From exa-pack
Executes Exa workflows: findSimilar for pages semantically like a URL, getContents for text extraction from URLs, answer for cited AI responses.
How this skill is triggered — by the user, by Claude, or both
Slash command
/exa-pack:exa-core-workflow-bThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Secondary Exa workflow covering three endpoints beyond search: `findSimilar` (discover pages semantically related to a URL), `getContents` (retrieve text/highlights for known URLs), and `answer` (get AI-generated answers with web citations). These complement the primary search workflow in `exa-core-workflow-a`.
Secondary Exa workflow covering three endpoints beyond search: findSimilar (discover pages semantically related to a URL), getContents (retrieve text/highlights for known URLs), and answer (get AI-generated answers with web citations). These complement the primary search workflow in exa-core-workflow-a.
exa-js installed and EXA_API_KEY configuredexa-core-workflow-a search patternsimport Exa from "exa-js";
const exa = new Exa(process.env.EXA_API_KEY);
// findSimilar takes a URL (not a query string) and returns
// pages with semantically similar content
const similar = await exa.findSimilar(
"https://openai.com/research/gpt-4",
{
numResults: 10,
excludeSourceDomain: true, // exclude openai.com from results
startPublishedDate: "2024-01-01T00:00:00.000Z",
excludeDomains: ["reddit.com", "twitter.com"],
}
);
for (const r of similar.results) {
console.log(`${r.title} — ${r.url}`);
}
// findSimilarAndContents combines similarity search + content extraction
const results = await exa.findSimilarAndContents(
"https://huggingface.co/blog/llama3",
{
numResults: 5,
text: { maxCharacters: 2000 },
highlights: { maxCharacters: 500, query: "open source LLM" },
excludeSourceDomain: true,
}
);
for (const r of results.results) {
console.log(`## ${r.title}`);
console.log(`URL: ${r.url}`);
console.log(`Highlights: ${r.highlights?.join(" | ")}`);
console.log(`Text preview: ${r.text?.substring(0, 300)}...\n`);
}
// getContents retrieves page content for a list of URLs you already have
// Useful when you have URLs from a previous search or external source
const contents = await exa.getContents(
[
"https://arxiv.org/abs/2401.00001",
"https://arxiv.org/abs/2401.00002",
"https://blog.example.com/article",
],
{
text: { maxCharacters: 3000 },
highlights: { maxCharacters: 500 },
summary: { query: "key findings and methodology" },
livecrawl: "preferred", // try fresh, fall back to cache
livecrawlTimeout: 15000, // 15s timeout
// Subpage crawling: retrieve linked pages from each URL
subpages: 3, // crawl up to 3 subpages per URL
subpageTarget: "documentation", // find subpages matching this term
}
);
for (const r of contents.results) {
console.log(`${r.title}: ${r.text?.length || 0} chars`);
if (r.summary) console.log(`Summary: ${r.summary}`);
}
// answer() searches the web and returns an AI-generated answer with sources
const answer = await exa.answer(
"What are the key differences between RAG and fine-tuning for LLMs?",
{
text: true,
// The answer response includes citations linking to source results
}
);
console.log("Answer:", answer.answer);
console.log("\nSources:");
for (const r of answer.results) {
console.log(` - ${r.title}: ${r.url}`);
}
// streamAnswer returns chunks as they're generated
for await (const chunk of exa.streamAnswer(
"What is the current state of quantum computing in 2025?"
)) {
if (chunk.content) {
process.stdout.write(chunk.content);
}
if (chunk.citations) {
console.log("\n\nCitations:", JSON.stringify(chunk.citations, null, 2));
}
}
| Error | HTTP Code | Cause | Solution |
|---|---|---|---|
INVALID_URLS | 400 | Malformed URLs in getContents | Validate URLs have protocol |
CRAWL_NOT_FOUND | 404 | Content unavailable at URL | Verify URL is accessible |
CRAWL_TIMEOUT | 504 | Live crawl exceeded timeout | Increase livecrawlTimeout |
SOURCE_NOT_AVAILABLE | 403 | Paywalled or blocked content | Try without livecrawl: "always" |
UNABLE_TO_GENERATE_RESPONSE | 501 | Insufficient data for answer | Rephrase query or add context |
Empty similar.results | 200 | Seed URL not indexed | Try a more popular seed URL |
async function findCompetitors(companyUrl: string) {
// Find companies similar to a given company
const similar = await exa.findSimilarAndContents(companyUrl, {
numResults: 10,
excludeSourceDomain: true,
text: { maxCharacters: 500 },
category: "company",
});
return similar.results.map(r => ({
name: r.title,
url: r.url,
description: r.text?.substring(0, 200),
}));
}
async function enrichUrls(urls: string[]) {
// Process URLs in batches to stay within rate limits
const batchSize = 10;
const allContents = [];
for (let i = 0; i < urls.length; i += batchSize) {
const batch = urls.slice(i, i + batchSize);
const contents = await exa.getContents(batch, {
text: { maxCharacters: 1500 },
summary: { query: "main topic and key points" },
});
allContents.push(...contents.results);
}
return allContents;
}
For common errors, see exa-common-errors. For SDK patterns, see exa-sdk-patterns.
npx claudepluginhub fleet-to-force/claude-code-plugins-plus --plugin exa-pack5plugins reuse this skill
First indexed Jul 10, 2026
Execute Exa findSimilar, getContents, answer, and streaming answer workflows. Use when finding pages similar to a URL, retrieving content for known URLs, or getting AI-generated answers with citations. Trigger with phrases like "exa find similar", "exa get contents", "exa answer", "exa similarity search", "findSimilarAndContents".
Performs high-precision semantic search and content retrieval via Exa API. Supports deep research, code documentation lookup, company research, and URL content extraction with structured output.
Searches the web and retrieves code context, documentation, and full-text content via Exa's neural search API. Requires EXA_API_KEY.