neurips-review-process
Use when explaining or diagnosing the NeurIPS main-track review process, including OpenReview, reviewer and AC roles, contribution-type review, ethics flags, reciprocal reviewing, discussion, and LLM-review policy.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill neurips-review-process --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# NeurIPS Review Process Use this skill to reason about what reviewers and ACs are likely to do with a submission. Do not use it to infer acceptance odds from folklore; use it to identify decision-relevant weaknesses. ## Process model - Reviews happen in OpenReview under double blind. - Reviewers are asked to evaluate quality, clarity, significance, and the submission's declared contribution type. - ACs coordinate reviewers, handle conflicts and quality issues, write or supervise meta-reviews, and make recommendations. - Ethics concerns can be flagged and routed to ethics reviewers; severe cases can affect decisions. - Authors who are also reviewers or ACs face reciprocal-reviewing obligations; gross negligence can create sanctions affecting their own submissions. ## Reviewer mental model Reviewers are overloaded cross-area specialists. They need to see: - what the contribution is; - why it is new relative to close NeurIPS/ICML/ICLR/ACL/CVPR/KDD-style work; - whether the evidence supports the exact claim; - whether limitations, safety, data, and reproducibility are handled responsibly; - whether the paper can be trusted as a scientific artifact. ## Diagnosis workflow 1. Map each li
- Process model
- Reviewer mental model
- Diagnosis workflow
- Output format
What does the neurips-review-process skill do?
Use when explaining or diagnosing the NeurIPS main-track review process, including OpenReview, reviewer and AC roles, contribution-type review, ethics flags, reciprocal reviewing, discussion, and LLM-review policy.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill neurips-review-process --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.