

  • Planning around AISTATS peer review
  • SKILL.md covers Process model, Who reviews here, Scoring leverage table and Stage-by-stage realism, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • OpenReview review release

What it does

Aistats Review Process is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when explaining or planning around AISTATS peer review, OpenReview review release, author-reviewer discussion, reviewer volunteer expectations, reviewer confidentiality, decision criteria, meta-review dynamics, the statistician-heavy reviewer pool, and PMLR proceedings outcomes.

Its SKILL.md is about 870 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science, covering Peer review. The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. | 覆盖主流期刊的… The licence is MIT.

When your agent uses it

  • Planning around AISTATS peer review
  • OpenReview review release
  • Author-reviewer discussion
  • Reviewer volunteer expectations

Example prompts

  • “/aistats-review-process”

What it can do on your machine

Read from SKILL.md and the folder at commit 932eb23. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Aistats Review Process loads about 867 tokens when it runs. Until then it costs about 77 tokens; SKILL.md has 360 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~77
When it runs · the whole SKILL.md, loaded when a task matches
~867

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 360 words, ~867 tokens.

Download SKILL.mdSave it as .claude/skills/aistats-review-process/SKILL.md (or your agent's skills folder).
name
aistats-review-process
description
Use when explaining or planning around AISTATS peer review, OpenReview review release, author-reviewer discussion, reviewer volunteer expectations, reviewer confidentiality, decision criteria, meta-review dynamics, the statistician-heavy reviewer pool, and PMLR proceedings outcomes.

AISTATS Review Process

Use this to reason about review-stage strategy. Reopen the current CFP, OpenReview group, author instructions, reviewer instructions if posted, and code of conduct before making process claims.

Process model

  • AISTATS uses OpenReview for submission and review workflow in recent cycles.
  • Reviewers evaluate technical correctness, statistical and machine-learning contribution, empirical support, clarity, reproducibility, and relevance to artificial intelligence and statistics.
  • Author discussion is limited. AISTATS 2026 used a discussion period after initial reviews, with text-only author-reviewer discussion and no links.
  • Reviewer and author obligations include confidentiality, appropriate conflicts, professional conduct, and respect for anonymity.
  • The most useful response is a decision-focused clarification that gives the area chair or meta-reviewer a clean rationale for acceptance or rejection.
  • Accepted papers are published in PMLR, so final metadata and camera-ready compliance matter as much as the initial acceptance.

Who reviews here

  • The pool mixes ML researchers with statisticians and statistical learning theorists; expect at least one reviewer to read proofs and assumption sets line by line.
  • Because AISTATS is smaller and more specialized than NeurIPS or ICML, topical matches are closer, so vague proof sketches get caught rather than skimmed past.
  • Borderline theory-plus-experiments papers usually fall on one of three edges: an assumption the experiments do not satisfy, a missing classical-statistics baseline, or a rate claim never checked empirically.
Show full SKILL.md (142 more words)Show less

Scoring leverage table

Review dimensionWhat raises itWhat sinks it
CorrectnessComplete assumption statements with a main-text proof sketchHidden conditions; constants swept into O-notation when they matter
SignificanceA guarantee the ML literature lacked, or a practical method statistics lackedIncremental rate gain with no conceptual or practical payoff
Empirical supportExperiments engineered to probe the theoryBenchmarks disconnected from the theorem regimes
ClarityNumbered assumptions and a single notation sourceNotation collisions between sections

Stage-by-stage realism

  • Initial reviews: triage by what the meta-reviewer would weigh, not by reviewer tone.
  • Discussion: windows are short; an early, precise reply is worth more than a late comprehensive one.
  • Decision: the meta-review synthesizes; one unanswered correctness objection outweighs several resolved clarity complaints.
  • Reviewer-volunteer expectations for submitting authors have appeared in recent cycles; confirm the current CFP rather than assuming either way.

Output format

text
[Current stage] submitted / reviews / discussion / decision / camera-ready
[Decision actors] <reviewers/meta-reviewer/chairs>
[Likely leverage] <correctness/statistics/experiments/clarity/reproducibility>
[Forbidden moves] <identity leak / external links if forbidden / new unsupported results>
[Next response move] <one action>

© brycewang-stanford, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in AISTATS-Skills/skills/aistats-review-process of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

Compare with similar skills

Aistats Review Process next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Aistats Review Process compared with similar skills
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Aistats Review Process this skillbrycewang-stanford/Awesome-Journal-Skills1.2k—~867Automated safety check: PassMIT
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Scholar Evaluationspacering-net/codeg3.9k11 repos~3.2kAutomated safety check: PassMIT
Academic Paper Writing PipelineImbad0202/academic-research-skills51k—~16kAutomated safety check: PassCustom licence
Academic Paper ReviewerImbad0202/academic-research-skills51k—~11kAutomated safety check: PassCustom licence
Peer ReviewK-Dense-AI/claude-scientific-writer2.4k2 repos~3.1kAutomated safety check: NotesMIT

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Questions about Aistats Review Process

What does Aistats Review Process do?

A skill your agent uses when explaining or planning around AISTATS peer review, OpenReview review release, author-reviewer discussion, reviewer volunteer expectations, reviewer confidentiality…. Aistats Review Process is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when explaining or planning around AISTATS peer review, OpenReview review release, author-reviewer discussion, reviewer volunteer expectations, reviewer confidentiality, decision criteria, meta-review dynamics, the statistician-heavy reviewer pool, and PMLR proceedings outcomes.

When should I use Aistats Review Process?

Aistats Review Process fits situations like: planning around AISTATS peer review; openReview review release; author-reviewer discussion; reviewer volunteer expectations.

How do I install Aistats Review Process in Claude Code?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aistats-review-process -a claude-code`. Or copy the skill folder (AISTATS-Skills/skills/aistats-review-process in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/aistats-review-process in your project. Claude Code loads it when a task matches its description.

How do I install Aistats Review Process in Codex?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aistats-review-process -a codex`. Or copy the skill folder (AISTATS-Skills/skills/aistats-review-process in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/aistats-review-process in your project. Codex loads it when a task matches its description.

Can I use Aistats Review Process in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aistats-review-process -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/aistats-review-process, .gemini/skills/aistats-review-process, .github/skills/aistats-review-process and .opencode/skills/aistats-review-process in your project.

What does Aistats Review Process need to run?

SKILL.md names no scripts, command-line tools or credentials: Aistats Review Process is instructions for the agent only.

Does Aistats Review Process access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Aistats Review Process safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Aistats Review Process use?

Aistats Review Process is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Aistats Review Process use?

About 867 tokens (SKILL.md is roughly 3.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Aistats Review Process?

Skills that share tags, products or a category with Aistats Review Process: Peer Review (spacering-net/codeg, 3.9k stars), Scholar Evaluation (spacering-net/codeg, 3.9k stars), Academic Paper Writing Pipeline (Imbad0202/academic-research-skills, 51k stars) and Academic Paper Reviewer (Imbad0202/academic-research-skills, 51k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Aistats Review Process?

brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,231 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.

Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.