keyword-search

Implement keyword search and autocomplete with Elasticsearch index mappings and query patterns.

Updated Feb 24, 2026

Search Tags:#search #autocomplete #query #elasticsearch #mapping #facets #keyword

Ready to run

npx skills add https://github.com/kevinsweet/elastic-ide-context --skill keyword-search

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: keyword-search
Source: https://github.com/kevinsweet/elastic-ide-context/tree/main/.cursor/skills/recipes/keyword-search
Command: npx skills add https://github.com/kevinsweet/elastic-ide-context --skill keyword-search

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Guides developers to implement robust keyword and full-text search with Elasticsearch, enabling fast text matching, filtering, and autocomplete across structured data.

Core Features & Use Cases

Index mapping with text fields and keyword sub-fields to support full-text search and exact filtering.
Autocomplete via completion fields to provide instant suggestions during typing.
Ingestion and query patterns guidance for common data types (products, articles, documents).
Use Case: Build a search experience with facets, synonyms, and typo-tolerant matching.

Quick Start

Create a new index with text and keyword fields, then implement a basic search endpoint.

Frequently Asked Questions about keyword-search

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I build autocomplete and keyword search with Elasticsearch for structured data?▼

To build Elasticsearch keyword search and autocomplete, you define index mappings with text fields, keyword sub-fields, and completion fields to support full-text matching, exact filtering, and instant typing suggestions across structured catalogs.

How do I configure Elasticsearch index mappings for text matching and exact filtering?▼

Configuring Elasticsearch index mappings requires setting up text fields for full-text search alongside keyword sub-fields for exact filtering, plus completion fields to deliver autocomplete suggestions for structured product or article data.

What is the best way to implement typo-tolerant search and facets in Elasticsearch?▼

The best way to implement typo-tolerant search and facets in Elasticsearch is by applying specific query patterns and ingestion guidance that support synonym matching, structured filtering, and relevance tuning to refine product catalog results.

Does Elasticsearch autocomplete work for product catalogs and article documents?▼

Yes, Elasticsearch autocomplete works for product catalogs and article documents by utilizing completion fields within your index mapping to provide instant query suggestions during user typing sessions.

Why are my Elasticsearch keyword search results returning irrelevant matches?▼

Irrelevant Elasticsearch keyword search results often stem from common ingestion pitfalls or unmapped text and keyword sub-fields, requiring relevance tuning and proper query pattern adjustments to improve text matching accuracy.

When do I need Elasticsearch keyword sub-fields for my search queries?▼

You need Elasticsearch keyword sub-fields when your search queries require exact filtering, structured data aggregation, or facets alongside standard full-text text matching for products, articles, or documents.