SkillHub

openreview-review-analyzer

v1.0.1

Fetch and analyze peer reviews from OpenReview for any academic paper. Use this skill when the user mentions OpenReview, asks about reviews for a paper, wants a review summary or synthesis, provides an openreview.net URL, mentions a paper forum ID, asks about reviewer opinions or scores for a confer...

Sourced from ClawHub, Authored by Vector

Installation

Please help me install the skill `openreview-review-analyzer` from SkillHub official store. npx skills add vectorsss/openreview-review-analyzer

OpenReview Review Analyzer

Fetch all public peer reviews for any paper on OpenReview and generate a structured synthesis report.

When to Use

  • User provides an OpenReview URL (e.g., https://openreview.net/forum?id=XXXXX)
  • User asks to analyze or summarize reviews for a conference paper
  • User mentions a paper's OpenReview forum ID
  • User wants to understand reviewer consensus, disagreements, or key concerns
  • User asks about scores, ratings, or review content for any venue on OpenReview

Workflow

Step 1: Extract Forum ID

Parse the OpenReview URL or forum ID from user input. The forum ID is the id parameter in the URL: - https://openreview.net/forum?id=xxxxxxx → forum ID = xxxxxxx

Step 2: Fetch Reviews via Script

Run the Python script to fetch all reviews and metadata:

python3 {baseDir}/scripts/fetch_reviews.py <forum_id>

The script has zero external dependencies — it uses Python's built-in urllib. If requests is installed it will use that instead, but it's not required.

The script outputs a JSON file at /tmp/openreview_<forum_id>.json containing: - Paper metadata (title, authors, abstract, venue, keywords) - All official reviews with ratings, confidence, strengths, weaknesses, questions, and full review text - All official comments (author responses, reviewer discussions) - Meta-review if available

If the script fails (e.g., network restrictions, reviews not public, paper withdrawn), use these fallback methods in order:

Fallback 1 — web_fetch the API directly:

web_fetch https://api2.openreview.net/notes?forum=<forum_id>

Parse the JSON response to get the submission, then:

web_fetch https://api2.openreview.net/notes?forum=<forum_id>&trash=true

to get all replies including reviews. Filter replies where invitations contains Official_Review.

Fallback 2 — web_search for review content: Search for "<forum_id>" review site:openreview.net or "<paper_title>" review <venue> to find discussions, blog posts, or cached review content.

Fallback 3 — inform the user: If no review data is accessible, explain that reviews may not be public yet, or suggest the user check the OpenReview page directly.

Step 3: Generate Synthesis Report

Read the JSON output and produce a structured report following {baseDir}/references/report-template.md.

Key analysis points: 1. Score Distribution — list each reviewer's rating and confidence, compute average 2. Consensus Points — identify strengths/weaknesses mentioned by multiple reviewers 3. Key Disagreements — where reviewers diverge in opinion 4. Critical Issues — weaknesses flagged as major by any reviewer 5. Questions Raised — important unresolved questions 6. Author Responses — summarize rebuttal if available, and whether reviewers updated scores 7. Meta-Review — include AC recommendation if available 8. Overall Assessment — synthesize into a clear verdict

Important Notes

  • OpenReview content is public for completed review cycles. Some venues keep reviews private until decisions are made.
  • For withdrawn papers, reviews may or may not be visible depending on venue policy.
  • Always attribute opinions to specific reviewers (e.g., "Reviewer 1 (rating: 5)") when citing specific claims.
  • The script uses the OpenReview API v2 by default (for venues from 2024+) and falls back to API v1 for older venues.
  • No authentication is needed for reading public reviews.

Output Language

Match the user's language. If the user writes in Chinese, output the report in Chinese. If in English, output in English.