docsor1212

Academic Figures — Development skill for Claude Code

Development community

Publication-ready research figures from a single command: forest plots, KM curves with risk tables, PRISMA 2020, ROC with DeLong — 21 chart types, 9 journal presets, Chinese support, MIT-0.

How to install Academic Figures

This entry records only its repository, not the path inside it, so there is no exact command to give. Open docsor1212/academic-figures and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Academic Figures does

Publication-ready research figures from a single command: forest plots, KM curves with risk tables, PRISMA 2020, ROC with DeLong — 21 chart types, 9 journal presets, Chinese support, MIT-0.

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README

Academic Figures

**Publication-ready scientific figures from data — one command, verified output.** 从数据一键生成投稿级论文图表：期刊合规、统计正确、中文零配置、纯本地运行。

[![SkillHub](https://img.shields.io/badge/SkillHub-academic--figures-blue)](https://skillhub.cn/skill/academic-figures) [![Site](https://img.shields.io/badge/Site-docsor.cn-teal)](https://docsor.cn) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) ![Python](https://img.shields.io/badge/Python-3.8%2B-blue) ![Tests](https://img.shields.io/badge/tests-233%20pass-brightgreen)

**22 chart types** (bar/box/violin/scatter/line/heatmap/clustered-heatmap/forest/KM/ROC/ venn 4-set ellipse/Bland-Altman/PCA/funnel/paired/dual-axis/stacked/composite/diagram/ PRISMA 2020 …) · **9 journal presets** (Nature/Lancet/Science/Cell/NEJM/JAMA/IEEE/CMA/ 中文核心) · **9 color themes** incl. colorblind-safe Okabe-Ito · **600dpi TIFF/PDF/SVG/EPS** · **fully local, zero telemetry**.

Quick Start

# one-command figure (auto-picks the chart type)
python3 scripts/gen_figure.py --quick -d data.csv

# Nature double-column submission (width/font/DPI per author guidelines)
python3 scripts/gen_figure.py -t bar -d data.json -o fig.pdf --journal nature --column double --verify

# Cox multi-variable regression forest (raw per-subject data; Efron + PH test)
python3 scripts/gen_figure.py -t forest -d patient.csv --stats cox   --cox-time time --cox-event event --cox-cols "age,sex,treat"

# Chinese zero-config (auto CJK font detection)
python3 scripts/gen_figure.py -t km -d survival.json -o km.png --cjk

Why academic-figures

Journal compliance built-in: column widths, font sizes and DPI from official author guidelines; --verify pixel-level text-overlap gate; audit_pdf.py font-size gate — the hard desk-reject reasons are guarded mechanically.
Statistical correctness: Cox (Efron ties + PH test), KM (risk table, log-rank, median survival 95% CI), ROC (DeLong), metafun