# Canvas Design

> 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.

- Skill: `fancyboi999/canvas-design` (Agent Skill, multi-file: 55 files)
- Install (CLI): `npx skillmds@latest add fancyboi999/canvas-design`
- Raw SKILL.md: https://api.skillmd.com/api/skills/fancyboi999/canvas-design/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Design & Media
- License: Apache-2.0
- Author: fancyboi999 (https://skillmd.com/u/fancyboi999)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/fancyboi999/canvas-design

---


# 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

**虚拟路径 vs 真实路径**：`ls` 和 `read_file` 工具使用虚拟路径（如 `/skills/...`），
但 `execute` 工具运行在真实 shell 中。Python 代码里**必须使用真实路径**。

规则：
1. **字体路径**：永远用 `os.environ["FONT_DIR"]`，不要硬编码
2. **输出文件**：永远用相对路径保存（如 `output.png`），文件会在沙箱工作目录中
3. **不要**把 `ls /skills/...` 看到的虚拟路径用在 Python 代码里

### Font Usage

字体通过 `$FONT_DIR` 环境变量访问（已在沙箱中预设）：

```python
import os
font_dir = os.environ["FONT_DIR"]  # 必须用环境变量，不要硬编码路径
fonts = [f for f in os.listdir(font_dir) if f.endswith(".ttf")]
```

Load fonts with Pillow:
```python
from PIL import ImageFont
font = ImageFont.truetype(os.path.join(font_dir, "WorkSans-Bold.ttf"), size=48)
```

Or with reportlab for PDF:
```python
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.

**所有路径必须用相对路径**（多用户并发时绝对路径会冲突）：

```
1. write_file path="generate.py"       ← 相对路径，不要用 /tmp/xxx
2. execute: python3 generate.py
3. Output: img.save("output.png")      ← 相对路径
4. execute: pwd                        ← 获取当前工作目录的完整路径
5. persist_sandbox_file filePath="{pwd输出}/output.png"
```

**禁止使用绝对路径写文件**：
- ❌ `write_file path="/tmp/script.py"` — 多用户会覆盖
- ✅ `write_file path="script.py"` — 每个用户独立沙箱

**Critical**: In Python scripts:
- Use `os.environ["FONT_DIR"]` for font paths（唯一允许的绝对路径）
- 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