Exa hello world
Skill jeremylongshore/claude-code-plugins-plus-skills/plugins/saas-packs/exa-pack/skills/exa-hello-world
'Create a minimal working Exa search example with real results.From its SKILL.md
npx -y skills add jeremylongshore/claude-code-plugins-plus-skills --skill exa-hello-worldAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
What its file declares
Copied from the file, not written here
The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
5.0 KB, ~1.1k tokens by cl100k_base, as published. Nobody here has run it
Exa Hello World
Overview
Minimal working examples demonstrating all core Exa search operations: basic search, search with contents, find similar, and get contents. Each example is runnable standalone.
Prerequisites
exa-jsSDK installed (npm install exa-js)EXA_API_KEYenvironment variable set- Node.js 18+ with ES module support
Instructions
Step 1: Basic Search (Metadata Only)
import Exa from "exa-js";
const exa = new Exa(process.env.EXA_API_KEY);
// Basic search returns URLs, titles, and scores — no page content
const results = await exa.search("best practices for building RAG pipelines", {
type: "auto", // auto | neural | keyword | fast | instant
numResults: 5,
});
for (const r of results.results) {
console.log(`[${r.score.toFixed(2)}] ${r.title}`);
console.log(` ${r.url}`);
}
Step 2: Search with Contents
// searchAndContents returns text, highlights, and/or summary with each result
const results = await exa.searchAndContents(
"how transformers work in large language models",
{
type: "neural",
numResults: 3,
text: { maxCharacters: 1000 },
highlights: { maxCharacters: 500, query: "attention mechanism" },
summary: { query: "explain transformers simply" },
}
);
for (const r of results.results) {
console.log(`## ${r.title}`);
console.log(`URL: ${r.url}`);
console.log(`Summary: ${r.summary}`);
console.log(`Text preview: ${r.text?.substring(0, 200)}...`);
console.log(`Highlights: ${r.highlights?.join(" | ")}`);
console.log();
}
Step 3: Find Similar Pages
// findSimilar takes a URL and returns semantically similar pages
const similar = await exa.findSimilarAndContents(
"https://arxiv.org/abs/2301.00234",
{
numResults: 5,
text: { maxCharacters: 500 },
excludeSourceDomain: true,
}
);
console.log("Pages similar to the seed URL:");
for (const r of similar.results) {
console.log(` ${r.title} — ${r.url}`);
}
Step 4: Get Contents for Known URLs
// getContents retrieves page content for specific URLs
const contents = await exa.getContents(
["https://example.com/article-1", "https://example.com/article-2"],
{
text: { maxCharacters: 2000 },
highlights: { maxCharacters: 500 },
livecrawl: "preferred",
livecrawlTimeout: 10000,
}
);
for (const r of contents.results) {
console.log(`${r.title}: ${r.text?.length} chars retrieved`);
}
Output
- Working TypeScript file with Exa client initialization
- Search results printed to console with titles, URLs, and scores
- Content extraction (text, highlights, summary) demonstrated
- Similarity search results from a seed URL
Error Handling
| Error | HTTP Code | Cause | Solution |
|---|---|---|---|
INVALID_API_KEY | 401 | API key missing or invalid | Check EXA_API_KEY env var |
INVALID_REQUEST_BODY | 400 | Malformed parameters | Verify parameter types match SDK docs |
NO_MORE_CREDITS | 402 | Account credits depleted | Top up at dashboard.exa.ai |
429 Too Many Requests | 429 | Rate limit exceeded | Wait and retry; default is 10 QPS |
Empty results array | 200 | Query too narrow or filters too strict | Broaden query or relax date/domain filters |
Examples
Complete Runnable Script
import Exa from "exa-js";
const exa = new Exa(process.env.EXA_API_KEY);
async function main() {
// 1. Search
const search = await exa.search("AI safety research", { numResults: 3 });
console.log(`Found ${search.results.length} results\n`);
// 2. Search with contents
const detailed = await exa.searchAndContents("AI safety research", {
numResults: 2,
text: true,
highlights: { maxCharacters: 300 },
});
console.log("First result text length:", detailed.results[0]?.text?.length);
// 3. Find similar
if (search.results[0]) {
const similar = await exa.findSimilar(search.results[0].url, {
numResults: 3,
});
console.log("\nSimilar pages:", similar.results.map(r => r.title));
}
}
main().catch(console.error);
Resources
Next Steps
Proceed to exa-core-workflow-a for neural search patterns or exa-sdk-patterns for production-ready code.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.