Alterlab figure qa

Skill AlterLab-IEU/AlterLab-Academic-Skills/skills/visualization/alterlab-figure-qa

239 evaluated academic Claude/agent skills across 17 research domains (bioinformatics, data science, clinical, social-science methods, Turkish academia & more). Executable eval per skill, deterministic citation verifier, research→write→review→publish pipeline, and a skill-finder front door. Claude Code, Cursor, Codex, Gemini CLI & Copilot.

Install

npx -y skills add AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-figure-qa

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

What its author says it does

Copied from the file, not written here

Verify publication figures with a render-then-check QA pass — data-fidelity against every underlying row, axis/label floor-and-ceiling legibility, bounding-box collision detection for overlapping text/markers, and 300-dpi print-readiness. Use when proofing or auditing a finished figure for correctness and print quality, catching mislabeled or overlapping elements, or confirming a plot faithfully represents its data before submission. For CREATING the plot prefer alterlab-matplotlib (or alterlab-seaborn / alterlab-plotly); for multi-panel publication layout prefer alterlab-scientific-viz; for schematic diagrams prefer alterlab-scientific-schematics. Part of the AlterLab Academic Skills suite.

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

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Figure QA (render-then-verify)

Overview

A finished figure can look fine and still be wrong: a series plotted from the wrong column, a legend covering a data point, tick labels clipped at the axis edge, or a 150-dpi export that pixelates in print. This skill is a render-then-verify QA pass — it re-renders the figure and checks it against a concrete, measurable checklist before submission. It complements the plotting skills (which make figures); it does not create plots.

When to Use This Skill

Use this skill when the user wants to:

Proof a finished figure for correctness and print-readiness before submission.
Confirm the plot faithfully represents its data (every row/series accounted for).
Catch overlapping or clipped labels, legends, and markers.
Verify resolution / export settings (e.g. 300 dpi, vector where required).

Does NOT Trigger

Scenario	Use instead
Create/plot the figure in the first place	`alterlab-matplotlib` / `alterlab-seaborn` / `alterlab-plotly`
Lay out a multi-panel publication figure	`alterlab-scientific-viz`
Draw a schematic / diagram	`alterlab-scientific-schematics`
Build an infographic	`alterlab-infographics`

Core Capabilities

1. Data-fidelity check

Verify the rendered marks against every row of the source data: series count, point count per series, min/max/range on each axis, and that categorical labels match the data's categories. Flag any series plotted from the wrong column or a silently dropped subset.

2. Label floor-and-ceiling legibility

Check that tick labels, axis titles, and annotations are within legibility bounds — a font floor (nothing below the journal's minimum pt at final size) and a ceiling (titles not so large they crowd the panel) — and that nothing is clipped at the axis boundary.

3. Bounding-box collision detection

Compute the bounding boxes of text, legend, and markers and detect overlaps/collisions (legend over data, colliding labels, out-of-axes text). Report each collision with its location so it can be nudged.

4. Resolution and export QA

Confirm the export meets the target: ≥300 dpi for raster, vector format where the venue requires it, correct figure dimensions/column width, and embedded fonts. Fail the check if the raster resolution is below the floor.

5. Report

Emit a pass/fail checklist per criterion with the specific offending element(s), so the fix is actionable. See references/figure_qa_checklist.md for the full rubric and Matplotlib bbox recipes.

Resources

references/figure_qa_checklist.md — the full QA rubric, Matplotlib renderer/bbox recipes for collision detection, dpi/vector export checks, and journal legibility floors. Loaded on demand.

Part of the AlterLab Academic Skills suite.