smithery/jeremylongshore

exa-performance-tuning

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". '

Installation

$ npx skills add smithery/jeremylongshore --skill exa-performance-tuning

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More details

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Skill metadata

Parsed from SKILL.md frontmatter.

Version1.11.0
LicenseMIT
CompatibilityDesigned for Claude Code
Allowed toolsRead, Write, Edit
Declared agents claude-code

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 6,557 B
  • docs SUMMARY.md 356 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

Exa Performance Tuning

Prerequisites

  • A measured latency/throughput/quality/error baseline, sanitized evaluation set, SLO owner, and rollback threshold.
  • Approved data/policy controls that remain in effect during tests.

Output

  • A measured performance recommendation with policy/quality guardrails, owner, and reversible change record.

Examples

Measure sanitized staging queries, change one request option, cache behavior, or concurrency limit, and compare aggregate latency, quality, and errors against baseline. Revert on regression; do not disable citation, source, privacy, or human-review controls to improve a metric.

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 < 3000) return "neural";
  return "deep";
}

async function optimizedSearch(query: string, latencyBudgetMs: number) {
  const type = selectSearchType(latencyBudgetMs);
  const numResults = latencyBudgetMs < 500 ? 3 : latencyBudgetMs < 2000 ? 5 : 10;

  return exa.search(query, { type, numResults });
}

Step 2: Minimize Content Retrieval

// Each content option adds latency. Only request what you need.

// Fastest: metadata only (no content retrieval)
const metadataOnly = await exa.search("query", { numResults: 5 });

// Medium: highlights only (much smaller than full text)
const highlightsOnly = await exa.searchAndContents("query", {
  numResults: 5,
  highlights: { maxCharacters: 300 },
  // No text or summary — saves content retrieval time
});

// Slower: full text (use maxCharacters to limit)
const withText = await exa.searchAndContents("query", {
  numResults: 3,  // fewer results = faster
  text: { maxCharacters: 1000 },  // limit content size
});

Step 3: Cache Search Results

import { LRUCache } from "lru-cache";

const searchCache = new LRUCache<string, any>({
  max: 5000,
  ttl: 2 * 3600 * 1000, // 2-hour TTL
});

async function cachedSearch(query: string, opts: any) {
  const key = `${query}:${opts.type || "auto"}:${opts.numResults || 10}`;
  const cached = searchCache.get(key);
  if (cached) return cached; // Cache hit: 0ms vs 500-2000ms

  const results = await exa.search(query, opts);
  searchCache.set(key, results);
  return results;
}

Step 4: Parallelize Independent Searches

// Run independent queries concurrently instead of sequentially
async function parallelSearch(queries: string[]) {
  const searches = queries.map(q =>
    cachedSearch(q, { type: "auto", numResults: 3 })
  );
  return Promise.all(searches);
  // 3 parallel searches: ~600ms total (limited by slowest)
  // 3 sequential searches: ~1800ms total
}

Step 5: Two-Phase Search Pattern

// Phase 1: Fast search for URLs only
// Phase 2: Selective content retrieval for top results only
async function twoPhaseSearch(query: string) {
  // Phase 1: metadata only (fast)
  const results = await exa.search(query, { type: "auto", numResults: 10 });

  // Phase 2: get content only for top 3 results
  const topUrls = results.results.slice(0, 3).map(r => r.url);
  const contents = await exa.getContents(topUrls, {
    text: { maxCharacters: 2000 },
    highlights: { maxCharacters: 500, query },
  });

  return contents;
  // Saves content retrieval time for 7 results you won't use
}

Step 6: Query Normalization for Cache Hits

function normalizeQuery(query: string): string {
  return query
    .toLowerCase()
    .trim()
    .replace(/\s+/g, " ")       // collapse whitespace
    .replace(/[?.!,;:]+$/, ""); // strip trailing punctuation
}

async function normalizedSearch(query: string, opts: any) {
  return cachedSearch(normalizeQuery(query), opts);
}
// Increases cache hit rate by 20-40% for user-generated queries

Performance Comparison

Strategy Latency Savings Implementation
instant type 5-10x faster than neural One-line change
Reduce numResults (10 -> 3) ~200-500ms saved One-line change
Highlights instead of text ~100-300ms saved Replace text with highlights
LRU cache 100% for cache hits ~20 lines
Parallel queries 2-3x throughput Promise.all wrapper
Two-phase search ~30-50% for large result sets ~15 lines

Error Handling

Issue Cause Solution
Search taking 3s+ Neural search on complex query Switch to fast or auto type
Timeout on content Large pages, slow sources Set maxCharacters limit
Cache miss rate high Unique queries each time Normalize queries before caching
Rate limit (429) Too many concurrent searches Add request queue with concurrency limit

Resources

Next Steps

For cost optimization, see exa-cost-tuning. For reliability, see exa-reliability-patterns.