Build search experiences that help users find what they need quickly, even when they are uncertain about what they are looking for. The goal is not perfect relevance on the first try; it is guiding users from intent to outcome through forgiving search and clear results.

Consult the search and filtering UX reference for autocomplete patterns, filter architecture, result presentation, and zero-results recovery. Consult the search and findability reference for site search, autosuggest, command palettes, and intent-aware findability. Consult the collection browsing and filtering reference for long result lists, faceted browsing, and filter overlays. Consult the predictive and intent-driven UI reference for recommendations, smart defaults, and resume flows.

MANDATORY PREPARATION

Read frontend-design and follow its Context Gathering Protocol. Reuse available context and ask only about consequential gaps. Additionally gather: what users typically search for, what common queries fail, and how large the searchable dataset is.

Assess Search Needs

Understand the search context before designing the interface:

Search intent: Are users looking for a specific item (known-item search), exploring a category (exploratory), or trying to complete a task (transactional)?
Dataset size: Small datasets (< 100 items) may not need search; filtering or categorization may suffice. Large datasets need faceted search and ranking.
Query patterns: What do users actually type? Common misspellings, synonyms, and abbreviations should be handled.
Failure modes: What happens when search returns nothing? When it returns too much?