exa-core-workflow-a

name	exa-core-workflow-a
description	Execute Exa neural search with contents, date filters, and domain scoping. Use when building search features, implementing RAG context retrieval, or querying the web with semantic understanding. Trigger with phrases like "exa search", "exa neural search", "search with exa", "exa searchAndContents", "exa query".
allowed-tools	Read, Write, Edit, Bash(npm:*), Bash(node:*), Grep
version	1.11.0
license	MIT
author	Jeremy Longshore <[e-mail]>
tags	["saas","exa","workflow","neural-search","search"]
compatibility	Designed for Claude Code

Exa Core Workflow A — Neural Search

Overview

Primary workflow for Exa: semantic web search using search() and searchAndContents(). Exa's neural search understands query meaning rather than matching keywords, making it ideal for research, RAG pipelines, and content discovery. This skill covers search types, content extraction, filtering, and categories.

Prerequisites

• exa-js installed and EXA_API_KEY configured
• Understanding of neural vs keyword search tradeoffs

Search Types

Type	Latency	Best For
auto (default)	300-1500ms	General queries; Exa picks best approach
neural	500-2000ms	Conceptual/semantic queries
keyword	200-500ms	Exact terms, names, URLs
fast	p50 < 425ms	Speed-critical applications
instant	< 150ms	Real-time autocomplete
deep	2-5s	Maximum quality, light deep search
deep-reasoning	5-15s	Complex research questions

Instructions

Step 1: Basic Neural Search

import Exa from "exa-js";

const exa = new Exa(process.env.EXA_API_KEY);

// Neural search: phrase your query as a statement, not a question
const results = await exa.search(
  "comprehensive guide to building production RAG systems",
  {
    type: "neural",
    : ,   
  }
);

 ( r  results.) {
  .();
  .();
}