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prettier updates
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src/platform/packages/shared/kbn-search-agent/src/agents/elasticsearch_onboarding.ts

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export const elasticsearchOnboardingAgent = {
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id: 'elasticsearch-onboarding',
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name: 'Elasticsearch Onboarding',
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description: 'Help developers new to Elasticsearch get from zero to a working search experience. Guide them through understanding their intent, mapping their data, and building a search experience with best practices baked in. Use this when developers are new to Elasticsearch and need help getting started with their search use case.',
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labels: ["search","onboarding","getting started"],
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description:
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'Help developers new to Elasticsearch get from zero to a working search experience. Guide them through understanding their intent, mapping their data, and building a search experience with best practices baked in. Use this when developers are new to Elasticsearch and need help getting started with their search use case.',
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labels: ['search', 'onboarding', 'getting started'],
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avatar_icon: 'logoElasticsearch',
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configuration: {
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instructions: `# Elastic Developer Guide

src/platform/packages/shared/kbn-search-agent/src/skills/catalog_ecommerce.ts

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export const catalogEcommerceSkill = {
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id: 'catalog-ecommerce',
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name: 'catalog-ecommerce',
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description: 'Guide for building catalog and e-commerce search with Elasticsearch. Use when a developer wants product search, faceted navigation, autocomplete, "did you mean" suggestions, or shopping-oriented search experiences.',
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description:
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'Guide for building catalog and e-commerce search with Elasticsearch. Use when a developer wants product search, faceted navigation, autocomplete, "did you mean" suggestions, or shopping-oriented search experiences.',
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content: `# Catalog / E-Commerce Search Guide
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Guide developers through building product catalog and e-commerce search with Elasticsearch. Use this guide when they need product search with filtering, faceting, autocomplete, boosting by attributes, and shopping-oriented relevance.

src/platform/packages/shared/kbn-search-agent/src/skills/index.ts

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import { vectorHybridSearchSkill } from './vector_hybrid_search';
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export { catalogEcommerceSkill, keywordSearchSkill, ragChatbotSkill, vectorHybridSearchSkill };
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export const skills = [catalogEcommerceSkill, keywordSearchSkill, ragChatbotSkill, vectorHybridSearchSkill];
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export const skills = [
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catalogEcommerceSkill,
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keywordSearchSkill,
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ragChatbotSkill,
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vectorHybridSearchSkill,
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];

src/platform/packages/shared/kbn-search-agent/src/skills/keyword_search.ts

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export const keywordSearchSkill = {
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id: 'keyword-search',
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name: 'keyword-search',
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description: 'Guide for building keyword/full-text search with Elasticsearch. Use when a developer wants text matching, filters, faceted search, autocomplete, or traditional search functionality.',
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description:
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'Guide for building keyword/full-text search with Elasticsearch. Use when a developer wants text matching, filters, faceted search, autocomplete, or traditional search functionality.',
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content: `# Keyword Search Guide
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Guide developers through building full-text keyword search with Elasticsearch. Use this guide when they need text matching, filters, faceting, autocomplete, or traditional search-bar behavior.

src/platform/packages/shared/kbn-search-agent/src/skills/rag_chatbot.ts

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export const ragChatbotSkill = {
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id: 'rag-chatbot',
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name: 'rag-chatbot',
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description: 'Guide for building RAG (retrieval-augmented generation) chatbots and Q&A systems with Elasticsearch. Use when a developer wants to build a chatbot, Q&A system, or AI assistant that answers questions from their own data.',
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description:
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'Guide for building RAG (retrieval-augmented generation) chatbots and Q&A systems with Elasticsearch. Use when a developer wants to build a chatbot, Q&A system, or AI assistant that answers questions from their own data.',
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content: `# RAG / Chatbot Guide
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Guide developers through building retrieval-augmented generation (RAG) systems with Elasticsearch as the retrieval backend. Use this guide when they want a chatbot, Q&A interface, or AI assistant that answers from their own documents.

src/platform/packages/shared/kbn-search-agent/src/skills/vector_hybrid_search.ts

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export const vectorHybridSearchSkill = {
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id: 'vector-hybrid-search',
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name: 'vector-hybrid-search',
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description: 'Guide for building vector search, hybrid search, and using Elasticsearch as a vector database. Covers semantic_text, dense_vector, embedding strategies, hybrid BM25+kNN via RRF, reranking, and production optimization. Use when a developer wants semantic search, hybrid search, kNN, embeddings, or Elasticsearch as a vector store.',
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description:
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'Guide for building vector search, hybrid search, and using Elasticsearch as a vector database. Covers semantic_text, dense_vector, embedding strategies, hybrid BM25+kNN via RRF, reranking, and production optimization. Use when a developer wants semantic search, hybrid search, kNN, embeddings, or Elasticsearch as a vector store.',
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content: `# Vector & Hybrid Search Guide
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Covers the full lifecycle of vector or hybrid search with Elasticsearch — planning, data modeling, search implementation, and optimization. All API examples use SENSE syntax for Kibana Dev Tools.

x-pack/platform/packages/shared/agent-builder/agent-builder-server/allow_lists.ts

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// Search
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`${internalNamespaces.search}.keyword-search`,
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`${internalNamespaces.search}.catalog-ecommerce`,
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`${internalNamespaces.search}.vector-database`,
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`${internalNamespaces.search}.semantic-search`,
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`${internalNamespaces.search}.hybrid-search`,
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`${internalNamespaces.search}.vector-hybrid-search`,
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`${internalNamespaces.search}.rag-chatbot`,
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] as const;
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