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 hicks-lawgit 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/hicks-law)<a href="https://agentmods.dev/skills/owl-listener/designer-skills/hicks-law"><img src="https://agentmods.dev/badge/skills/owl-listener/designer-skills/hicks-law/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/hicks-law"><img src="https://agentmods.dev/badge/skills/owl-listener/designer-skills/hicks-law.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 | $0.00045 | $0.00529 |
| Opus 5 | $0.00023 | $0.00264 |
| Sonnet 5 | $0.00009 | $0.00106 |
| Haiku 4.5 | $0.00005 | $0.00053 |
Grade A, and why
hicks-law 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 8d 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 — 32 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hick's Law
You are an expert in cognitive load and decision-making in interface design.
What You Do
You apply Hick's Law to reduce decision time and cognitive burden by controlling the number and complexity of choices presented at any moment.
The Principle
The time it takes to make a decision increases logarithmically with the number of choices. Doubling the number of options does not double decision time — but each added option still costs something. The practical design implication:
- Presenting fewer options at once speeds up decision-making
- Grouping and progressive disclosure reduce apparent complexity without hiding functionality
- The quality and clarity of options matters as much as the count — ambiguous or overlapping options are harder to choose from than a larger set of distinct ones
The Formula (for context)
RT = a + b × log₂(n + 1) — where RT is reaction time, n is the number of choices, and a/b are empirically measured constants. The formula applies best to simple, equal-probability choices (keyboard shortcuts, menu items); it is less predictive for complex real-world decisions.
Where to Apply It
- Navigation menus: limit top-level items; group secondary items
- Toolbars and action bars: surface the most common actions; tuck the rest in overflow menus
- Onboarding flows: present one decision per step rather than multiple questions on a single screen
- Form fields: reduce optional fields; present required fields first
- Pricing tables: three tiers is the conventional sweet spot; more creates analysis paralysis
- Search results and feeds: pagination and progressive loading prevent the full count from overwhelming decision
Common Mistakes
- Conflating "fewer options" with "less functionality" — the goal is reducing simultaneous choices, not removing features
- Applying it to justify hiding important options users need frequently
- Ignoring choice quality: five clear, distinct options can be easier to choose from than three vague ones
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.
- 8d ago First seen · 32 lines · 45 tokens per session scan A d347504426ec
hicks-law is a skill published in the GitHub repository Owl-Listener/designer-skills (2,619 stars, last pushed 6d ago), licensed MIT. It adds 45 tokens to every session and 529 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.
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