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patrykkopycinski
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search-app-setup

Provision Elasticsearch indices, mappings, analyzers, synonyms, and validate queries.

6|Updated Feb 20, 2026
Search Tags:#indexing#integration#validation#search#elasticsearch#synonyms#search-ui
One-click install
npx skills add https://github.com/patrykkopycinski/elastic-cursor-plugin --skill search-app-setup
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: search-app-setup
Source: https://github.com/patrykkopycinski/elastic-cursor-plugin/tree/main/.cursor/skills/search-app-setup
Command: npx skills add https://github.com/patrykkopycinski/elastic-cursor-plugin --skill search-app-setup

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill guides developers through provisioning, configuring, and validating an Elastic-powered search application to remove friction when creating indices, managing synonyms, and integrating search into a UI or Kibana.

Core Features & Use Cases

  • Index creation & mappings: Use create_index to define indices, mappings, and analyzers for relevance control.
  • Search application integration: Provision a search application or integrate programmatic search into a custom front-end or Kibana Discover.
  • Synonyms and relevance tuning: Manage synonyms and adjust analyzers to improve query matching.
  • Indexing and validation: Index sample data with index_document or bulk_index and verify behavior with search and test_search.
  • Use Case: Quickly scaffold a product catalog search with synonyms, tuned relevance, and a simple search UI for demonstration or production testing.

Quick Start

Ask the AI to create an Elastic search application by provisioning a new index with mappings, loading sample data, enabling synonyms, running basic searches for validation, and scaffolding a simple search UI.

Frequently Asked Questions about search-app-setup

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

FAQPage Schema
How do I build an Elasticsearch app with a search UI and sample data?▼

Building an Elasticsearch search app involves creating indices with custom mappings and analyzers, indexing sample data, and validating query relevance using search and test_search tools before integrating a search UI.

How do I configure synonyms and analyzers in Elasticsearch for relevance tuning?▼

Configuring synonyms and analyzers in Elasticsearch requires defining them within your index mappings during index creation to control query matching and improve overall search relevance for your application.

What is the best way to validate Elasticsearch queries before integrating a custom front-end?▼

The best way to validate Elasticsearch queries is to index sample documents and run test searches using dedicated search and test_search tools to verify relevance and matching behavior prior to UI integration.

Does this workflow support integrating Elasticsearch with Kibana Discover?▼

Yes, this workflow supports integrating Elasticsearch with Kibana Discover, allowing you to provision a search application or integrate programmatic search directly into custom front-ends or Kibana.

How do I create an Elasticsearch index with custom mappings for a product catalog?▼

Creating an Elasticsearch index for a product catalog requires using index creation tools to define custom mappings and analyzers, which establishes relevance control before you index sample documents.

Why are my Elasticsearch synonym configurations not matching queries correctly?▼

Elasticsearch synonym configurations may fail to match queries if analyzers are not properly mapped during initial index creation, requiring you to validate behavior by running test searches against indexed sample data.

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