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

):

Harsh but fair reviewer

Expects good experiments that lead to insights

Harsh and critical reviewer

Looking for impactful ideas in the field
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)

Weaknesses (consensus across reviewers)

Questions for Authors

Specific Suggestions for Improvement

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.