render-publication-graphic
Über
Diese Fähigkeit erzeugt druckfertige 2D-Grafiken mit korrekter DPI, Farbprofilen und Typografie für Druck und digitale Nutzung. Sie ist für die Erstellung von Journal-Abbildungen, Druckmaterialien und zur Einhaltung technischer Spezifikationen konzipiert und unterstützt Multi-Format-Exporte aus einer einzigen Quelle. Entwickler können sie nutzen, um die Erstellung von Grafiken zu automatisieren, die strengen Publikationsanforderungen entsprechen.
Schnellinstallation
Claude Code
Empfohlennpx skills add pjt222/agent-almanac -a claude-code/plugin add https://github.com/pjt222/agent-almanacgit clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/render-publication-graphicKopieren Sie diesen Befehl und fügen Sie ihn in Claude Code ein, um diese Fähigkeit zu installieren
Dokumentation
Render Publication Graphic
Produce pub-ready graphics meeting tech req for journals, books, presentations, web. DPI, color space, typography, file format select, metadata embed.
Use When
- Prep figures for journal submission
- Graphics for print pubs (books, mags)
- High-quality assets for presentations
- Web pubs w/ proper opt
- Meet pub tech specs
- Archive w/ proper metadata
- Multi-format from single source
In
| Input | Type | Description | Example |
|---|---|---|---|
| Source graphic | File/Data | Original visualization or artwork | SVG, R ggplot, Python matplotlib, Blender render |
| Publication target | Specification | Journal, web, print, presentation | Nature journal, IEEE paper, website |
| Technical requirements | Parameters | DPI, dimensions, color space, format | 300 DPI, 180mm width, CMYK, TIFF |
| Style guide | Document | Publisher typography and formatting rules | Font families, line widths, color palette |
| Metadata | Information | Title, author, date, copyright, description | Figure caption, license info |
Do
1. Determine Output Req
ID tech specs for target pub:
# Common publication requirements
academic_journal:
dpi: 300-600
format: TIFF, EPS, PDF
color_space: RGB or CMYK (check guidelines)
max_width: 180mm (single column) or 390mm (double column)
fonts: Embed or outline
resolution_minimums:
line_art: 1000 DPI
halftone: 300 DPI
combination: 600 DPI
web_publication:
dpi: 72-96 (retina: 144-192)
format: PNG, WebP, SVG
color_space: sRGB
max_file_size: 200KB-500KB
optimization: Compress, progressive loading
presentation:
dpi: 96-150
format: PNG, PDF, SVG
color_space: RGB
dimensions: 16:9 or 4:3 aspect ratio
contrast: High contrast for projectors
print_book:
dpi: 300-600
format: TIFF, PDF/X
color_space: CMYK
bleed: 3-5mm beyond trim
fonts: Embedded
→ Clear understanding of target req If err: contact pub for specific guidelines, use conservative defaults
2. Set Correct DPI for Raster
Configure resolution by output medium:
from PIL import Image
def set_dpi_pillow(image_path, output_path, target_dpi=300):
"""Set DPI metadata for PNG/TIFF."""
img = Image.open(image_path)
# Save with DPI metadata
img.save(output_path, dpi=(target_dpi, target_dpi))
print(f"Saved with {target_dpi} DPI: {output_path}")
def calculate_dimensions(width_mm, height_mm, dpi=300):
"""Calculate pixel dimensions from physical size."""
# Convert mm to inches
width_inches = width_mm / 25.4
height_inches = height_mm / 25.4
# Calculate pixels
width_px = int(width_inches * dpi)
height_px = int(height_inches * dpi)
return width_px, height_px
# Example: 180mm wide figure at 300 DPI
width, height = calculate_dimensions(180, 120, dpi=300)
print(f"Required resolution: {width}x{height} pixels")
# Output: Required resolution: 2126x1417 pixels
# R ggplot2 export with proper DPI
library(ggplot2)
# Create plot
p <- ggplot(mtcars, aes(x = wt, y = mpg)) +
geom_point() +
theme_minimal(base_size = 12)
# Save for publication (300 DPI)
ggsave(
filename = "figure1.png",
plot = p,
width = 180,
height = 120,
units = "mm",
dpi = 300
)
# Save as vector for flexibility
ggsave(
filename = "figure1.pdf",
plot = p,
width = 180,
height = 120,
units = "mm",
device = cairo_pdf # Better text rendering
)
→ Graphics rendered at correct resolution for print quality If err: verify DPI metadata saved correctly, check file size appropriate
3. Configure Color Space
Set appropriate color profile:
from PIL import Image, ImageCms
def convert_to_cmyk(rgb_image_path, cmyk_output_path):
"""Convert RGB to CMYK for print."""
img = Image.open(rgb_image_path)
if img.mode != 'RGB':
img = img.convert('RGB')
# Convert to CMYK
cmyk_img = img.convert('CMYK')
cmyk_img.save(cmyk_output_path, format='TIFF', compression='tiff_lzw')
print(f"Converted to CMYK: {cmyk_output_path}")
def apply_srgb_profile(image_path, output_path):
"""Apply sRGB profile for web."""
img = Image.open(image_path)
# sRGB profile (embedded in Pillow)
srgb_profile = ImageCms.createProfile('sRGB')
# Convert to sRGB
img_srgb = ImageCms.profileToProfile(
img,
srgb_profile,
srgb_profile,
renderingIntent=ImageCms.Intent.PERCEPTUAL
)
img_srgb.save(output_path)
# ImageMagick for color space conversion
convert input.png -colorspace sRGB output_srgb.png
convert input.png -colorspace CMYK output_cmyk.tiff
# Check color profile
identify -verbose image.png | grep -i colorspace
→ Color space matches pub req If err: verify color profile embedded, test print preview
4. Configure Typography
Ensure text readable + properly formatted:
from PIL import ImageFont
def get_publication_fonts():
"""Load fonts appropriate for publication."""
# Common publication-safe fonts
fonts = {
'serif': 'Times New Roman',
'sans': 'Arial',
'mono': 'Courier New'
}
try:
# Load with proper size for DPI
# At 300 DPI, 12pt = 12 * 300/72 = 50 pixels
base_size_300dpi = 50
font_regular = ImageFont.truetype(f"{fonts['sans']}.ttf", base_size_300dpi)
font_bold = ImageFont.truetype(f"{fonts['sans']} Bold.ttf", base_size_300dpi)
return {'regular': font_regular, 'bold': font_bold}
except:
return {'regular': ImageFont.load_default(), 'bold': ImageFont.load_default()}
# Typography guidelines
typography_specs = {
'minimum_font_size': '8pt', # Readable when printed
'line_width_min': 0.5, # Points, for print clarity
'panel_labels': {
'font': 'Arial Bold',
'size': '12pt',
'position': 'top-left',
'style': 'A, B, C' # Or (a), (b), (c)
},
'axis_labels': {
'font': 'Arial',
'size': '10pt'
},
'legend': {
'font': 'Arial',
'size': '9pt',
'position': 'outside plot area'
}
}
# R publication-quality typography
library(ggplot2)
p <- ggplot(mtcars, aes(x = wt, y = mpg)) +
geom_point(size = 2) +
labs(
title = "Fuel Efficiency vs Weight",
x = "Weight (1000 lbs)",
y = "Miles per Gallon"
) +
theme_bw(base_size = 12, base_family = "Arial") +
theme(
plot.title = element_text(size = 14, face = "bold"),
axis.title = element_text(size = 12),
axis.text = element_text(size = 10),
legend.text = element_text(size = 10),
panel.grid.minor = element_blank(),
# Ensure text is black for print
text = element_text(color = "black")
)
→ Text readable at pub size, fonts embedded properly If err: increase font sizes, check font licensing, convert text to outlines
5. Select File Format
Choose by use case:
def export_multi_format(source_path, output_base, formats=['png', 'pdf', 'tiff']):
"""Export graphic in multiple formats."""
from PIL import Image
import cairosvg
import os
base, ext = os.path.splitext(output_base)
if ext.lower() in ['.svg']:
# SVG source - convert to rasters
for fmt in formats:
output = f"{base}.{fmt}"
if fmt == 'png':
cairosvg.svg2png(
url=source_path,
write_to=output,
output_width=2126, # 180mm @ 300 DPI
output_height=1417 # 120mm @ 300 DPI
)
elif fmt == 'pdf':
cairosvg.svg2pdf(url=source_path, write_to=output)
elif fmt == 'tiff':
# Convert via PNG intermediate
temp_png = f"{base}_temp.png"
cairosvg.svg2png(url=source_path, write_to=temp_png)
img = Image.open(temp_png)
img.save(output, format='TIFF', compression='tiff_lzw')
os.remove(temp_png)
else:
# Raster source
img = Image.open(source_path)
for fmt in formats:
output = f"{base}.{fmt}"
if fmt == 'png':
img.save(output, format='PNG', dpi=(300, 300), optimize=True)
elif fmt == 'tiff':
img.save(output, format='TIFF', compression='tiff_lzw', dpi=(300, 300))
elif fmt == 'pdf':
# Use img2pdf or similar for raster-to-PDF
img.save(output, format='PDF', resolution=300.0)
print(f"Exported in formats: {', '.join(formats)}")
# Format selection guide
format_guide = {
'TIFF': {
'use_for': 'Journal submission, archival',
'benefits': 'Lossless, supports CMYK, high quality',
'compression': 'LZW or ZIP (lossless)'
},
'PDF': {
'use_for': 'Submission, print, archival',
'benefits': 'Vector or raster, text searchable, widely accepted',
'variants': 'PDF/A (archival), PDF/X (print)'
},
'PNG': {
'use_for': 'Web, presentations, digital',
'benefits': 'Lossless, transparency, good compression',
'limitation': 'RGB only, larger than JPEG'
},
'SVG': {
'use_for': 'Web, further editing, scalable graphics',
'benefits': 'Vector, infinitely scalable, small file size',
'limitation': 'Not always accepted by journals'
},
'EPS': {
'use_for': 'Legacy journal requirements',
'benefits': 'Vector format accepted by older systems',
'limitation': 'Being phased out, use PDF instead'
}
}
→ Appropriate format for pub channel If err: check pub req, provide multi formats
6. Optimize for Web
Create web-optimized vers:
def optimize_for_web(input_path, output_path, max_width=1200, quality=85):
"""Optimize image for web publication."""
from PIL import Image
img = Image.open(input_path)
# Resize if too large
if img.width > max_width:
ratio = max_width / img.width
new_height = int(img.height * ratio)
img = img.resize((max_width, new_height), Image.LANCZOS)
# Convert to RGB if needed
if img.mode in ('RGBA', 'LA', 'P'):
background = Image.new('RGB', img.size, (255, 255, 255))
if img.mode == 'P':
img = img.convert('RGBA')
background.paste(img, mask=img.split()[-1] if 'A' in img.mode else None)
img = background
# Save optimized
img.save(output_path, format='JPEG', quality=quality, optimize=True, progressive=True)
# Check file size
import os
file_size_kb = os.path.getsize(output_path) / 1024
print(f"Optimized: {file_size_kb:.1f} KB")
def create_responsive_set(input_path, output_base):
"""Create multiple resolutions for responsive web."""
from PIL import Image
img = Image.open(input_path)
sizes = [
(640, '640w'),
(1024, '1024w'),
(1920, '1920w')
]
for width, suffix in sizes:
if img.width >= width:
ratio = width / img.width
height = int(img.height * ratio)
resized = img.resize((width, height), Image.LANCZOS)
output = f"{output_base}_{suffix}.jpg"
resized.save(output, format='JPEG', quality=85, optimize=True)
→ Web-optimized images < 500KB, responsive sizes generated If err: reduce quality, resize further, consider WebP format
7. Embed Metadata
Add descriptive metadata for archival:
from PIL import Image
from PIL.PngImagePlugin import PngInfo
def embed_metadata(image_path, output_path, metadata):
"""Embed metadata in PNG."""
img = Image.open(image_path)
# Create metadata
png_info = PngInfo()
for key, value in metadata.items():
png_info.add_text(key, str(value))
# Save with metadata
img.save(output_path, format='PNG', pnginfo=png_info)
# Example metadata
metadata = {
'Title': 'Figure 1: Relationship between weight and fuel efficiency',
'Author': 'Jane Doe',
'Description': 'Scatter plot showing negative correlation',
'Copyright': 'CC-BY 4.0',
'Software': 'R 4.3.0, ggplot2 3.4.0',
'Creation Date': '2026-02-16',
'Source': 'mtcars dataset'
}
embed_metadata('figure1.png', 'figure1_with_metadata.png', metadata)
→ Metadata embedded + retrievable If err: check format supports metadata (PNG, TIFF, PDF yes; JPEG limited)
Check
- DPI meets pub req (typically 300+)
- Physical dims correct for pub
- Color space appropriate (RGB web, CMYK print)
- Format accepted by publisher
- Text readable at pub size
- Fonts embedded or outlined
- Line widths visible printed
- Color contrast sufficient grayscale
- File size in limits
- Metadata embedded
- Tested print preview or rendering
Traps
- Insufficient resolution: 72 DPI web cannot print at quality
- Wrong color space: RGB may print diff than displayed
- Font substitution: Non-embedded fonts replaced w/ defaults
- Small text: Fonts < 8pt may be illegible printed
- Thin lines: Lines < 0.5pt may not print clearly
- File size: High DPI very large, compress appropriately
- Compression artifacts: JPEG unsuitable for line art or text
- Missing bleed: Print needs 3-5mm bleed beyond trim
- Transparency issues: Some formats don't preserve correctly
- Aspect ratio: Distortion from incorrect dimension calc
→
- create-2d-composition: Create source graphics
- render-blender-output: 3D render settings for pub
- generate-quarto-report: Integrate graphics → docs
GitHub Repository
Verwandte Skills
executing-plans
DesignVerwenden Sie die Fähigkeit "executing-plans", wenn Sie einen vollständigen Implementierungsplan zur Ausführung in kontrollierten Batches mit Überprüfungspunkten vorliegen haben. Sie lädt den Plan und überprüft ihn kritisch, führt dann Aufgaben in kleinen Batches (standardmäßig 3 Aufgaben) aus und meldet den Fortschritt zwischen jedem Batch zur Überprüfung durch den Architekten. Dies gewährleistet eine systematische Implementierung mit integrierten Qualitätskontrollpunkten.
requesting-code-review
DesignDiese Fähigkeit sendet einen Unteragenten für Code-Review, um Codeänderungen anhand der Anforderungen zu analysieren, bevor fortgefahren wird. Sie sollte nach dem Abschließen von Aufgaben, der Implementierung größerer Funktionen oder vor dem Zusammenführen in den Hauptzweig verwendet werden. Die Überprüfung hilft dabei, Probleme frühzeitig zu erkennen, indem die aktuelle Implementierung mit dem ursprünglichen Plan verglichen wird.
connect-mcp-server
DesignDiese Fähigkeit bietet Entwicklern eine umfassende Anleitung, um MCP-Server über HTTP-, stdio- oder SSE-Transports mit Claude Code zu verbinden. Sie behandelt Installation, Konfiguration, Authentifizierung und Sicherheit für die Integration externer Dienste wie GitHub, Notion und benutzerdefinierter APIs. Nutzen Sie sie beim Einrichten von MCP-Integrationen, bei der Konfiguration externer Tools oder bei der Arbeit mit Claude's Model Context Protocol.
web-cli-teleport
DesignDiese Fähigkeit unterstützt Entwickler bei der Wahl zwischen Claude Code Web- und CLI-Schnittstellen basierend auf Aufgabenanalysen und ermöglicht nahtloses Session-Teleporting zwischen diesen Umgebungen. Sie optimiert den Workflow, indem sie den Sitzungsstatus und Kontext beim Wechsel zwischen Web, CLI oder Mobilgeräten verwaltet. Nutzen Sie sie für komplexe Projekte, die in verschiedenen Phasen unterschiedliche Werkzeuge erfordern.
