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Read vis

Skill QinghongLin/paperdoctor/skills/read-vis

PaperDoctor: Evidence-Grounded and Actionable Feedback for Scientific Papers in Progress

Install
npx -y skills add QinghongLin/paperdoctor --skill read-vis

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

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 3 stars3 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Check a paper's visual presentation for layout, figure quality, spacing, and formatting issues. Use when reviewing paper polish before submission.

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

6.9 KB, as published. Nobody here has run it

Paper Visual Check

Check a paper from the visual side.

Focus on what can be seen on the page:

  • layout is reasonable or not
  • figures are too small or too large
  • spacing is awkward
  • tables are cramped or hard to read
  • captions are detached
  • figures look low-quality or obviously AI-generated

Do not focus on code, experiments, or citations here.

When to Use

  • Check whether the paper looks polished
  • Find obvious visual problems before submission
  • Review figures, tables, spacing, and page balance

Workflow

Visual Check:
- [ ] Resolve PDF input
- [ ] Reuse or render page images
- [ ] Inspect pages visually
- [ ] Save report

Resolve Input

  • Input should be a PDF path.
  • If prepare-paper has already run, use {paper_dir}/metadata/page/ as the page-image directory.
  • If page images do not exist yet, render them with:
python tools/pdf_render.py /path/to/paper.pdf

This writes:

  • {paper_dir}/metadata/page/page-001.png, page-002.png, ...
  • {paper_dir}/metadata/page/manifest.json

What to Check

Look for visible issues such as:

  • bad spacing
  • poor page balance
  • overflow or clipping
  • a weak last line with only a few trailing words
  • tiny figures or tables
  • figures that are too large for their value
  • captions far from the figure or table
  • crowded tables
  • blurry or low-quality figures
  • figures with obvious AI-generation artifacts

Every finding should point to a specific target when possible:

  • Figure 2
  • Table 3
  • right-column equation block
  • bottom image on page 6
  • caption under Figure 4

Do not write vague findings like "layout is a bit off". Say exactly what is wrong and where it is.

Do not treat anonymous submission formatting as a visual issue. Examples:

  • Anonymous Author(s)
  • hidden affiliations
  • placeholder contact fields used for blind review

These are submission-state choices, not layout defects.

If a paragraph ends with a very short final line, treat that as a valid visual issue when it makes the page look poorly balanced. Suggest reflowing nearby text, adjusting spacing, or reordering content.

Zoom in when in doubt

When a figure or table is too dense or too small to judge confidently from the full page, crop the region and re-read the crop:

python -c "
from PIL import Image
Image.open('{paper_dir}/metadata/page/page-004.png').crop((LEFT, TOP, RIGHT, BOTTOM)).save('/tmp/zoom.png')
"

Then Read /tmp/zoom.png to inspect axis labels, sub-panel text, or AI-generation artifacts at full resolution. Crop instead of hedging — replace "might be too small to read" or "looks blurry but unsure" with a decisive judgment after a closer look.

Output

Write the report by issue, not by page.

Each issue should be one concrete visual problem:

{
  "page": 4,
  "quote": ["Figure 3"],
  "status": "warning",
  "reason": "Figure 3 is too small to read comfortably, especially the axis labels.",
  "suggest": "Enlarge Figure 3 or simplify the panel so the labels remain legible."
}

Use:

  • page: page number
  • quote: array of affected targets (e.g. ["Figure 3"] or ["Figure 4", "Figure 5"])
  • status: warning or error
  • reason: exact visual problem
  • suggest: concrete suggestion

status rules:

  • error100% certain defects:

    • Content clipped/cut off, text completely illegible, broken layout
    • Missing figures, factual errors in figure content (wrong labels, copy-paste)
    • Obviously AI-generated figures with visible artifacts (extra fingers, garbled text, impossible geometry, hallucinated details) used as actual scientific content (not as decorative illustrations)
  • warninggenuine quality issues:

    • Rough/unpolished figures that look hastily made (misaligned elements, inconsistent styling, low-resolution rasterized text)
    • Overlapping text that obscures data, color choices that make categories indistinguishable
    • Figures or tables that are too sparse — excessive whitespace, a tiny chart floating in a large empty area, a table with 2 rows taking half a page
    • Important labels hard to read even when zoomed in

Do NOT flag (not even warning):

  • Polished dense figures with clean vector graphics, consistent styling, clear legends — density is a feature when well-executed
  • Tables with small but readable font — standard in conference papers
  • Pages with multiple well-formatted figures/tables — layout choice

Quality judgment guide:

  • Polished & informative (clean vector graphics, consistent colors, clear legends, professional layout) → do not flag, even if dense
  • Rough & poorly executed (default matplotlib with no styling, blurry/pixelated sub-images, misaligned labels, hard to compare panels, missing visual separators, low-resolution rasterized content, inconsistent fonts/sizing) → warning
  • AI-generated artifacts (DALL-E/Midjourney figures with telltale distortions used as scientific figures) → error
  • Too sparse (a bar chart with 3 bars taking an entire page, mostly empty figure area) → warning
  • Dense comparison grids where sub-images are too small to see meaningful differences → warning

Font size rule of thumb: Compare text inside figures/tables to the paper's body text. If figure labels, axis text, or table content is noticeably smaller than the body text (roughly <60% of body font size), flag as warning. Body text in a standard conference paper is ~10pt; figure text below ~6pt is a problem.

Figure-caption coherence:

  • A good figure makes its caption easy to understand — the visual clearly illustrates what the caption describes
  • warning if a figure is hard to connect to its caption (e.g. caption describes a trend but the figure doesn't clearly show it, or caption references sub-panels by labels that are missing/hard to find)
  • error if the caption describes something completely different from what the figure shows (factual mismatch)

Aim for quality over quantity — fewer, more actionable findings are better than many nitpicks.

Save one report with:

  • summary
  • issues

Example shape:

{
  "summary": {
    "total_issues": 5,
    "warning_issues": 4,
    "error_issues": 1
  },
  "results": [
    {
      "page": 4,
      "quote": ["Figure 3"],
      "status": "warning",
      "reason": "Figure 3 is too small to read comfortably, especially the axis labels.",
      "suggest": "Enlarge Figure 3 or simplify the panel so the labels remain legible."
    }
  ]
}

If a page has no visual problem, do not create a dummy entry for that page.

Output:

  • {paper_dir}/reports/check_vis.json

Tips

  • Judge from visual evidence only.
  • Prefer obvious, actionable feedback.
  • If a figure looks AI-generated, say what visual artifact suggests that.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.