Individual skill
ux-search
Design or critique search experiences — search input, auto-suggest, results page, filtering/sorting, and zero-results recovery. Matches search features to how users actually seek (known-item vs. exploratory) and gates levers like rich suggestions, filter layout, and chips. Trigger when the user asks to design or review search, a search bar, autocomplete/auto-suggest, search results, filters, sorting, or a "no results" page.
ux/components/search/SKILL.md
Source commit 5007cd0241ccaa51ae2e4681f9618912dc10e239
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- No
- Repository scan complete
- No
- Skill scan complete
- Yes
- Observed behavior
- Not checked yet
- Last checked
- Nov 6, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
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Repository context
- Repository stars (not skill ratings)
- 40
- Repository last updated
- Jul 2, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- ai-skills Repository topic
- claude-skills Repository topic
- design-skills Repository topic
- figma-skill Repository topic
- pm-skills Repository topic
- ux-skill Repository topic
- design Derived category
- design-interface Derived category
Files and excerpt
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SKILL.mdcore · 10,823 bytes
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# Search Skill
## How this skill behaves (read first)
This is a **generative** skill. The default failure modes: **a box and nothing more** (an input that returns a bare list — no suggestions, no query persistence, no recovery), **dead ends** ("No results found." period), and **feature stacking** (rich suggestions + trending + recent + filters + chips everywhere, even where search is a minor utility). Search is a *journey* — formulate → suggest → results → refine — and which stages need investment depends on how users seek. This skill gates:
1. **Establish how users seek and how central search is** — that decides which stages to invest in.
2. **Apply the always-true core** — discoverable placement, working input conventions, suggestion basics, a scannable results page, no dead ends.
3. **Surface the context-dependent decisions** (rich auto-suggest, filter layout, chips, view options) with trade-offs.
Then it **hands off to `ux-heuristics-audit`, `ux-accessibility-audit`, `ux-aesthetics-audit`, and `ux-microcopy-audit`** for validation.
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