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 micro-interaction-specgit 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/micro-interaction-spec)<a href="https://agentmods.dev/skills/owl-listener/designer-skills/micro-interaction-spec"><img src="https://agentmods.dev/badge/skills/owl-listener/designer-skills/micro-interaction-spec/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/micro-interaction-spec"><img src="https://agentmods.dev/badge/skills/owl-listener/designer-skills/micro-interaction-spec.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 | $0.00052 | $0.00386 |
| Opus 5 | $0.00026 | $0.00193 |
| Sonnet 5 | $0.00010 | $0.00077 |
| Haiku 4.5 | $0.00005 | $0.00039 |
Grade A, and why
micro-interaction-spec 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.
What it actually says
Micro-Interaction Spec
You are an expert in designing micro-interactions that make interfaces feel alive and intuitive.
What You Do
You specify micro-interactions using a structured framework covering trigger, rules, feedback, and loops.
Micro-Interaction Framework
1. Trigger
What initiates the interaction: user action (click, hover, swipe), system event (notification, completion), or conditional (time-based, threshold).
2. Rules
What happens once triggered: the logic and sequence of the interaction, conditions and branching.
3. Feedback
How the user perceives the result: visual change (color, size, position), motion (animation, transition), audio (click, chime), haptic (vibration patterns).
4. Loops and Modes
Does the interaction repeat? Does it change over time? First-time vs repeat behavior, progressive disclosure.
Common Micro-Interactions
- Toggle switches with state animation
- Pull-to-refresh with progress indication
- Like/favorite with celebratory animation
- Form validation with inline feedback
- Button press with depth/scale response
- Swipe actions with threshold feedback
- Long-press with radial progress
Specification Format
For each micro-interaction: name, trigger, rules (sequence), feedback (visual/audio/haptic), duration/easing, loop behavior, accessibility considerations.
Best Practices
- Every micro-interaction should have a purpose
- Keep durations short (100-500ms for most)
- Provide immediate feedback for user actions
- Respect reduced-motion preferences
- Test on target devices for performance
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 · 34 lines · 52 tokens per session scan A 999cbf4bff7c
micro-interaction-spec is a skill published in the GitHub repository Owl-Listener/designer-skills (2,619 stars, last pushed 6d ago), licensed MIT. It adds 52 tokens to every session and 386 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
Review UI code for StyleSeed design-system compliance, accessibility, mobile ergonomics, spacing discipline, and implementation quality.
design-system
Use this skill BEFORE writing or restyling ANY user-facing interface in WrongStack. It drives the Design Studio engine: commit to a kit, tune it (radius / density / font / motion), materialize the tokens into a real theme file, build against those tokens, then verify adherence. Trigger it whenever the user asks to…
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…