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Self review

Skill dongzhigang13305312738-art/paper-skills/self-review

Automatically review an academic paper using the NeurIPS review form with three reviewer personas, ensemble scoring, and reflection refinement. Extracts text from PDF, runs structured review, and outputs actionable feedback. Use when the user wants to review a paper before submission or get feedback on a draft.From its SKILL.md

Install
npx -y skills add dongzhigang13305312738-art/paper-skills --skill self-review

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

3 things to look at

  • 26 days oldThe repository was created 26 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
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SKILL.md

3.4 KB, 789 tokens by cl100k_base, as published. Nobody here has run it

Self-Review

Review an academic paper using a structured review form with multiple reviewer personas.

Input

  • $ARGUMENTS — Path to PDF file or .tex file

Scripts

Extract text from PDF

python ~/.claude/skills/self-review/scripts/extract_pdf_text.py paper.pdf --output paper_text.txt
python ~/.claude/skills/self-review/scripts/extract_pdf_text.py paper.pdf --format markdown

Tries pymupdf4llm (best) → pymupdf → pypdf. Install: pip install pymupdf4llm pymupdf pypdf

Parse PDF into structured sections

python ~/.claude/skills/self-review/scripts/parse_pdf_sections.py \
  --pdf paper.pdf --output sections.json

Extracts title (via font size), section headings, and section text. Requires: pip install pymupdf Key flags: --format text, --verbose

Workflow

Step 1: Load Paper

  • If PDF: use extract_pdf_text.py to extract text
  • If .tex: read the LaTeX source directly

Step 2: Three-Persona Review

Run three independent reviews using different personas (from references/review-form.md):

  1. Harsh but fair reviewer: Expects good experiments that lead to insights
  2. Harsh and critical reviewer: Looking for impactful ideas in the field
  3. Open-minded reviewer: Looking for novel ideas not proposed before

For each persona, generate a review following the NeurIPS review JSON format in references/review-form.md.

Step 3: Reflection Refinement (up to 3 rounds per reviewer)

After each review, apply the reflection prompt: re-evaluate accuracy and soundness, refine if needed. Stop when "I am done".

Step 4: Aggregate

  • Combine all three reviews
  • Average numerical scores (round to nearest integer)
  • Synthesize a meta-review finding consensus
  • Weight scores using AgentLaboratory weights: Overall (1.0), Contribution (0.4), Presentation (0.2), others (0.1 each)

Step 5: Actionable Report

Output format:

## Review Summary
- **Overall Score**: X/10 (Weighted: Y/10)
- **Decision**: Accept / Reject
- **Confidence**: Z/5

## Strengths (consensus across reviewers)
1. ...
2. ...

## Weaknesses (consensus across reviewers)
1. ...
2. ...

## Questions for Authors
1. ...

## Specific Suggestions for Improvement
1. [Section X, Page Y]: ...
2. [Section Z, Page W]: ...

## Score Breakdown
| Dimension | R1 | R2 | R3 | Avg |
|-----------|----|----|-----|-----|
| Overall | ... | ... | ... | ... |
| Contribution | ... | ... | ... | ... |
| ... | ... | ... | ... | ... |

References

  • NeurIPS review form, scoring weights, personas, reflection prompts: ~/.claude/skills/self-review/references/review-form.md
  • PDF text extraction: ~/.claude/skills/self-review/scripts/extract_pdf_text.py

Missing Sections Check

You MUST verify that all required sections are present: Abstract, Introduction, Methods/Approach, Experiments/Results, Discussion/Conclusion. Reduce scores if any are missing.

Related Skills

What ships with it: 3 files

16.2 KB alongside SKILL.md, 2 of them executable

references/

scripts/

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