Peer Review
spacering-net/codeg
Structured manuscript/grant review with checklist-based evaluation.
A skill your agent uses when reasoning about UAI peer review on OpenReview, including bidding, double-blind evaluation against the correctness, novelty, backing, and clarity criteria, the…
Install Uai Review Process
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill uai-review-process -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills uai-review-process --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/UAI-Skills/skills/uai-review-process .claude/skills/uai-review-process && rm -rf skills-srcUse ~/.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/
Install the "uai-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/UAI-Skills/skills/uai-review-process into .claude/skills/uai-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uai-review-process", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/UAI-Skills/skills/uai-review-processType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill uai-review-process -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills uai-review-process --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/UAI-Skills/skills/uai-review-process .agents/skills/uai-review-process && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "uai-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/UAI-Skills/skills/uai-review-process into .agents/skills/uai-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uai-review-process", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill uai-review-process -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills uai-review-process --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/UAI-Skills/skills/uai-review-process .cursor/skills/uai-review-process && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "uai-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/UAI-Skills/skills/uai-review-process into .cursor/skills/uai-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uai-review-process", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/brycewang-stanford/Awesome-Journal-Skills.git --path UAI-Skills/skills/uai-review-process--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill uai-review-process -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills uai-review-process --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/UAI-Skills/skills/uai-review-process .gemini/skills/uai-review-process && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "uai-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/UAI-Skills/skills/uai-review-process into .gemini/skills/uai-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uai-review-process", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills uai-review-processInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill uai-review-process -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/UAI-Skills/skills/uai-review-process .github/skills/uai-review-process && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "uai-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/UAI-Skills/skills/uai-review-process into .github/skills/uai-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uai-review-process", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill uai-review-process -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills uai-review-process --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/UAI-Skills/skills/uai-review-process .opencode/skills/uai-review-process && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "uai-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/UAI-Skills/skills/uai-review-process into .opencode/skills/uai-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uai-review-process", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
uai-review-process- GitHub stars
- 1.2k
- Token cost
- ~1.8k tokens
- SKILL.md length
- 847 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when reasoning about UAI peer review on OpenReview, including bidding, double-blind evaluation against the correctness, novelty, backing, and clarity criteria, the…
- Reasoning about UAI peer review on OpenReview
- SKILL.md covers The 2026 pipeline, stage by…, Matching is an…, Who reviews at UAI and Scale and format context, plus 6 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Including bidding
What it does
Uai Review Process is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when reasoning about UAI peer review on OpenReview, including bidding, double-blind evaluation against the correctness, novelty, backing, and clarity criteria, the author-response window, the reviewer-and-area-chair discussion that follows it, decision timing, spotlight versus poster outcomes, and PMLR publication of accepted papers.
Its SKILL.md is about 1.8k 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
- Reasoning about UAI peer review on OpenReview
- Including bidding
- Double-blind evaluation against the correctness
- Clarity criteria
Example prompts
- “/uai-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
Uai Review Process loads about 1.8k tokens when it runs. Until then it costs about 90 tokens; SKILL.md has 847 words of instructions outside code blocks.
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). 847 words, ~1,794 tokens.
Download SKILL.mdSave it as
.claude/skills/uai-review-process/SKILL.md (or your agent's skills folder).- name
- uai-review-process
- description
- Use when reasoning about UAI peer review on OpenReview, including bidding, double-blind evaluation against the correctness, novelty, backing, and clarity criteria, the author-response window, the reviewer-and-area-chair discussion that follows it, decision timing, spotlight versus poster outcomes, and PMLR publication of accepted papers.
UAI Review Process
Use this to model what happens to a UAI submission after upload, and to time author effort where it changes outcomes. Stage dates below are the published 2026 pipeline (verified 2026-07-08); the shape tends to persist across cycles, the dates never do.
The 2026 pipeline, stage by stage
| Stage | 2026 window | Who acts | Author leverage |
|---|---|---|---|
| Submission closes | Feb 25 (AoE) | Authors | Total — last moment anything enters the record |
| Bidding | Mar 2–9 | SACs, ACs, reviewers | Indirect: title, abstract, subject areas drive matching |
| Review writing | Mar 21 – Apr 11 | Reviewers | None — the paper speaks alone |
| Author response | Apr 23 – May 2 | Authors | High on misreadings; low on true weaknesses |
| Reviewer–AC discussion | May 2–8 | Reviewers + ACs | Only via the response already filed |
| Notification | Jun 1 | Program Chairs | None |
| Camera-ready | Jul 27 | Authors | Presentation of accepted content |
| Conference | Aug 17–21 | Everyone | Talks, posters, corridor conversations — reputation, not decision |
Note the gaps: reviews are written weeks before authors see them, and the decisive reviewer–AC conversation happens after authors go silent. Both asymmetries reward papers and responses that anticipate objections rather than react to them.
Matching is an author-controlled variable
Bidding means your title, abstract, and subject-area selections are routing decisions. An abstract that says "probabilistic" but hides the causal-identification core will be bid on by the wrong reviewers, and misrouted reviews are the hardest to respond to. Choose OpenReview subject areas to describe what a reviewer must know to verify the paper, not what makes it sound broad.
Who reviews at UAI
The pool concentrates on probabilistic inference, graphical models, causality, Bayesian statistics, decision theory, and learning theory. The 2026 reviewer instructions asked reviewers to state clearly what clarification they want from authors — expect direct, technical questions. Planning consequences:
- At least one reader will attempt your proofs or re-derive your estimator. Write assumption chains for verification, not persuasion.
- Empirical-only papers face a pool that instinctively asks "where is the uncertainty in your uncertainty estimate?" — variance reporting is table stakes.
- The author agreement (one author reviews if asked) means your own team may be inside someone else's pipeline simultaneously; wall off conflicts early and honor confidentiality both ways — review misconduct falls under the AUAI code of conduct.
Scale and format context
UAI is a compact meeting by ML-conference standards — each edition fits a single PMLR volume (2025: v286), far smaller than NeurIPS-scale venues. Practically: your paper is likelier to be read by people who work on exactly its topic, reviewer anonymity is thinner in niche subfields (write accordingly), and poster sessions carry real technical conversation. Session structure and track layout are set per edition — verify rather than assume.
Reading a UAI decision
Accepted papers are all presented as posters plus spotlights (physically or remotely in 2026), with longer slots for selected papers. So an acceptance may arrive with a presentation-format distinction; treat a longer slot as a visibility bonus, not a different publication class — the PMLR volume records all accepted papers identically.
For rejections, extract signal by axis:
Post-decision triage (fill one line per review):
R1: axis=correctness fixable=yes action=repair Lemma 2 edge case before resubmission
R2: axis=backing fixable=yes action=add multi-seed study + calibration curves
R3: axis=novelty fixable=no action=re-scope contribution or change venue
→ If any "novelty, fixable=no" comes from a correct reading, the next venue decision
matters more than any revision (see uai-topic-selection).Show full SKILL.md (352 more words)Show less
What authors see versus what actually happens
Planning improves when the hidden half of the pipeline is explicit:
- Visible to authors: the submission form, the reviews when released, the response box, the decision, and (post-decision) the meta-review if issued.
- Hidden from authors: bidding outcomes and assignment quality; reviewer confidence scores as ACs weigh them; the May reviewer–AC discussion; how borderline stacks are ranked at the program level.
- Consequences: you cannot fix a bad assignment after bidding — only prevent it via abstract and subject areas; you cannot join the May discussion — only arm it with a response ACs can quote; you cannot appeal taste — only demonstrable factual error, through the chairs.
Signals to log for the next cycle
Whatever the outcome, the review set is calibration data about how this venue reads your group's work. Record: which criterion drew the most text; whether the appendix was demonstrably read; which baselines reviewers asked for unprompted; which subject-area choices produced well-matched reviewers. Two cycles of such notes outperform any generic advice about "what UAI wants".
If the process misfires
- A review that misstates what the paper does (not disputes — misstates) is response-window material: quote the submission, politely, with locations.
- A review that appears to have skipped the appendix proofs is still your problem to solve: restate the two-line version in the response and point at the full argument.
- Suspected conflicts, plagiarized review text, or conduct issues go to the program chairs privately — never into the public forum thread.
- After a final decision, the productive appeal is a better paper at the next venue; UAI has no rolling revise-and-resubmit track.
Confidentiality and conduct boundaries
- Submissions are confidential inputs to the process; do not quote reviews publicly or contact reviewers. Escalation path is the program chairs (uai2026chairs+program address for that cycle).
- The AUAI code of conduct covers the review ecosystem, official communication channels, and social media, and names fabrication, falsification, and plagiarism as misconduct.
- LLM-use policy for authors or reviewers was not published for 2026 (待核实); where a cycle is silent, default to the confidentiality rule — no feeding others' submissions or reviews into external services.
Output format
[Stage now] pre-submission / under review / response window / awaiting decision / decided
[Days to next transition] <n, from the current official dates>
[Routing quality] subject areas + abstract match actual verifiers?
[Predicted objection axes] <correctness / novelty / backing / clarity, ranked>
[Process risks] <conflicts, confidentiality, volunteer-reviewer load>© 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 UAI-Skills/skills/uai-review-process of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Uai 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Uai Review Process this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.8k | Automated safety check: Pass | MIT | |
| Peer Reviewspacering-net/codeg | 3.9k | 17 repos | ~5.9k | Automated safety check: Notes | MIT | |
| Scholar Evaluationspacering-net/codeg | 3.9k | 11 repos | ~3.2k | Automated safety check: Pass | MIT | |
| Academic Paper Writing PipelineImbad0202/academic-research-skills | 51k | — | ~16k | Automated safety check: Pass | Custom licence | |
| Academic Paper ReviewerImbad0202/academic-research-skills | 51k | — | ~11k | Automated safety check: Pass | Custom licence | |
| Peer ReviewK-Dense-AI/claude-scientific-writer | 2.4k | 2 repos | ~3.1k | Automated safety check: Notes | MIT |
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Peer Review
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Questions about Uai Review Process
What does Uai Review Process do?
A skill your agent uses when reasoning about UAI peer review on OpenReview, including bidding, double-blind evaluation against the correctness, novelty, backing, and clarity criteria, the…. Uai Review Process is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when reasoning about UAI peer review on OpenReview, including bidding, double-blind evaluation against the correctness, novelty, backing, and clarity criteria, the author-response window, the reviewer-and-area-chair discussion that follows it, decision timing, spotlight versus poster outcomes, and PMLR publication of accepted papers.
When should I use Uai Review Process?
Uai Review Process fits situations like: reasoning about UAI peer review on OpenReview; including bidding; double-blind evaluation against the correctness; clarity criteria.
How do I install Uai Review Process in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill uai-review-process -a claude-code`. Or copy the skill folder (UAI-Skills/skills/uai-review-process in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/uai-review-process in your project. Claude Code loads it when a task matches its description.
How do I install Uai Review Process in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill uai-review-process -a codex`. Or copy the skill folder (UAI-Skills/skills/uai-review-process in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/uai-review-process in your project. Codex loads it when a task matches its description.
Can I use Uai 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 uai-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/uai-review-process, .gemini/skills/uai-review-process, .github/skills/uai-review-process and .opencode/skills/uai-review-process in your project.
What does Uai Review Process need to run?
SKILL.md names no scripts, command-line tools or credentials: Uai Review Process is instructions for the agent only.
Does Uai 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 Uai 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 Uai Review Process use?
Uai 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 Uai Review Process use?
About 1.8k tokens (SKILL.md is roughly 7.2k 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 Uai Review Process?
Skills that share tags, products or a category with Uai 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 Uai 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.