canvas-design

name	canvas-design
description	Create beautiful visual art as .png and .pdf files using design philosophy. Use when the user asks to create a poster, visual artwork, design piece, or static visual output via code generation. Requires the execute tool and Python with Pillow/reportlab.
license	Apache-2.0
metadata	{"author":"anthropic","version":"1.0","adapted-for":"ai-media-canvas"}

Canvas Design Skill

These are instructions for creating visual artwork through code execution. Output .md (philosophy) + .pdf or .png (artwork) files.

Prerequisites

This skill requires:

• The execute tool (sandbox code execution)
• Python 3 with Pillow and reportlab installed
• Font files available at the path in $FONT_DIR environment variable

Workflow

Complete in two steps:

1. Design Philosophy Creation (.md concept)
2. Express by creating it on a canvas via Python code execution (.pdf or .png)

Step 1: Design Philosophy

Create a VISUAL PHILOSOPHY (not layouts or templates) that will be interpreted through:

• Form, space, color, composition
• Images, graphics, shapes, patterns
• Minimal text as visual accent

Name the movement (1-2 words): e.g., "Brutalist Joy" / "Chromatic Silence"

Articulate the philosophy (4-6 paragraphs) covering:

• Space and form
• Color and material
• Scale and rhythm
• Composition and balance
• Visual hierarchy

Critical guidelines:

• Avoid redundancy — each design aspect mentioned once
• Emphasize craftsmanship REPEATEDLY: "meticulously crafted", "master-level execution"
• Leave creative space for interpretation

Step 2: Canvas Creation

Use the execute tool to run Python code that generates the artwork.

IMPORTANT: Path Rules

Virtual paths vs real paths: the ls and read_file tools use virtual paths such as /skills/..., but the execute tool runs in a real shell. Python code must use real paths.

Rules:

1. Font paths: always use os.environ["FONT_DIR"]; do not hard-code paths.
2. Output files: always save with relative paths such as output.png; files are created in the sandbox working directory.
3. Do not use virtual paths from ls /skills/... inside Python code.

Font Usage

Fonts are accessed through the $FONT_DIR environment variable, which is preset in the sandbox:

import os
font_dir = os.environ["FONT_DIR"]  # Use the environment variable; do not hard-code paths.
fonts = [f for f in os.listdir(font_dir) if f.endswith(".ttf")]

Load fonts with Pillow:

from PIL import ImageFont
font = ImageFont.truetype(os.path.join(font_dir, "WorkSans-Bold.ttf"), size=48)

Or with reportlab for PDF:

from reportlab.pdfbase import pdfmetrics
from reportlab.pdfbase.ttfonts import TTFont
pdfmetrics.registerFont(TTFont("WorkSans", os.path.join(font_dir, "WorkSans-Bold.ttf")))

Available Font Families

Serif: CrimsonPro (Regular/Bold/Italic), Gloock, IBMPlexSerif (Regular/Bold/Italic/BoldItalic), InstrumentSerif, Italiana, LibreBaskerville, Lora, YoungSerif

Sans-serif: ArsenalSC, BricolageGrotesque (Regular/Bold), InstrumentSans, Jura, Outfit, PoiretOne, SmoochSans, WorkSans

Monospace: DMMono, GeistMono (Regular/Bold), IBMPlexMono (Regular/Bold), JetBrainsMono, RedHatMono, Tektur

Display: BigShoulders (Regular/Bold), Boldonse, EricaOne, NationalPark, Silkscreen, PixelifySans

Handwritten: NothingYouCouldDo

Design Principles

• Create museum/magazine-quality work — dense patterns, systematic shapes, clinical typography
• Use a limited color palette (3-5 colors) that feels intentional and cohesive
• Text is always minimal and visual-first — never paragraphs, only essential words
• Use DIFFERENT fonts for different roles (display, body, labels, accents)
• Nothing may overlap; all elements must stay within canvas boundaries with proper margins
• Never cartoony or amateur — even for playful subjects, maintain sophistication

Code Execution Pattern

Write a complete Python script, then execute it.

All write paths must be relative. Absolute paths can collide across concurrent users:

1. write_file path="generate.py"       <- relative path, not /tmp/xxx
2. execute: python3 generate.py
3. Output: img.save("output.png")      <- relative path
4. execute: pwd                        <- get the current working directory
5. persist_sandbox_file filePath="{pwd output}/output.png"

Do not write files with absolute paths:

• Bad: write_file path="/tmp/script.py" because users can overwrite each other.
• Good: write_file path="script.py" because each user has an independent sandbox.

Critical: In Python scripts:

• Use os.environ["FONT_DIR"] for font paths. This is the only allowed absolute path.
• Save output with RELATIVE paths (e.g., img.save("poster.png"))
• Do NOT use /skills/... paths — those are virtual backend paths, not real filesystem

Refinement Pass

After generating the initial artwork, take a second pass:

• Re-examine the code for alignment, spacing, color calibration
• Refine rather than add — make existing composition more cohesive
• The user expects "museum quality" — every detail matters

Step 3: Persist Output

After generating the artwork file, use the persist_sandbox_file tool to upload it to persistent storage. This gives the user a downloadable URL.

Important Notes

• Always write complete Python scripts — do not use placeholders
• Canvas size recommendation: 2400×3200 px for posters, 1920×1080 for landscapes
• Save output as PNG (for raster) or PDF (for print-quality)
• The subtle reference from the user's request should be woven into the art like a jazz musician quoting another song — perceptible to insiders but invisible to others