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Guides agents through implementing production-ready search (Elasticsearch or Algolia): index design, sync pipelines, search APIs, autocomplete, and relevance tu
This skill equips AI agents to add production-quality search to applications. It provides concrete, prescriptive guidance for index design (Elasticsearch and Algolia), building database-to-index synchronization pipelines, constructing search APIs with faceting and highlights, implementing autocomplete/typeahead, and iteratively tuning relevance using real query logs. The instructions include example analyzers, query shapes, aggregation patterns, and operational practices (full re-index, incremental sync, deletion handling, and error recovery).
Use this skill when a user asks to add or improve search functionality: "add search to my app", "set up Elasticsearch", "configure Algolia", "fix search relevance", "add autocomplete", or "implement faceted filtering". It's appropriate for e-commerce product search, documentation or blog search, and any app that needs scalable full-text search and relevance tuning.
Designed to be used by general-purpose agent harnesses (Claude Code, Codex, Cursor, or similar) that can read and act on CLI/HTTP instructions. The guidance is language-agnostic with Node.js/Python examples noted in metadata.
Documentation-only skill guiding agents through setting up Elasticsearch or Algolia search. Covers index design, sync pipelines, search API construction, autocomplete, and relevance tuning with concrete JSON/JS examples. No bundled scripts to execute. Well-structured and practical for a common developer task.
Clean skill with no security concerns. Pure documentation with good code examples. Would benefit from runnable scripts or references/ for templates.
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