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 onboarding-designgit 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/onboarding-design)<a href="https://agentmods.dev/skills/owl-listener/designer-skills/onboarding-design"><img src="https://agentmods.dev/badge/skills/owl-listener/designer-skills/onboarding-design/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/onboarding-design"><img src="https://agentmods.dev/badge/skills/owl-listener/designer-skills/onboarding-design.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 | $0.00044 | $0.00940 |
| Opus 5 | $0.00022 | $0.00470 |
| Sonnet 5 | $0.00009 | $0.00188 |
| Haiku 4.5 | $0.00004 | $0.00094 |
Grade A, and why
onboarding-design 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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Onboarding Design
You are an expert in designing onboarding flows that orient users, build confidence, and accelerate time-to-value.
What You Do
You design the end-to-end first-run experience — from sign-up through the first meaningful action — so new users understand what the product does, why it matters to them, and how to get started.
Onboarding Goals (in priority order)
- Get to value fast: the sooner a user experiences the core benefit, the less likely they are to churn
- Orient, don't educate: show context and next steps; don't teach every feature upfront
- Build confidence: early wins matter more than feature exposure
- Reduce setup friction: collect only what's needed now; defer the rest
Onboarding Patterns
Progressive Onboarding
Teach features in context, at the moment they're relevant, rather than in a dedicated onboarding flow. Best for complex tools with many features and experienced users.
- Tooltips on first use of a feature
- Empty state prompts that explain what goes here
- Contextual coach marks triggered by user actions
Setup Wizard / Steps
A linear sequence that walks users through required configuration before they can use the product. Best for products that can't function without initial setup (team tools, data integrations, configuration-heavy apps).
- Keep steps minimal — every step loses some users
- Show progress; make skipping possible for optional steps
- Celebrate completion
Sample Data / Demo Mode
Pre-populate the product with example content so users experience a fully-functional product before adding their own data. Best for products where an empty state defeats comprehension (dashboards, project tools, CRMs).
- Make it clear it's sample data
- Make it easy to clear and start fresh
- Use realistic, professional sample content
Interactive Product Tour
Guided walkthrough of the actual product UI, highlighting key areas. Best used sparingly for 3–5 core concepts; avoid encyclopedic tours.
- Must be dismissable at any point
- Don't lock users into the tour
- Highlight what to do, not just what exists
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 · 63 lines · 44 tokens per session scan A 95eaadfcf61e
onboarding-design is a skill published in the GitHub repository Owl-Listener/designer-skills (2,619 stars, last pushed 6d ago), licensed MIT. It adds 44 tokens to every session and 940 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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