# Send Generating Publication Ready Figures In R to your agent
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
## Fast path
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
## Suggested prompts
### New install

```text
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
```
### Upgrade existing

```text
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
```
## Machine-readable fields
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        "Review SKILL.md after the package is downloaded.",
        "Confirm the extracted package contains the expected setup assets."
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        "Validate the skill or prompts are available in your target agent workspace.",
        "Capture any manual follow-up steps the agent could not complete."
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```
## Documentation

### 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:

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


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



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)



Create multi-panel figures - Combine plots using:

patchwork for simple layouts
cowplot for complex compositions
Custom annotation and labeling



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"

### 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_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

### Nature-Approved Colors

# Primary colors
nature_colors <- 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 <- ggplot(mtcars, aes(x = wt, y = mpg, color = factor(cyl))) +
  geom_point(size = 3)

Skill transforms to:

# Publication-ready version
p <- 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 <- (panel_a | panel_b) / (panel_c | panel_d)

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

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

### Tools & Packages Commonly Used

PurposeR PackagesBase plottingggplot2Themesggplot2, cowplot, hrbrthemesColor palettesviridis, RColorBrewer, scales, ggsciMulti-panelpatchwork, cowplot, ggpubrExportggplot2, raggFontsextrafont, showtextAnnotationsggrepel, ggpp

### Common Journal Requirements

JournalWidth (single)Width (double)Max HeightMin DPINature89 mm183 mm234 mm300Science57 mm114 mm229 mm300Cell85 mm178 mm229 mm300PNAS87 mm178 mm227 mm300PLOS ONE170 mm-230 mm300eLife183 mm-244 mm300

### 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)
## Trust
- Source: tencent
- Verification: Indexed source record
- Publisher: JackKuo666
- Version: 0.1.0
## Source health
- Status: healthy
- Source download looks usable.
- Yavira can redirect you to the upstream package for this source.
- Health scope: source
- Reason: direct_download_ok
- Checked at: 2026-04-23T16:43:11.935Z
- Expires at: 2026-04-30T16:43:11.935Z
- Recommended action: Download for OpenClaw
## Links
- [Detail page](https://openagent3.xyz/skills/generating-publication-ready-figures-in-r)
- [Send to Agent page](https://openagent3.xyz/skills/generating-publication-ready-figures-in-r/agent)
- [JSON manifest](https://openagent3.xyz/skills/generating-publication-ready-figures-in-r/agent.json)
- [Markdown brief](https://openagent3.xyz/skills/generating-publication-ready-figures-in-r/agent.md)
- [Download page](https://openagent3.xyz/downloads/generating-publication-ready-figures-in-r)