review-figures

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Send paper figures to vision-capable models for feedback on clarity, design, and presentation

expectedparrot By expectedparrot schedule Updated 4/13/2026

name: review-figures description: Send paper figures to vision-capable models for feedback on clarity, design, and presentation allowed-tools: Read, Bash, Glob, Grep user-invocable: true

Review Figures

Sends each figure from the paper to vision-capable models via EDSL for feedback on clarity, labeling, design quality, and caption adequacy. Results are recorded as eval responses under the "figures" category.

Usage

/review-figures

Prerequisites

  • The paper must be registered in katz with images copied to .katz/versions/<commit>/paper/. (This happens automatically when registering with katz paper register — sibling image files are copied alongside the manuscript.)
  • edsl must be installed.

Workflow

1. Validate

Run katz paper status to confirm registration. Check that images exist:

ls .katz/versions/$(katz paper status | python3 -c "import sys,json; print(json.load(sys.stdin)['commit'])")/paper/*.png

2. Run the figure review

# All figures, 2 models (Claude Opus + GPT-5.4)
python <katz-skills-path>/review-figures/scripts/edsl_review_figures.py

# Dry run to see what would be sent
python <katz-skills-path>/review-figures/scripts/edsl_review_figures.py --dry-run

# Single model
python <katz-skills-path>/review-figures/scripts/edsl_review_figures.py --models 1

The script:

  • Loads all images from the paper directory
  • Extracts surrounding caption/notes from the manuscript for context
  • Sends each figure + context to vision models
  • Records results as eval responses with grades under the "figures" category

3. View results

Results appear in the HTML report under the Evaluations section (category: "figures"), or via:

katz eval results --category figures

4. What the models evaluate

Each figure is assessed on five dimensions:

  • Self-explanatory: Can it be understood standalone? Axes labeled? Legend present?
  • Takeaway: Is the main message immediately apparent?
  • Design quality: Color choices, clutter, data-ink ratio, font sizes
  • Caption adequacy: Does the caption explain what's shown and how to read it?
  • Suggestions: Specific improvements
Install via CLI
npx skills add https://github.com/expectedparrot/katz --skill review-figures
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