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Review academic papers for correctness, quality, and novelty using OpenJudge's multi-stage pipeline. Supports PDF files and LaTeX source packages (.tar.gz/.zip). Covers 10 disciplines: cs, medicine, physics, chemistry, biology, economics, psychology, environmental_science, mathematics, social_sciences.
Passed 21 of 23 test cases with the skill, and 12 of 23 without it.
and 9 more in the full report
10 fixed13 passed either way2 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
I want to analyze `manuscript_v2.pdf` using the paper review cookbook. Only `ANTHROPIC_API_KEY` is present in my environment variables. Which model should be selected if I omit the `--model` flag?
| Checked | Without skill | With skill |
|---|---|---|
| Selects anthropic/claude-opus-4-6 as the default model | Missed | Passed |
The instructions your model reads when the skill loads.
Multi-stage academic paper review using the OpenJudge PaperReviewPipeline:
# Install OpenJudge
pip install py-openjudge
# Extra dependency for paper_review
pip install litellm
pip install pypdfium2 # only if using vision mode (use_vision_for_pdf=True)
| Info | Required? | Notes |
|---|---|---|
| Paper file path | Yes | PDF or .tar.gz/.zip TeX package |
| API key | Yes | Env var preferred: OPENAI_API_KEY, ANTHROPIC_API_KEY, etc. |
| Model name | No | gpt-5.2, anthropic/claude-opus-4-6, dashscope/qwen-vl-plus. See Model selection below |
| Discipline | No | If not given, uses general CS/ML-oriented prompts |
| Venue | No | e.g. "NeurIPS 2025", "The Lancet" |
| Instructions | No | Free-form reviewer guidance, e.g. "Focus on experimental design" |
| Language | No | "en" (default) or "zh" for Simplified Chinese output |
| BibTeX file | No | Required only for reference verification |
| CrossRef email | No | Improves API rate limits for BibTeX verification |
File type is auto-detected: .pdf → PDF review, .tar.gz/.zip → TeX review, .bib → BibTeX verification.
test cases passed, vs 12 / 23 without
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