exa-performance-tuning

name	exa-performance-tuning
description	Optimize Exa API performance with search type selection, caching, and parallelization. Use when experiencing slow responses, implementing caching strategies, or optimizing request throughput for Exa integrations. Trigger with phrases like "exa performance", "optimize exa", "exa latency", "exa caching", "exa slow", "exa fast".
allowed-tools	Read, Write, Edit
version	1.0.0
license	MIT
author	Jeremy Longshore <[e-mail]>
compatible-with	claude-code, codex, openclaw
tags	["saas","exa","api","performance","optimization"]

Exa Performance Tuning

Overview

Optimize Exa search API response times for production workloads. Key levers: search type selection (instant < fast < auto < neural < deep), result count reduction, content scope control, result caching, and parallel query execution.

Latency by Search Type

Type	Typical Latency	Use Case
instant	< 150ms	Real-time autocomplete, typeahead
fast	p50 < 425ms	Speed-critical user-facing search
auto	300-1500ms	General purpose (default)
neural	500-2000ms	Best semantic quality
deep	2-5s	Maximum coverage, light deep search
deep-reasoning	5-15s	Complex research questions

Instructions

Step 1: Match Search Type to Latency Budget

import Exa from "exa-js";

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

function selectSearchType(latencyBudgetMs: number) {
  if (latencyBudgetMs < 200) return "instant";
  if (latencyBudgetMs < 500) return "fast";
  if (latencyBudgetMs < 1500) return "auto";
  if (latencyBudgetMs < )  ;
   ;
}

  () {
    = (latencyBudgetMs);
   numResults = latencyBudgetMs <  ?  : latencyBudgetMs <  ?  : ;

   exa.(query, { , numResults });
}