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Generating Publication Ready Figures In R

作者 JackKuo666 · GitHub ↗ · v0.1.0
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在 OpenClaw 中安装
/install generating-publication-ready-figures-in-r
功能描述
Transform standard ggplot2 figures into publication-quality visualizations matching Nature, Science, and other top journal styles with proper themes, colors,...
使用说明 (SKILL.md)

Generating Publication-Ready Figures in R

This skill specializes in transforming ordinary ggplot2 plots into professional, publication-ready figures that meet the strict standards of top-tier journals like Nature, Science, Cell, and others.

Use this skill when the user wants to:

  • Convert ggplot plots to journal-style figures
  • Apply Nature/Science publication themes to existing plots
  • Create multi-panel figures with consistent styling
  • Export figures with proper DPI, dimensions, and formats
  • Match specific journal submission guidelines
  • Create colorblind-safe and publication-quality color schemes

What This Skill Does

When activated, this skill will:

  1. Analyze existing ggplot code - Read and understand the current plot structure

  2. Apply journal themes - Add publication-quality themes including:

    • Proper font sizes and families
    • Clean axis lines and backgrounds
    • Journal-specific color palettes
    • Legend positioning and styling
  3. Optimize for submission - Ensure figures meet:

    • DPI requirements (typically 300-600 DPI)
    • Width/height specifications (single vs double column)
    • File format requirements (TIFF, PDF, EPS)
    • Color space requirements (CMYK vs RGB)
  4. Create multi-panel figures - Combine plots using:

    • patchwork for simple layouts
    • cowplot for complex compositions
    • Custom annotation and labeling
  5. Export properly - Save with correct:

    • Resolution (DPI)
    • Dimensions (inches/cm)
    • File format
    • Color profile

Example User Requests That Should Trigger This Skill

  • "Transform this ggplot to Nature journal style"
  • "Make this figure publication-ready for Science"
  • "Create a two-column figure matching Cell format"
  • "Export these plots at 600 DPI for submission"
  • "Apply a colorblind-safe palette to my plots"
  • "Combine these four plots into one publication figure"
  • "Format my scatter plot for PNAS submission"

Journal Style Guidelines

Nature Style

  • Font: Arial or Helvetica
  • Font sizes: Axis titles 7-9 pt, axis labels 6-8 pt
  • Single column: 89 mm (3.5 in) width
  • Double column: 183 mm (7.2 in) width
  • Max height: 234 mm (9.2 in)
  • Resolution: 300-600 DPI
  • Formats: TIFF, PDF, EPS (vector preferred)

Science Style

  • Font: Arial
  • Font sizes: Title 9 pt, labels 7 pt
  • Single column: 57 mm (2.25 in) width
  • Double column: 114 mm (4.5 in) width
  • Resolution: 300-600 DPI
  • Formats: TIFF, PDF, EPS

Cell Press Style

  • Font: Arial or Helvetica
  • Single column: 85 mm (3.3 in) width
  • Double column: 178 mm (7 in) width
  • Resolution: 300 DPI minimum
  • Formats: TIFF, EPS, PDF

Theme Templates Available

theme_nature()

Clean, minimalist theme matching Nature journals:

  • No gray backgrounds
  • Minimal grid lines
  • Arial font family
  • Proper axis sizing

theme_science()

Theme for Science journal submissions:

  • Compact layout
  • Clean typography
  • Optimized for smaller widths

theme_cellpress()

Cell Press journal theme:

  • Professional appearance
  • Flexible legend placement
  • Publication-ready defaults

theme_colorblind()

Colorblind-safe palette with:

  • Viridis/Colorbrewer schemes
  • High contrast ratios
  • Print-friendly colors

Color Palettes

Nature-Approved Colors

# Primary colors
nature_colors \x3C- c(
  blue = "#3B4992",
  red = "#EE0000",
  green = "#008B45",
  purple = "#631879"
)

Colorblind-Safe Scales

  • scale_fill_viridis()
  • scale_color_okabe_ito() (Okabe-Ito palette)
  • scale_color_viridis()

Example Workflow

User: Here's my ggplot code, make it Nature-style.

# Original plot
p \x3C- ggplot(mtcars, aes(x = wt, y = mpg, color = factor(cyl))) +
  geom_point(size = 3)

Skill transforms to:

# Publication-ready version
p \x3C- ggplot(mtcars, aes(x = "Weight (tons)", y = "Fuel Efficiency (mpg)",
                        color = "Cylinders")) +
  geom_point(size = 2.5, shape = 16, alpha = 0.8) +
  scale_color_nature() +
  theme_nature(base_size = 8) +
  labs(title = NULL)

# Export at correct size
ggsave("figure1.pdf", p, width = 3.5, height = 3, dpi = 300,
       device = "pdf")

Multi-Panel Figures

# Combine plots with patchwork
library(patchwork)

figure1 \x3C- (panel_a | panel_b) / (panel_c | panel_d)

# Add panel labels
figure1 \x3C- figure1 +
  plot_annotation(tag_levels = "A",
                  tag_suffix = ")")

# Export
ggsave("figure1.pdf", figure1, width = 7, height = 6, dpi = 300)

Tools & Packages Commonly Used

Purpose R Packages
Base plotting ggplot2
Themes ggplot2, cowplot, hrbrthemes
Color palettes viridis, RColorBrewer, scales, ggsci
Multi-panel patchwork, cowplot, ggpubr
Export ggplot2, ragg
Fonts extrafont, showtext
Annotations ggrepel, ggpp

Common Journal Requirements

Journal Width (single) Width (double) Max Height Min DPI
Nature 89 mm 183 mm 234 mm 300
Science 57 mm 114 mm 229 mm 300
Cell 85 mm 178 mm 229 mm 300
PNAS 87 mm 178 mm 227 mm 300
PLOS ONE 170 mm - 230 mm 300
eLife 183 mm - 244 mm 300

Quick Reference

Applying a theme

p + theme_nature()           # Nature style
p + theme_science()          # Science style
p + theme_cellpress()        # Cell Press style
p + theme_colorblind()       # Colorblind-safe

Export formats

# Vector (preferred)
ggsave("figure.pdf", ... device = "pdf")
ggsave("figure.eps", ... device = "eps")

# Raster (high DPI)
ggsave("figure.tiff", ... device = "tiff", dpi = 600)
ggsave("figure.png", ... device = "png", dpi = 300)

Common fixes

  • Text too small: Increase base_size in theme
  • Legend overlap: Use theme(legend.position = "bottom")
  • Colors not distinct: Use scale_fill_viridis()
  • Fonts not rendering: Use extrafont::font_import()

Notes

  • Always check specific journal guidelines before submission
  • Vector formats (PDF/EPS) are preferred over raster
  • Use consistent styling across all figures in a paper
  • Test colorblind accessibility with colorblindr package
  • Keep axis labels clear and concise
  • Avoid redundant chart junk (backgrounds, grid lines)
安全使用建议
This skill appears coherent in purpose (making ggplot figures publication-ready) but is instruction-only: it advertises R functions and a project structure that are not included in the published bundle. Before using: 1) don't blindly run code the agent suggests — verify whether theme_* and export_publication functions exist in your environment; 2) if the agent suggests sourcing remote R scripts, inspect their contents before sourcing; 3) be cautious with extrafont::font_import() and other commands that change system fonts or write files — they can be slow and may require permissions; 4) if you expect a ready-to-use package, ask the publisher for the missing R files or a proper install mechanism (CRAN/GitHub repo) so you can review and install safely. Providing the missing R/publication_themes.R or a link to the repository would increase confidence and could change this assessment to benign.
功能分析
Type: OpenClaw Skill Name: generating-publication-ready-figures-in-r Version: 0.1.0 The skill bundle is benign. Its stated purpose is to transform ggplot2 figures into publication-quality visualizations, which is clearly supported by the provided documentation and R code examples. There is no evidence of prompt injection against the AI agent, malicious execution (e.g., `curl|bash`), data exfiltration, persistence mechanisms, or obfuscation. File operations like `ggsave` and `export_publication` are directly aligned with the skill's legitimate function of saving generated figures.
能力评估
Purpose & Capability
The skill claims a library of R functions (theme_nature, scale_color_nature, export_publication, R/publication_themes.R, etc.) and a project structure, but the published package only contains SKILL.md and README.md. There are no code files or install instructions to provide the advertised functions. A user expecting to simply call those functions will not find them in this bundle.
Instruction Scope
The SKILL.md stays within the stated purpose (transform ggplot objects, combine panels, export with ggsave, use packages like patchwork/cowplot). It does instruct operations that write files (ggsave) and to run font-import commands (extrafont::font_import()), which affect the local environment — those are expected for the purpose but worth reviewing before executing. The instructions assume local R code (sourcing publication_themes.R) that is not included.
Install Mechanism
No install spec and no binaries requested: the skill is instruction-only. This minimizes install-time risk, but combined with the missing code files, it means the skill likely intends to have the agent produce or instruct usage of code rather than provide it.
Credentials
The skill requests no environment variables or credentials (good). However, it references operations that interact with the user's filesystem and local R environment (sourcing local scripts, running font_import, saving files). Because the R code that implements the themes isn't present, an agent or a user may be prompted to download or source external scripts — any external sourcing should be verified. No secrets are requested.
Persistence & Privilege
The skill does not request persistent installation or elevated privileges; always is false and there are no install scripts. It does instruct actions that modify the local environment (writing files, importing fonts), but it does not attempt to modify other skills or system-wide agent settings.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install generating-publication-ready-figures-in-r
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /generating-publication-ready-figures-in-r 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v0.1.0
- Initial release of publication-ready ggplot2 figure transformation skill for R. - Supports easy conversion of standard plots to Nature, Science, Cell, and other top journal styles. - Provides themed templates for major journals, colorblind-safe palettes, and multi-panel layout tools. - Exports figures with proper DPI, dimensions, file format, and color profiles as required by journals. - Includes quick reference for applying themes, export formats, and common styling fixes.
元数据
Slug generating-publication-ready-figures-in-r
版本 0.1.0
许可证
累计安装 1
当前安装数 1
历史版本数 1
常见问题

Generating Publication Ready Figures In R 是什么?

Transform standard ggplot2 figures into publication-quality visualizations matching Nature, Science, and other top journal styles with proper themes, colors,... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 396 次。

如何安装 Generating Publication Ready Figures In R?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install generating-publication-ready-figures-in-r」即可一键安装,无需额外配置。

Generating Publication Ready Figures In R 是免费的吗?

是的,Generating Publication Ready Figures In R 完全免费(开源免费),可自由下载、安装和使用。

Generating Publication Ready Figures In R 支持哪些平台?

Generating Publication Ready Figures In R 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Generating Publication Ready Figures In R?

由 JackKuo666(@jackkuo666)开发并维护,当前版本 v0.1.0。

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