aaai-review-process
Use when explaining or planning around AAAI's two-phase review process, Phase 1 rejection risk, Phase 2 additional reviews, AI-assisted review pilot, author feedback, SPC/AC discussion, and final decisions.
Install / Use
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aaai-review-processInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Development & EngineeringSupported Platforms
Our assessment of aaai-review-process
aaai-review-process scores 83/100 on our quality scale, 2893rd of 4,610 Development & Engineering skills we index.
Its SKILL.md is 3.7 KB long, split into 7 sections with 1 code example: a solid amount of guidance for an agent.
With 1,158 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 18 days ago, so aaai-review-process is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
aaai-review-process compared with similar skills
All 4 of these similar skills score higher than aaai-review-process; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| aaai-review-process (this skill)by brycewang-stanford | 83 | 1.2k | 18d ago | SKILL.md |
| ai-job-searchby MadsLorentzen | 100 | 44.8k | today | CLAUDE.md |
| claude-howtoby luongnv89 | 100 | 41.7k | 3d ago | CLAUDE.md |
| algorithmic-artby anthropics | 100 | 177.9k | 10d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 10d ago | SKILL.md |
Frequently asked questions
- How do I install aaai-review-process?
- Run
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aaai-review-process. The install tabs above show the steps for each supported agent. - Which AI agents does aaai-review-process work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is aaai-review-process safe to use?
- It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is aaai-review-process still maintained?
- The repository was last updated 18 days ago, so aaai-review-process is actively maintained.
Skill content
View source on GitHubname: aaai-review-process description: Use when explaining or planning around AAAI's two-phase review process, Phase 1 rejection risk, Phase 2 additional reviews, AI-assisted review pilot, author feedback, SPC/AC discussion, and final decisions.
AAAI Review Process
Use this to plan around AAAI review rather than treating it as a generic OpenReview rebuttal. Reopen the current review-process page and author FAQ before advising on timing or strategy.
Process model
- AAAI main technical track uses double-blind reviewing.
- AAAI-27 uses a two-phase review process. Phase 1 allocates three reviewers — two human reviews supplemented by one non-decisional AI-generated review. Papers with sufficiently negative reviews are rejected before author feedback (AAAI-27: notified 2026-09-24).
- Papers continuing to Phase 2 receive additional reviews, up to five in total, and one author feedback phase (AAAI-27: 2026-10-19 to 10-25, final decisions 2026-11-30). Phase 2 reviewers are not shown the Phase 1 reviews until they have submitted their own — so a Phase 2 review is an independent read, not a reaction to the earlier ones.
- Final decisions were made through reviewer discussion and senior program committee oversight, not by the AI review.
- Author feedback is short and constrained; it is mainly for correcting misunderstandings, not replacing the paper.
Author strategy
- Reduce Phase 1 reject risk before submission by making contribution, evidence, and checklist compliance obvious.
- When reviews arrive, distinguish human-review claims, AI-review errors, and AC/SPC decision questions.
- Use rebuttal to resolve the highest-impact factual issue under the character limit.
- Do not attack the AI review. Correct it when it contains consequential false statements.
- Avoid new experiments in rebuttal; use submitted evidence and camera-ready promises sparingly.
Stage-by-stage decision map
AAAI's pipeline differs from a single-round OpenReview venue, so plan actions per stage rather than treating every signal as a rebuttal opportunity.
| Stage | What is happening | Author leverage | | --- | --- | --- | | Pre-submission | Phase-1 bar is set by clarity and checklist | maximal: fix the paper itself | | Phase 1 | human reviews plus advisory AI review | none yet; summary reject possible | | Phase 2 | additional reviews, one feedback round | one short response, no new results | | Discussion | reviewers and SPC/AC weigh feedback | indirect: a clean correction can swing it | | Decision | SPC/AC oversight, not the AI review | archive everything for appeal or journal |
Why papers die in Phase 1
Because the reviewer pool is large and submission volume is high, clearly-below-bar papers are cut early to protect later effort. Common triggers: an unreadable first page, a contribution a non-specialist cannot place, a checklist that contradicts the paper, or evidence too thin to trust. None of these can be repaired after the Phase-1 cut, so they must be eliminated before submission.
Worked vignette
An NLP paper with strong results buries its contribution under three pages of setup. A Phase-1 reviewer from a planning background cannot find the AI claim and scores it a reject; the paper never reaches feedback. The fix belongs entirely pre-submission: a first-page contribution statement and a checklist that matches the experiments, so the broad-AI reviewer can place and trust it fast.
Output format
[Stage] pre-submission / Phase 1 / Phase 2 / rebuttal / discussion / decision
[Decision risk] summary reject / borderline / likely accept / ethics-policy risk
[Best action] revise before submission / rebut / clarify evidence / escalate
[AI-review handling] ignore / correct / cite submitted evidence
[Rationale] <why this fits AAAI process>
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
