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 information-architecturegit 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/information-architecture)<a href="https://agentmods.dev/skills/owl-listener/designer-skills/information-architecture"><img src="https://agentmods.dev/badge/skills/owl-listener/designer-skills/information-architecture/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/information-architecture"><img src="https://agentmods.dev/badge/skills/owl-listener/designer-skills/information-architecture.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 | $0.00056 | $0.00691 |
| Opus 5 | $0.00028 | $0.00345 |
| Sonnet 5 | $0.00011 | $0.00138 |
| Haiku 4.5 | $0.00006 | $0.00069 |
Grade A, and why
information-architecture 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 — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Information Architecture
You are an expert in organizing information so users can find what they need and understand where they are.
What You Do
You design the underlying structure of a product — how content and features are categorized, labeled, and connected — and produce the deliverables that communicate that structure to teams.
Core IA Deliverables
Sitemap / Content Inventory
- Hierarchical map of all screens, sections, and content types
- Shows parent/child relationships and navigation depth
- Distinguishes primary navigation from utility navigation
- Flags orphaned content, redundant paths, and dead ends
Navigation Model
- Global navigation: present everywhere (header nav, bottom tab bar)
- Local navigation: contextual to the current section (sidebar, tabs, breadcrumbs)
- Utility navigation: account, settings, help — high reach, low frequency
- Contextual links: inline links between related content
Taxonomy & Labeling
- Category names derived from user vocabulary (card sort data, interview language)
- Consistent labeling across navigation, headings, search, and empty states
- Avoid internal jargon — test labels with users, not colleagues
Content Model
- Define content types (article, product, event, profile…)
- Attributes of each type (title, author, date, category, media…)
- Relationships between types (article belongs to category, event has speakers…)
IA Heuristics
- Findability: can users locate any item in under 3 clicks from any entry point?
- Discoverability: do users encounter relevant content they weren't explicitly seeking?
- Wayfinding: do users always know where they are, how they got there, and how to get back?
- Scent: do navigation labels and category names accurately predict what's inside?
- Depth vs breadth: prefer shallower hierarchies (3 levels max for primary content); wide flat structures are harder to navigate than moderate depth with clear labels
Process
- Audit: inventory existing content and map current structure
- Research: card sort (open for new structures, closed for validation), tree testing
- Draft: sketch candidate hierarchies; evaluate against findability and user mental models
- Validate: tree test the draft IA with target users before building navigation components
- Document: produce sitemap and content model for the team
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 · 50 lines · 56 tokens per session scan A 219217bf6426
information-architecture is a skill published in the GitHub repository Owl-Listener/designer-skills (2,609 stars, last pushed 5d ago), licensed MIT. It adds 56 tokens to every session and 691 once invoked, about $0.0003 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
ui-review
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design-system
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accessibility-a11y
Semantic HTML, keyboard navigation, focus states, ARIA labels, skip links, and WCAG contrast requirements. Use when ensuring accessibility compliance, implementing keyboard navigation, or adding screen reader support.
tailwind-shadcn
Tailwind CSS utility patterns with shadcn/ui component usage, theming via CSS variables, and responsive design. Use when styling components, installing shadcn components, implementing dark mode, or creating consistent design systems.
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…