MCP HubMCP Hub
Volver a habilidades

create-2d-composition

pjt222
Actualizado 2 days ago
7 vistas
17
2
17
Ver en GitHub
Metaautomationdesigndata

Acerca de

Esta habilidad permite la generación programática de gráficos 2D como diagramas, gráficos y recursos visuales mediante la creación de SVG y algoritmos de diseño. Es ideal para automatizar figuras reproducibles, construir visualizaciones personalizadas o producir gráficos por lotes con variaciones de parámetros. Los desarrolladores pueden utilizarla cuando las bibliotecas de gráficos estándar son insuficientes o cuando se necesitan flujos de trabajo de producción gráfica programables.

Instalación rápida

Claude Code

Recomendado
Principal
npx skills add pjt222/agent-almanac -a claude-code
Comando PluginAlternativo
/plugin add https://github.com/pjt222/agent-almanac
Git CloneAlternativo
git clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/create-2d-composition

Copia y pega este comando en Claude Code para instalar esta habilidad

Documentación

Create 2D Composition

Generate 2D graphics programmatically using SVG construction, diagram layout algorithms, image compositing, and batch processing workflows. Covers vector graphics generation, raster image manipulation, typography, and automated production of charts, diagrams, and infographics.

适用场景

  • Generating diagrams, flowcharts, or infographics programmatically
  • Creating reproducible scientific figures or publication graphics
  • Automating production of badges, icons, or visual assets
  • Compositing multiple images or data visualizations
  • Building custom chart types not available in standard libraries
  • Batch generating graphics with parameter variations
  • Creating SVG templates for web or print applications

输入

InputTypeDescriptionExample
Layout specificationConfigurationDimensions, margins, grid layoutCanvas 800x600px, 20px margins
Visual elementsData/AssetsShapes, text, images, data pointsRectangle coordinates, labels, icons
Style parametersCSS/AttributesColors, fonts, stroke widths, opacityfill="#3366cc", stroke-width="2"
Data sourcesFiles/ArraysValues to visualize or annotateCSV data, JSON configuration
Output formatStringSVG, PNG, PDF, composite formatsoutput.svg, 300 DPI PNG

步骤

1. Set Up Python Environment

Install required libraries for 2D composition:

# Core libraries
pip install svgwrite pillow cairosvg

# Optional: advanced features
pip install drawsvg reportlab pycairo

# For data-driven graphics
pip install matplotlib numpy pandas

预期结果: Libraries installed successfully 失败处理: Check Python version (3.7+), use virtual environment to avoid conflicts

2. Create Basic SVG Graphics

Generate SVG using svgwrite:

import svgwrite
from svgwrite import cm, mm

def create_basic_svg(output_path):
    """Create a simple SVG graphic."""
    # Initialize drawing (use mm for precise dimensions)
    dwg = svgwrite.Drawing(output_path, size=('180mm', '120mm'), profile='full')

    # Add background rectangle
    dwg.add(dwg.rect(
        insert=(0, 0),
        size=('100%', '100%'),
        fill='white'
    ))

    # Add shapes
    dwg.add(dwg.circle(
        center=(90*mm, 60*mm),
        r=30*mm,
        fill='lightblue',
        stroke='navy',
        stroke_width=2
    ))

    dwg.add(dwg.rect(
        insert=(30*mm, 30*mm),
        size=(60*mm, 40*mm),
        fill='lightgreen',
        stroke='darkgreen',
        stroke_width=2,
        rx=5,  # Rounded corners
        ry=5
    ))

    # Add text
    dwg.add(dwg.text(
        'Example Graphic',
        insert=(90*mm, 20*mm),
        text_anchor='middle',
        font_size='18pt',
        font_family='Arial',
        fill='black'
    ))

    dwg.save()
    print(f"Saved: {output_path}")

预期结果: SVG file generated with shapes and text 失败处理: Check svgwrite version, verify output directory writable

3. Build Diagrams with Layout Logic

Create structured diagrams with calculated positioning:

def create_flowchart(steps, output_path):
    """Generate a flowchart from list of steps."""
    dwg = svgwrite.Drawing(output_path, size=('800px', '600px'))

    # Layout parameters
    box_width = 120
    box_height = 60
    spacing_y = 100
    start_x = 340
    start_y = 50

    for i, step in enumerate(steps):
        y_pos = start_y + i * spacing_y

        # Draw box
        box = dwg.add(dwg.g(id=f'step_{i}'))

        box.add(dwg.rect(
            insert=(start_x, y_pos),
            size=(box_width, box_height),
            fill='lightblue',
            stroke='navy',
            stroke_width=2,
            rx=5,
            ry=5
        ))

        # Add text (wrapped if needed)
        text_lines = wrap_text(step, max_width=16)
        text_y = y_pos + box_height/2 - (len(text_lines)-1) * 7

        for j, line in enumerate(text_lines):
            box.add(dwg.text(
                line,
                insert=(start_x + box_width/2, text_y + j*14),
                text_anchor='middle',
                font_size='12pt',
                font_family='Arial',
                fill='black'
            ))

        # Draw arrow to next step
        if i < len(steps) - 1:
            arrow_start_y = y_pos + box_height
            arrow_end_y = y_pos + spacing_y

            dwg.add(dwg.line(
                start=(start_x + box_width/2, arrow_start_y),
                end=(start_x + box_width/2, arrow_end_y),
                stroke='black',
                stroke_width=2,
                marker_end=dwg.marker(
                    id='arrow',
                    viewBox='0 0 10 10',
                    refX=5,
                    refY=5,
                    markerWidth=6,
                    markerHeight=6,
                    orient='auto'
                )
            ))

    dwg.save()

def wrap_text(text, max_width=20):
    """Simple text wrapping."""
    words = text.split()
    lines = []
    current_line = []

    for word in words:
        test_line = ' '.join(current_line + [word])
        if len(test_line) <= max_width:
            current_line.append(word)
        else:
            if current_line:
                lines.append(' '.join(current_line))
            current_line = [word]

    if current_line:
        lines.append(' '.join(current_line))

    return lines

预期结果: Flowchart with connected boxes and arrows 失败处理: Adjust layout calculations, verify arrow marker definitions

4. Composite Raster Images

Combine multiple images using Pillow:

from PIL import Image, ImageDraw, ImageFont, ImageFilter
import os

def composite_images(image_paths, output_path, layout='grid'):
    """Composite multiple images into single output."""
    # Load images
    images = [Image.open(path) for path in image_paths]

    if layout == 'grid':
        # Calculate grid dimensions
        n = len(images)
        cols = int(n ** 0.5)
        rows = (n + cols - 1) // cols

        # Get max dimensions
        max_width = max(img.width for img in images)
        max_height = max(img.height for img in images)

        # Create composite canvas
        canvas_width = cols * max_width
        canvas_height = rows * max_height
        composite = Image.new('RGB', (canvas_width, canvas_height), 'white')

        # Paste images
        for i, img in enumerate(images):
            row = i // cols
            col = i % cols
            x = col * max_width
            y = row * max_height
            composite.paste(img, (x, y))

    elif layout == 'horizontal':
        # Horizontal concatenation
        total_width = sum(img.width for img in images)
        max_height = max(img.height for img in images)
        composite = Image.new('RGB', (total_width, max_height), 'white')

        x_offset = 0
        for img in images:
            composite.paste(img, (x_offset, 0))
            x_offset += img.width

    elif layout == 'vertical':
        # Vertical concatenation
        max_width = max(img.width for img in images)
        total_height = sum(img.height for img in images)
        composite = Image.new('RGB', (max_width, total_height), 'white')

        y_offset = 0
        for img in images:
            composite.paste(img, (0, y_offset))
            y_offset += img.height

    composite.save(output_path)
    print(f"Saved composite: {output_path}")

def add_annotations(image_path, annotations, output_path):
    """Add text annotations to image."""
    img = Image.open(image_path)
    draw = ImageDraw.Draw(img)

    # Load font
    try:
        font = ImageFont.truetype("Arial.ttf", 24)
    except:
        font = ImageFont.load_default()

    for annotation in annotations:
        text = annotation['text']
        position = annotation['position']
        color = annotation.get('color', 'black')

        # Add text shadow for readability
        shadow_offset = 2
        draw.text(
            (position[0] + shadow_offset, position[1] + shadow_offset),
            text,
            font=font,
            fill='white'
        )
        draw.text(position, text, font=font, fill=color)

    img.save(output_path)

预期结果: Composite image created with proper layout 失败处理: Check all input images exist, verify image modes compatible

5. Generate Data-Driven Graphics

Create visualizations from data:

import numpy as np

def create_bar_chart_svg(data, labels, output_path):
    """Generate SVG bar chart from data."""
    dwg = svgwrite.Drawing(output_path, size=('600px', '400px'))

    # Chart area
    margin = 50
    chart_width = 500
    chart_height = 300
    bar_spacing = 10

    # Calculate bar dimensions
    n_bars = len(data)
    bar_width = (chart_width - (n_bars - 1) * bar_spacing) / n_bars

    # Scale data to fit chart
    max_value = max(data)
    scale = chart_height / max_value

    # Draw axes
    dwg.add(dwg.line(
        start=(margin, margin),
        end=(margin, margin + chart_height),
        stroke='black',
        stroke_width=2
    ))
    dwg.add(dwg.line(
        start=(margin, margin + chart_height),
        end=(margin + chart_width, margin + chart_height),
        stroke='black',
        stroke_width=2
    ))

    # Draw bars
    for i, (value, label) in enumerate(zip(data, labels)):
        x = margin + i * (bar_width + bar_spacing)
        bar_height = value * scale
        y = margin + chart_height - bar_height

        # Bar
        dwg.add(dwg.rect(
            insert=(x, y),
            size=(bar_width, bar_height),
            fill='steelblue',
            stroke='navy',
            stroke_width=1
        ))

        # Value label
        dwg.add(dwg.text(
            f'{value:.1f}',
            insert=(x + bar_width/2, y - 5),
            text_anchor='middle',
            font_size='10pt',
            fill='black'
        ))

        # X-axis label
        dwg.add(dwg.text(
            label,
            insert=(x + bar_width/2, margin + chart_height + 20),
            text_anchor='middle',
            font_size='10pt',
            fill='black'
        ))

    dwg.save()

预期结果: SVG bar chart with scaled data 失败处理: Handle edge cases (empty data, negative values), add validation

6. Batch Generate Graphics

Automate creation of multiple graphics:

def batch_generate_badges(users, template_path, output_dir):
    """Generate badge for each user."""
    os.makedirs(output_dir, exist_ok=True)

    for user in users:
        output_path = os.path.join(output_dir, f"{user['id']}_badge.svg")

        dwg = svgwrite.Drawing(output_path, size=('300px', '100px'))

        # Background
        dwg.add(dwg.rect(
            insert=(0, 0),
            size=('100%', '100%'),
            fill='#3366cc',
            rx=10,
            ry=10
        ))

        # User name
        dwg.add(dwg.text(
            user['name'],
            insert=(150, 40),
            text_anchor='middle',
            font_size='20pt',
            font_weight='bold',
            fill='white'
        ))

        # User role
        dwg.add(dwg.text(
            user['role'],
            insert=(150, 70),
            text_anchor='middle',
            font_size='14pt',
            fill='lightblue'
        ))

        dwg.save()
        print(f"Generated badge: {output_path}")

预期结果: Individual graphic generated for each data item 失败处理: Check data structure, handle missing fields with defaults

7. Convert SVG to Raster

Export SVG to PNG/PDF for various uses:

import cairosvg

def svg_to_png(svg_path, png_path, dpi=300):
    """Convert SVG to PNG with specified DPI."""
    # Calculate pixel dimensions from DPI
    # Assuming A4 size as example
    width_inches = 8.27
    height_inches = 11.69

    width_px = int(width_inches * dpi)
    height_px = int(height_inches * dpi)

    cairosvg.svg2png(
        url=svg_path,
        write_to=png_path,
        output_width=width_px,
        output_height=height_px
    )
    print(f"Converted to PNG: {png_path}")

def svg_to_pdf(svg_path, pdf_path):
    """Convert SVG to PDF."""
    cairosvg.svg2pdf(url=svg_path, write_to=pdf_path)
    print(f"Converted to PDF: {pdf_path}")

预期结果: Raster output generated at specified resolution 失败处理: Install cairo system library if missing, check SVG validity

Validation Checklist

  • Graphics render correctly in target applications
  • Text is readable and properly positioned
  • Colors match specifications (check hex codes)
  • Dimensions appropriate for use case
  • SVG validates against standard (if required)
  • Raster exports have correct DPI
  • Layout adapts to data variations
  • Batch processing completes without errors
  • Output files organized logically
  • Code includes error handling

常见问题

  1. Unit confusion: SVG units (px, mm, cm) vs screen pixels vs print DPI
  2. Text overflow: Text exceeding shape boundaries, implement wrapping
  3. Font availability: System fonts may differ, embed or use web-safe fonts
  4. Coordinate calculations: Off-by-one errors in grid layouts
  5. Color format: SVG uses hex strings (#rrggbb), not tuples
  6. SVG validity: Check XML structure, close all tags
  7. File paths: Handle special characters and spaces in filenames
  8. Memory/aspect ratio: Chunk large batches; maintain proportions when resizing; PNG supports alpha, JPEG does not

相关技能

Repositorio GitHub

pjt222/agent-almanac
Ruta: i18n/zh-CN/skills/create-2d-composition
0
agentsagentskillsai-assisted-developmentclaude-codeskillsteams

Habilidades relacionadas

content-collections

Meta

Esta habilidad proporciona una configuración probada en producción para Content Collections, una herramienta centrada en TypeScript que transforma archivos Markdown/MDX en colecciones de datos con tipado seguro mediante validación Zod. Úsala al construir blogs, sitios de documentación o aplicaciones Vite + React con mucho contenido para garantizar seguridad de tipos y validación automática de contenido. Abarca todo, desde la configuración del plugin de Vite y compilación MDX hasta la optimización de despliegue y validación de esquemas.

Ver habilidad

polymarket

Meta

Esta habilidad permite a los desarrolladores crear aplicaciones con la plataforma de mercados de predicción Polymarket, incluyendo la integración de API para operaciones y datos de mercado. También proporciona transmisión de datos en tiempo real a través de WebSocket para monitorear operaciones en vivo y actividad del mercado. Úsela para implementar estrategias de trading o crear herramientas que procesen actualizaciones de mercado en tiempo real.

Ver habilidad

creating-opencode-plugins

Meta

Esta habilidad ayuda a los desarrolladores a crear complementos de OpenCode que se conectan a más de 25 tipos de eventos, como comandos, archivos y operaciones LSP. Proporciona la estructura del complemento, las especificaciones de la API de eventos y los patrones de implementación para módulos en JavaScript/TypeScript. Úsala cuando necesites interceptar, monitorear o extender el ciclo de vida del asistente de IA de OpenCode con lógica personalizada basada en eventos.

Ver habilidad

sglang

Meta

SGLang es un framework de alto rendimiento para el servicio de LLM que se especializa en generación rápida y estructurada para JSON, expresiones regulares y flujos de trabajo de agentes utilizando su caché de prefijos RadixAttention. Ofrece una inferencia significativamente más rápida, especialmente para tareas con prefijos repetidos, lo que lo hace ideal para salidas complejas y estructuradas, y conversaciones multiturno. Elige SGLang sobre alternativas como vLLM cuando necesites decodificación restringida o estés construyendo aplicaciones con uso extensivo de prefijos compartidos.

Ver habilidad