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Skills/lingzhi227/agent-research-skills/self-review
self-review logo

self-review

lingzhi227/agent-research-skills
785 installs133 stars
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Installation

npx skills add https://github.com/lingzhi227/agent-research-skills --skill self-review

Summary

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.

SKILL.md

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

  • Upstream: paper-compilation
  • Downstream: paper-revision, rebuttal-writing
  • See also: slide-generation

Score

0–100
63/ 100

Grade

C

Popularity15/30

785 installs — growing adoption.

Completeness27/30

Documented: full SKILL.md body, description, one-line install. Missing: category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Self Review skill score badge previewScore badge

Markdown

[![Self Review skill](https://www.claudemarket.ai/skills/lingzhi227/agent-research-skills/self-review/badges/score.svg)](https://www.claudemarket.ai/skills/lingzhi227/agent-research-skills/self-review)

HTML

<a href="https://www.claudemarket.ai/skills/lingzhi227/agent-research-skills/self-review"><img src="https://www.claudemarket.ai/skills/lingzhi227/agent-research-skills/self-review/badges/score.svg" alt="Self Review skill"/></a>

Self Review FAQ

How do I install the Self Review skill?

Run “npx skills add https://github.com/lingzhi227/agent-research-skills --skill self-review” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Self Review skill do?

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. The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Self Review skill free?

Yes. Self Review is a free, open-source skill published from lingzhi227/agent-research-skills. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Self Review work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Self Review works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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