From exa
Exa.ai search API integration for neural and keyword web search with content retrieval. Use when implementing web search features, integrating Exa SDK (exa_py, exa-js), or retrieving web content. Triggers on: Exa, exa_py, exa-js, neural search, web search API, search_and_contents, searchAndContents, find_similar, findSimilar, domain filtering, date filtering, text extraction, page summaries, highlights, search auto mode, fast search, search categories, livecrawl, excluding domains, include text, exclude text, EXA_API_KEY.
npx claudepluginhub ejirocodes/agent-skills --plugin exaThis skill uses the workspace's default tool permissions.
| Topic | When to Use | Reference |
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Generates original PNG/PDF visual art via design philosophy manifestos for posters, graphics, and static designs on user request.
| Topic | When to Use | Reference |
|---|---|---|
| Search Modes | Choosing between auto, neural, and keyword search | search-modes.md |
| Filters | Domain, date, text, and category filtering | filters.md |
| Contents | Text extraction, highlights, summaries, livecrawl | contents.md |
| SDK Patterns | Python (exa_py) and TypeScript (exa-js) usage | sdk-patterns.md |
from exa_py import Exa
exa = Exa(api_key="your-api-key") # or set EXA_API_KEY env var
results = exa.search_and_contents(
"latest developments in quantum computing",
type="auto",
num_results=10,
text=True,
highlights=True
)
for result in results.results:
print(f"{result.title}: {result.url}")
print(result.text[:500])
import Exa from "exa-js";
const exa = new Exa(process.env.EXA_API_KEY);
const results = await exa.searchAndContents(
"latest developments in quantum computing",
{
type: "auto",
numResults: 10,
text: true,
highlights: true,
}
);
results.results.forEach((result) => {
console.log(`${result.title}: ${result.url}`);
});
results = exa.search_and_contents(
"AI startup funding rounds",
type="neural",
num_results=10,
include_domains=["techcrunch.com", "venturebeat.com"],
start_published_date="2024-01-01",
text={"max_characters": 2000},
summary=True
)
similar = exa.find_similar_and_contents(
"https://example.com/interesting-article",
num_results=10,
exclude_source_domain=True,
text=True
)
| Mode | When to Use | Notes |
|---|---|---|
auto | Default for most queries | Exa optimizes between neural/keyword automatically |
neural | Natural language, conceptual queries | Best for "what is...", "how to...", topic exploration |
keyword | Exact matches, technical terms, names | Best for specific product names, error codes, proper nouns |
keyword for conceptual queries - Neural search understands intent better; use auto or neural for natural language questionstext=True - Search returns URLs only by default; explicitly request content with text=Truehighlights - Use highlights=True for relevant snippets without downloading full page textEXA_API_KEY environment variable or pass explicitly to constructorsummary - For RAG applications, summary=True provides concise context without full page texttype="neural"; auto mode doesn't include them