openreview-review-analyzer
VerifiedFetch and analyze peer reviews from OpenReview for any academic paper. Use this skill when the user mentions OpenReview, asks about reviews for a paper, want...
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# 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:
```bash 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If the script fails (e.g., network restrictions, reviews not public, paper withdrawn), use these fallback methods in order: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:
- Score Distribution — list each reviewer's rating and confidence, compute average
- Consensus Points — identify strengths/weaknesses mentioned by multiple reviewers
- Key Disagreements — where reviewers diverge in opinion
- Critical Issues — weaknesses flagged as major by any reviewer
- Questions Raised — important unresolved questions
- Author Responses — summarize rebuttal if available, and whether reviewers updated scores
- Meta-Review — include AC recommendation if available
- 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.
Use Cases
- Fetch and synthesize all peer reviews for any paper on OpenReview into a structured report
- Analyze reviewer consensus, disagreements, and critical issues across multiple reviews
- Track score distributions and confidence levels for conference paper submissions
- Summarize author rebuttals and whether reviewers updated their scores post-discussion
- Generate bilingual review synthesis reports matching the user's language preference
Pros & Cons
Pros
- +Zero external dependencies — uses only Python's built-in urllib for API access
- +Supports both OpenReview API v1 and v2 for papers across all conference years
- +Multiple fallback methods (direct API, web search) if the primary script fails
Cons
- -Only works with publicly visible reviews — cannot access reviews still under embargo
- -Limited to papers hosted on OpenReview — does not cover other review platforms
FAQ
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