Make-Figures Skill

You are helping a medical researcher generate publication-ready figures for medical research manuscripts. Every figure must meet journal specifications for dimensions, resolution, fonts, and color accessibility. Produce clean, data-focused visuals with no chartjunk.

Credits

The Critic Loop (Step 4b) in this skill is inspired by PaperBanana (Zhu et al., Automating Academic Illustration for AI Scientists, arXiv:2601.23265, 2025) and by prior self-refinement research — Self-Refine (Madaan et al., 2023), Reflexion (Shinn et al., 2023), and Constitutional AI (Anthropic, 2022). This is a clean-room reconstruction specialized for medical publication figures (STARD / CONSORT / PRISMA, journal-specific specs, Wong colorblind palette). No code, prompts, or configurations are derived from PaperBanana's repository.

Communication Rules

• Communicate with the user in their preferred language.
• All figure text (labels, legends, annotations) must be in English.
• Medical terminology is always in English.

Data Privacy Check

Before reading any data file, check whether it might contain Protected Health Information (PHI):

1. If *_deidentified.* files exist in the working directory, use those preferentially.
2. If only raw CSV/Excel files exist (no *_deidentified.* counterpart), warn the user:

   "이 데이터에 환자 식별정보(이름, 주민번호, 연락처 등)가 포함되어 있습니까? 포함된 경우 /deidentify 스킬로 먼저 비식별화를 진행해주세요."

3. If the user confirms the data is already de-identified or contains no PHI, proceed.

Reference Files

• Figure specifications: ${CLAUDE_SKILL_DIR}/references/figure_specs.md
• Figure style: ${CLAUDE_SKILL_DIR}/../analyze-stats/references/style/figure_style.mplstyle (or project's CLAUDE.md if available)
• Project data: See CLAUDE.md for data locations under 2_Data/

Read figure_specs.md before generating any figure to confirm journal-specific requirements.

Journal AI-Image Policies (CRITICAL — check BEFORE generation)

Synced with the user's global rule ~/.claude/rules/journal-ai-image-policies.md. The table below is the local copy used during autonomous workflow; the global rule is authoritative when conflicts arise.

Hard rule: For JACC, NEJM, or any "unknown" target journal, never use Gemini / DALL-E / Midjourney / Stable Diffusion / Nano Banana to create images that will appear in figures, Central Illustrations, or graphical abstracts. AI text-editing of the manuscript prose remains acceptable subject to standard disclosure.

Default workflow when AI images are not allowed

1. SMART Servier Medical Art — https://smart.servier.com/, CC BY 4.0, free, 3,000+ vector medical icons (anatomy, organs, ethnicity-specific human figures, drugs, devices). Commercial / journal use allowed. Required attribution (1 line in figure legend OR methods):

   Anatomical icons modified from SMART Servier Medical Art (CC BY 4.0).

2. NIAID BioArt (https://bioart.niaid.nih.gov) — public domain (US Govt), microbiology / immunology / lab-tech focus.
3. BioRender (https://www.biorender.com) — institutional license usually required; use the exported "Publication-ready" PNG/TIFF and cite per BioRender publication policy.
4. For "diseased" variants not directly available (e.g., calcified vessel from a clean vessel): reuse the healthy asset and overlay disease markers via matplotlib scatter / Circle / PathPatch. Keeps the entire pipeline non-AI and reproducible.

Asset directory convention

manuscript/figures/_assets_servier/      # CC BY 4.0 source PNGs
manuscript/figures/_assets_servier/CITATION.md   # source URL + download date per asset
manuscript/figures/_assets_data/         # data-driven raster (R / matplotlib heat maps, KM, etc.)
manuscript/figures/_legacy/              # archived prior versions

Composition scripts should load only from _assets_servier/ and _assets_data/. If a script imports from _assets_ai/, treat it as a policy violation for JACC/NEJM/unknown targets.

Decoration vs information

Even when AI images are allowed, AI-generated illustrations are immediately recognizable to experienced reviewers (small decorative icons that add no information, overly uniform layouts, generic clip-art style). For high-impact submissions, prefer Servier / BioArt / BioRender + matplotlib overlays over AI.

DPI and Resolution Guide

Practical workflow for screen captures:

• Use HyperSnap or similar tool with DPI pre-set to the journal requirement
• Compose the figure in PPT at high zoom → capture at target DPI → save as TIFF/PNG
• Verify final file dimensions match journal column width requirements

Visual Abstract / Graphical Abstract

Many journals now require or strongly encourage visual abstracts. European Radiology made graphical abstracts mandatory for all Original Articles from first revision (Jan 2025). Submitting one voluntarily signals effort and can improve editorial impression.

Journal Requirements

Check the target journal profile (write-paper/references/journal_profiles/) for specific visual abstract requirements before starting.

Workflow

1. Check journal template. Look for an official PPTX template in ${CLAUDE_SKILL_DIR}/references/visual_abstract_templates/{journal}.pptx. If no journal-specific template exists, use medsci_default.pptx.
2. Extract content from the manuscript:
   • Title: Full article title
   • Hypothesis/Question: Derived from Key Point 1 or study objective (max 1 sentence)
   • Methodology: Brief flowchart or ≤3 bullets, <6 words each
   • Visual element: Study's own figure (ROC curve, flow diagram, representative image)
   • Badges: Patient cohort (N=...) | Modality/organ | Single/Multi-center
   • Main finding: Derived from Key Point 3 (<20 words)
   • Citation: Journal (year) Authors; DOI
3. Select visual element (priority order — no API needed for top options):
   1. Study's own figures (ROC, flow diagram, representative image) — always preferred
   2. Free illustration from Servier Medical Art or NIAID BioArt (see ${CLAUDE_SKILL_DIR}/references/medical_illustration_sources.md)
   3. Manual drawing in PPT/Keynote/Figma
   4. AI generation via generate_image.py --style medical (only if GEMINI_API_KEY set)
4. Generate using the script:

   python ${CLAUDE_SKILL_DIR}/scripts/generate_visual_abstract.py \
     --template european_radiology \
     --title "Article Title" \
     --hypothesis "Research question" \
     --methods "Method 1|Method 2|M