Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/cxcscmu/skilllearnbench/pillow-technical-drawingnpx skills add cxcscmu/SkillLearnBench --skill pillow-technical-drawinggit clone --depth 1 https://github.com/cxcscmu/SkillLearnBenchWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/cxcscmu/skilllearnbench/pillow-technical-drawing)<a href="https://agentmods.dev/skills/cxcscmu/skilllearnbench/pillow-technical-drawing"><img src="https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/pillow-technical-drawing.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00024 | $0.00470 |
| Opus 5 | $0.00012 | $0.00235 |
| Sonnet 5 | $0.00005 | $0.00094 |
| Haiku 4.5 | $0.00002 | $0.00047 |
Grade A, and why
pillow-technical-drawing scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Technical Drawing with Pillow
Setup
pip install Pillow
Key Patterns
Rounded Rectangles (component layers)
from PIL import Image, ImageDraw, ImageFont
img = Image.new('RGB', (1800, 2400), '#F5F4ED')
draw = ImageDraw.Draw(img)
# Rounded rectangle for a component layer
draw.rounded_rectangle([x1, y1, x2, y2], radius=12, fill='#D97757', outline='#141413', width=2)
Exploded-View Layout
- Stack layers vertically with consistent vertical gaps (60-100px)
- Offset each layer slightly on the X-axis for 3D depth illusion
- Use isometric-style parallelogram shapes for depth perception
Annotation Leader Lines
# Thin annotation line from component to label
draw.line([(comp_x, comp_y), (label_x, label_y)], fill='#B0ADA5', width=1)
# Small circle at the component end
draw.ellipse([comp_x-3, comp_y-3, comp_x+3, comp_y+3], fill='#B0ADA5')
Text Labels
font_heading = ImageFont.truetype("/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf", 72)
font_label = ImageFont.truetype("/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf", 24)
draw.text((x, y), "NOVA", fill='#141413', font=font_heading)
Isometric 3D Effect with Polygons
# Create parallelogram for isometric top face
top_face = [(x, y), (x+w, y-skew), (x+w+d, y-skew+d), (x+d, y+d)]
draw.polygon(top_face, fill=color, outline='#141413', width=1)
Saving
img.save('output.png', dpi=(300, 300))
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 58 lines · 24 tokens per session scan A 4e31f81f191a
pillow-technical-drawing is a skill published in the GitHub repository cxcscmu/SkillLearnBench (83 stars, last pushed 1mo ago), licensed MIT. It adds 24 tokens to every session and 470 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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