feat(styles): enhance sizing and font settings for visualizations

- Update chart size and title font size in Altair
- Adjust text sizes for axes and titles in Bokeh
- Standardize sizing and font settings for Highcharts
- Improve text and element sizes in Matplotlib
- Refine layout and sizing for Plotly
- Enhance figure size and text settings in Plotnine
- Update styling for Pygal and Seaborn to ensure visibility

Author: MarkusNeusinger

prompts/default-style-guide.md

@@ -1,19 +1,14 @@
 # PyPlots.ai Default Style Guide
 
-Minimal style requirements for consistent visualizations.
+Style requirements for consistent visualizations at **4800 × 2700 px**.
 
-## Color Palette
+## Important: Large Canvas Size
 
-Use colors in this order for data series:
+pyplots renders at **4800 × 2700 px** (much larger than standard plots). All element sizes must be scaled for visibility!
 
-| #  | Name          | Hex       |
-|----|---------------|-----------|
-| 1  | Python Blue   | #306998   |
-| 2  | Python Yellow | #FFD43B   |
-| 3  | Signal Red    | #DC2626   |
-| 4  | Teal Green    | #059669   |
-| 5  | Violet        | #8B5CF6   |
-| 6  | Orange        | #F97316   |
+**Common Mistake:** Using default/standard sizes results in tiny, hard-to-see elements.
+
+---
 
 ## Dimensions
 
@@ -22,27 +17,59 @@ Use colors in this order for data series:
 | Image Size       | 4800 × 2700 px   |
 | Aspect Ratio     | 16:9             |
 
-## Typography & Lines (Recommended)
+---
+
+## Color Palette
+
+Primary colors (always use these first):
+
+| #  | Name          | Hex       |
+|----|---------------|-----------|
+| 1  | Python Blue   | #306998   |
+| 2  | Python Yellow | #FFD43B   |
+
+For additional colors: AI chooses appropriate, colorblind-safe colors.
+
+---
+
+## Visual Sizing Principles
+
+Since we render at 4800 × 2700 px, elements must be **visually prominent**:
+
+### Text
+- **Title**: Large and clearly readable
+- **Axis labels**: Prominent, not tiny
+- **Tick labels**: Readable at full image size
+- **Legend**: Easy to read
+
+### Data Elements
+- **Points/Markers**: Clearly visible, not tiny dots
+- **Lines**: Thick enough to see clearly
+- **Bars**: With subtle edges for definition
+
+### General Rules
+- Elements should be **~3-4x larger** than standard defaults
+- When in doubt, make it bigger
+- Test: Would this be readable on a 4K monitor?
+
+---
+
+## Grid
 
-These values typically work well at 4800 × 2700 px:
+- Subtle, not dominant
+- Low opacity (around 30%)
+- Should enhance readability, not distract
 
-| Element          | Size   |
-|------------------|--------|
-| Title            | 20pt   |
-| Axis Labels      | 20pt   |
-| Tick Labels      | 16pt   |
-| Legend           | 16pt   |
-| Annotations      | 14pt   |
-| Line Width       | 2 px   |
-| Marker Size      | 4 px   |
+---
 
 ## AI Discretion
 
-The following are left to AI judgment based on the specific visualization:
+The AI decides based on the specific library and visualization:
 
+- Exact sizes and parameters (library-specific)
 - Font family
-- Grid style and visibility
-- Tick configuration
-- Legend placement and styling
+- Grid style (on/off, dashed/solid)
+- Legend placement
+- Additional colors beyond the primary two
 
-Focus on **clarity and readability** for the specific plot type.
+**Priority:** Clarity and readability at 4800 × 2700 px.

prompts/library/altair.md

@@ -9,13 +9,16 @@ import altair as alt
 ## Create Chart
 
 ```python
-chart = alt.Chart(df).mark_point().encode(
+chart = alt.Chart(df).mark_point(size=150).encode(  # size ~3-4x default
     x='col_x:Q',
     y='col_y:Q'
 ).properties(
     width=1600,
     height=900,
-    title=title
+    title=alt.Title(title, fontSize=28)
+).configure_axis(
+    labelFontSize=18,
+    titleFontSize=22
 )
 ```
 

prompts/library/bokeh.md

@@ -55,12 +55,19 @@ export_png(p, filename='plot.png')
 
 **Note**: Requires `selenium` and WebDriver for PNG export.
 
-## Styling
+## Sizing for 4800×2700 px
 
 ```python
-p.xaxis.axis_label = x_label
-p.yaxis.axis_label = y_label
-# Grid: AI discretion
+# Text sizes
+p.title.text_font_size = '28pt'
+p.xaxis.axis_label_text_font_size = '22pt'
+p.yaxis.axis_label_text_font_size = '22pt'
+p.xaxis.major_label_text_font_size = '18pt'
+p.yaxis.major_label_text_font_size = '18pt'
+
+# Element sizes
+p.scatter(..., size=15)        # ~3-4x default
+p.line(..., line_width=3)
 ```
 
 ## Output File

prompts/library/highcharts.md

@@ -111,16 +111,32 @@ driver.quit()
 Path(temp_path).unlink()  # Clean up temp file
 ```
 
-## Chart Size
+## Sizing for 4800×2700 px
 
 ```python
-# Target: 4800 × 2700 px (see default-style-guide.md)
 chart.options.chart = {
-    'type': 'column',  # or 'bar', 'scatter', etc.
+    'type': 'column',
     'width': 4800,
     'height': 2700,
     'backgroundColor': '#ffffff'
 }
+
+# Text sizes
+chart.options.title = {'text': title, 'style': {'fontSize': '28px'}}
+chart.options.x_axis = {
+    'title': {'text': x_label, 'style': {'fontSize': '22px'}},
+    'labels': {'style': {'fontSize': '18px'}}
+}
+chart.options.y_axis = {
+    'title': {'text': y_label, 'style': {'fontSize': '22px'}},
+    'labels': {'style': {'fontSize': '18px'}}
+}
+
+# Marker sizes (in plotOptions)
+chart.options.plot_options = {
+    'scatter': {'marker': {'radius': 8}},  # ~3-4x default
+    'line': {'lineWidth': 3}
+}
 ```
 
 ## Output File

prompts/library/letsplot.md

@@ -19,11 +19,23 @@ plot = (
 )
 ```
 
-## Figure Size
+## Figure Size & Sizing for 4800×2700 px
 
 ```python
-# Target: 4800 × 2700 px (see default-style-guide.md)
-plot = plot + ggsize(1600, 900)  # Base size, scaled 3x on export
+# Base size (scaled 3x on export = 4800 × 2700 px)
+plot = plot + ggsize(1600, 900)
+
+# Text and element sizes
+plot = plot + theme(
+    axis_title=element_text(size=20),
+    axis_text=element_text(size=16),
+    plot_title=element_text(size=24),
+    legend_text=element_text(size=16)
+)
+
+# Element sizes in geoms
++ geom_point(size=4)    # ~3-4x default
++ geom_line(size=1.5)   # line width
 ```
 
 ## Save (PNG)

prompts/library/matplotlib.md

@@ -33,15 +33,32 @@ plt.scatter(x, y)
 plt.savefig('plot.png', dpi=300, bbox_inches='tight')
 ```
 
+## Sizing for 4800×2700 px
+
+```python
+# Text sizes
+ax.set_title(title, fontsize=24)
+ax.set_xlabel(x_label, fontsize=20)
+ax.set_ylabel(y_label, fontsize=20)
+ax.tick_params(axis='both', labelsize=16)
+ax.legend(fontsize=16)
+
+# Element sizes
+ax.scatter(x, y, s=200)      # s=150-300 (not s=50!)
+ax.plot(x, y, linewidth=3)   # linewidth=2-4 (not 1!)
+
+# Grid
+ax.grid(True, alpha=0.3, linestyle='--')
+```
+
 ## Styling
 
 ```python
-ax.set_xlabel(x_label)
-ax.set_ylabel(y_label)
-ax.set_title(title)
-ax.legend()  # if needed
+ax.set_xlabel(x_label, fontsize=20)
+ax.set_ylabel(y_label, fontsize=20)
+ax.set_title(title, fontsize=24)
+ax.legend(fontsize=16)  # if needed
 plt.tight_layout()
-# Grid: AI discretion
 ```
 
 ## API Compatibility (3.9+)

prompts/library/plotly.md

@@ -19,15 +19,19 @@ fig.add_trace(go.Scatter(x=x, y=y))
 fig = px.scatter(df, x='col_x', y='col_y')
 ```
 
-## Layout
+## Layout & Sizing for 4800×2700 px
 
 ```python
 fig.update_layout(
-    title=title,
-    xaxis_title=x_label,
-    yaxis_title=y_label,
-    template='plotly_white',  # Clean template
+    title=dict(text=title, font=dict(size=28)),
+    xaxis=dict(title=dict(text=x_label, font=dict(size=22)), tickfont=dict(size=18)),
+    yaxis=dict(title=dict(text=y_label, font=dict(size=22)), tickfont=dict(size=18)),
+    template='plotly_white',
 )
+
+# Marker/line sizes
+fig.update_traces(marker=dict(size=12))   # ~3-4x default
+fig.update_traces(line=dict(width=3))
 ```
 
 ## Save (PNG)

prompts/library/plotnine.md

@@ -22,10 +22,21 @@ plot = (
 )
 ```
 
-## Figure Size
+## Figure Size & Sizing for 4800×2700 px
 
 ```python
-plot = plot + theme(figure_size=(16, 9))
+plot = plot + theme(
+    figure_size=(16, 9),
+    text=element_text(size=14),           # Base text
+    axis_title=element_text(size=20),     # Axis labels
+    axis_text=element_text(size=16),      # Tick labels
+    plot_title=element_text(size=24),     # Title
+    legend_text=element_text(size=16)
+)
+
+# Element sizes in geoms
++ geom_point(size=4)    # ~3-4x default
++ geom_line(size=1.5)   # line width
 ```
 
 ## Save (PNG)

prompts/library/pygal.md

@@ -52,7 +52,7 @@ chart.render_to_file('plot.svg')
 chart.render_to_png('plot.png')
 ```
 
-## Styling
+## Sizing for 4800×2700 px
 
 ```python
 custom_style = Style(
@@ -61,7 +61,13 @@ custom_style = Style(
     foreground='#333',
     foreground_strong='#333',
     foreground_subtle='#666',
-    colors=('#3498db', '#2ecc71', '#e74c3c', '#9b59b6')
+    colors=('#306998', '#FFD43B'),  # pyplots primary colors
+    title_font_size=28,
+    label_font_size=18,
+    major_label_font_size=16,
+    legend_font_size=16,
+    value_font_size=14,
+    stroke_width=3              # line width
 )
 
 chart = pygal.Bar(style=custom_style)

prompts/library/seaborn.md

@@ -31,6 +31,23 @@ fig = g.figure
 plt.savefig('plot.png', dpi=300, bbox_inches='tight')
 ```
 
+## Sizing for 4800×2700 px
+
+```python
+# Text sizes (seaborn uses matplotlib underneath)
+ax.set_title(title, fontsize=24)
+ax.set_xlabel(x_label, fontsize=20)
+ax.set_ylabel(y_label, fontsize=20)
+ax.tick_params(axis='both', labelsize=16)
+
+# Or use sns.set_context for global scaling
+sns.set_context("talk", font_scale=1.2)
+
+# Element sizes in seaborn functions
+sns.scatterplot(..., s=200)           # marker size
+sns.lineplot(..., linewidth=3)        # line width
+```
+
 ## API Compatibility (0.14+)
 
 ```python