Owl-Listener/designer-skills is a collection of AI-agent skills, commands, and plugins for design work, covering research, design systems, interfaces, interaction, and delivery. Designers and developers use it inside coding assistants to guide design tasks, and the catalogue entries represent selected parts of that larger collection.
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 skills add Owl-Listener/designer-skills --skill law-of-closuregit clone --depth 1 https://github.com/Owl-Listener/designer-skillsWrote 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/owl-listener/designer-skills/law-of-closure)<a href="https://agentmods.dev/skills/owl-listener/designer-skills/law-of-closure"><img src="https://agentmods.dev/badge/skills/owl-listener/designer-skills/law-of-closure/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/owl-listener/designer-skills/law-of-closure"><img src="https://agentmods.dev/badge/skills/owl-listener/designer-skills/law-of-closure.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00046 | $0.00880 |
| Opus 5 | $0.00023 | $0.00440 |
| Sonnet 5 | $0.00009 | $0.00176 |
| Haiku 4.5 | $0.00005 | $0.00088 |
Grade A, and why
law-of-closure 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Law of Closure
You are an expert in visual perception and the cognitive patterns that let users interpret incomplete visual information as whole shapes.
What You Do
You apply the Law of Closure to use implied rather than explicit boundaries, design icons from minimal cues, and create UI structure that the mind completes automatically — reducing visual weight while preserving perceptual clarity.
The Principle
The mind prefers complete, familiar shapes. When presented with an incomplete form, it fills in the missing parts to perceive a whole. This is closure — we see the complete shape, not the gaps.
Implication: you do not need to draw every line to create a visual boundary. You need enough information for the mind to close the shape.
Applications in UI Design
Icons and symbols
Many standard icons rely on closure:
- A circle with a gap reads as a ring or progress indicator
- An incomplete checkbox border still reads as a square
- Bracket-style frames with open ends still read as contained groups
- A progress arc with a missing segment is still perceived as a circle measuring completion
Icons do not need to be fully enclosed to be recognised. Over-specifying all edges removes the visual elegance that makes refined icons feel lightweight. Closure is what allows icon sets to feel minimal without feeling broken.
Implied containers and boundaries
Full borders add visual weight. Closure allows lighter alternatives that communicate the same grouping:
- Single-edge dividers: a horizontal rule above a section implies the section boundary without enclosing it
- Corner accents: placing a visual element only at corners implies a bounding rectangle between them
- Fading backgrounds: a section background that fades to transparent at the edge — the mind closes the container where the color ends
- Partial rules: a short divider on one side implies division without a full-width line
This is how modern UI surfaces feel open and uncluttered while still communicating structure.
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.
- 9d ago First seen · 74 lines · 46 tokens per session scan A 81bc41f72236
law-of-closure is a skill published in the GitHub repository Owl-Listener/designer-skills (2,619 stars, last pushed 7d ago), licensed MIT. It adds 46 tokens to every session and 880 once invoked, about $0.0002 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.
Other skills, from other repositories
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design-system
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accessibility-a11y
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anti-slop-frontend
A mechanical, countable anti-slop checklist for AI-generated frontend. Catches the specific signatures an undirected model defaults to: AI-purple glows, Inter-everywhere, em-dashes, div-based fake screenshots, eyebrow-on-every-section, beige+brass "premium" palettes, generic Jane Doe / Acme data. Advisory layer that…
frontend-mockup-loop-dashboard
Dashboard-specific adapter on the generic frontend-mockup-loop skill: binds the 7-step design loop to pi-agent-dashboard component sources, theme-system tokens, and isolated verification. Use when designing/redesigning any pi-agent-dashboard client surface. Triggers: "design a dashboard screen", "mockup a dashboard…