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make-figures

Generate publication-ready medical figures from manuscripts using R, Python, and PPTX templates.

243|60|Updated Apr 6, 2026
Search Tags:#quality-check#publication#figures#flow-diagram#roc-curve#medical-visualization#journal-specs
One-click install
npx skills add https://github.com/Aperivue/medsci-skills --skill make-figures
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: make-figures
Source: https://github.com/Aperivue/medsci-skills/tree/main/skills/make-figures
Command: npx skills add https://github.com/Aperivue/medsci-skills --skill make-figures

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires Pillow, numpy, PyMuPDF, google-generativeai, python-pptx, pytesseract, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Researchers spend hours crafting publication-ready figures that adhere to journal specifications and accessibility guidelines. This Skill automates figure generation, formatting, and annotation to streamline manuscript preparation.

Core Features & Use Cases

  • Generate publication-ready figures (ROC curves, forest plots, calibration plots, Kaplan-Meier curves, Bland-Altman plots, confusion matrices, and pipeline diagrams) and visual abstracts that comply with journal templates and figure guidelines.
  • Validate figures against journal specs (DPI, dimensions, fonts, Wong color palette) and provide deterministic output with a built-in critic loop for iterative refinement.
  • Use cases include STARD/CONSORT/PRISMA flow diagrams, diagnostic accuracy visuals, meta-analysis figures, and study-design schematics, with optional exemplar references for critique.

Quick Start

Provide the manuscript data and run the figure-generation pipeline to output publication-ready figures and flow diagrams.

Frequently Asked Questions about make-figures

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate publication-ready medical figures from my manuscript data?▼

To generate publication-ready medical figures from manuscript data, provide your dataset to the automated pipeline. It outputs ROC curves, forest plots, and Kaplan-Meier curves while validating DPI, dimensions, and fonts against strict journal specifications.

Can I create CONSORT and PRISMA flow diagrams automatically for journal submission?▼

Yes, you can create CONSORT and PRISMA flow diagrams for journal submission. The Skill uses R templates to generate standard study-design schematics and STARD flow diagrams, ensuring they meet publication guidelines through an automated critic loop.

Does this tool validate figure dimensions and color accessibility for medical journals?▼

Yes, the tool validates figure dimensions and color accessibility for medical journals. It checks DPI, fonts, and applies the Wong color palette to ensure visual abstracts and data plots meet strict journal specifications during its quality-check workflow.

What is the best way to build visual abstracts that comply with journal templates?▼

The best way to build compliant visual abstracts is using the integrated PPTX templates. The pipeline generates them alongside data plots and runs automated QC to verify formatting, dimensions, and accessibility before final output.

Do I need Python and R to produce diagnostic accuracy visuals like Bland-Altman plots?▼

Yes, you need Python and R to produce diagnostic accuracy visuals. The workflow uses Python for data plots like Bland-Altman plots and confusion matrices, while R handles pipeline diagrams and flow schematics.

Why do my generated forest plots fail journal quality checks?▼

Forest plots may fail journal quality checks due to incorrect DPI, dimensions, or fonts. The built-in critic loop iteratively refines calibration plots and meta-analysis figures, ensuring deterministic output that meets strict publication guidelines.

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