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Complete flow from index creation to working vector search with Elasticsearch
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
Basado en la clasificación ocupacional SOC
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Guide users from zero to a working Elastic cluster — Cloud or on-prem, connection config, first queries, and next steps.
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Interactive guide for creating SLOs from discovered APM and metric data — identifies candidates, lets user configure targets, and creates SLOs.
Create, configure, and manage Elasticsearch indices — mappings, settings, templates, data streams, and lifecycle policies.
| name | vector-search-setup |
| description | Complete flow from index creation to working vector search with Elasticsearch |
Use this skill when the user wants to add vector/semantic search to their application.
create_index with a mapping that includes a dense_vector field (dimensions match your model, e.g. 384 or 768).create_inference_endpoint for an embedding model (e.g. ELSER or a third-party endpoint).create_ingest_pipeline with an inference processor to embed text at index time if needed.index_document or bulk_index; ensure the vector field is populated (from app or pipeline).search tool with a knn query (or hybrid with a keyword query) to run vector search.search with a kNN query and confirm hits and scores.