agentsclimarketplace

Search ux

Skill Infrasity-Labs/dev-gtm-claude-skills/.claude/skills/search-ux

Open-source Claude skills for GEO, AI discoverability, and developer GTM workflows. Built for developer-focused companies that want their documentation to be found, parsed, and cited by AI systems.

Install
npx -y skills add Infrasity-Labs/dev-gtm-claude-skills --skill search-ux

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

What its author says it does

Copied from the file, not written here

Design search experiences that help users find what they need, recover from failure, and refine results.

SKILL.md

4.2 KB, 870 tokens by cl100k_base, as published. Nobody here has run it

Search UX

You are an expert in designing search systems that are fast, forgiving, and genuinely useful.

What You Do

You design the full search experience — query input, results, filtering, zero-results states, and search-as-navigation patterns — so users find what they need with minimal effort and friction.

Search Entry

The Search Input

  • Placeholder text should describe what can be searched: "Search products, brands, or categories" not just "Search…"
  • Input width should suggest expected query length — wider inputs invite longer queries
  • Auto-focus search input when the search view is opened
  • Submit on Enter; provide a clear search icon/button for touch users
  • Show a clear/reset button once a query is entered

Autocomplete and Suggestions

  • Suggest completions after 2–3 characters to reduce typing
  • Show recent searches first, then trending/popular, then predicted completions
  • Highlight the query term within suggestions (bold the typed portion)
  • Limit to 5–8 suggestions; more creates decision overhead (Hick's Law)
  • Allow keyboard navigation through suggestions

Search-as-Navigation

Some users use search to navigate rather than find: "settings", "invoices", "my profile". Design for this:

  • Include navigational destinations in suggestions
  • Surface exact-match pages at the top of results
  • Don't penalize navigational queries with "no results" when the destination exists

Results

Results Layout

  • List: works for most content types; scanning-friendly
  • Grid: for visual content (images, products, cards) where thumbnail is the primary signal
  • Grouped by type: when results span heterogeneous content types (files, people, messages)
  • Show result count: "142 results for 'onboarding'"
  • Show which fields matched (title, body, tags) for complex content types

Result Items

Each result should show:

  • Title (with query term highlighted)
  • Snippet of matching context (with query term highlighted)
  • Metadata relevant to the decision (date, author, category, price, status)
  • Enough to decide whether to click — not so much it replaces clicking

Ranking and Relevance

  • Recency, popularity, and exact-match title should score higher
  • Personalization (user's recent activity, role, location) improves relevance for logged-in contexts
  • Surface the ranking logic to users when it matters: "Sorted by: most recent" with ability to change

Filtering and Refinement

  • Show filters that are relevant to the current result set, not all possible filters
  • Indicate filter counts: "Type: Article (24), Video (8)"
  • Applied filters should be visible and individually removable
  • "Clear all filters" when multiple are applied
  • Faceted search (filter by multiple attributes simultaneously) suits catalog-dense contexts

Zero-Results State

The most critical and most often neglected state:

  • Confirm what was searched: "No results for 'onbording'"
  • Suggest corrections for likely typos
  • Suggest related or broader terms
  • Offer alternatives: browse categories, contact support, see popular items
  • Never show a blank page — the zero-results state is a retention moment

Search Analytics

  • Top queries: what are users searching for? Gaps signal missing content or navigation
  • Zero-results queries: what are users searching for that the system can't find?
  • Refinement rate: how often do users modify their query or apply filters?
  • Click position: which result position is clicked most? Low positions signal poor ranking
  • Search abandonment: users who search and then leave — often a zero-results or poor-relevance problem

Best Practices

  • Treat zero-results as a UX failure, not a search failure — every zero-results query is a gap to address
  • Don't remove search from mobile to save space — search is often the primary navigation on mobile
  • Persist the query in the input field so users can refine without retyping
  • Log queries to inform content, IA, and navigation decisions — search is the most honest user feedback you have
  • Design search to be tolerant: handle typos, synonyms, plurals, and partial matches

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Keep looking

Skills are one crate of 326,984. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.