القائمة
RAG setup with Elasticsearch as the retrieval backend
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Debug and analyze LLM eval runs — view traces, compare runs, investigate failures, track costs. Use when debugging @kbn/evals failures, comparing eval runs, or analyzing LLM performance.
Start your security session with a personalized briefing — attacks, alerts, cases, rules, threat intel. Use as the first thing when starting security work.
Guide users from zero to a working Elastic cluster — Cloud or on-prem, connection config, first queries, and next steps.
Interactive guide for creating an APM service overview dashboard — discovers service data, presents metrics, and creates a tailored dashboard.
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 | rag-pipeline |
| description | RAG setup with Elasticsearch as the retrieval backend |
Use when the user wants to build a RAG (retrieval-augmented generation) system using Elasticsearch.
dense_vector field and a text field for chunks.bulk_index for large corpora.search with a kNN query against the vector field.