Exa Search Integration Skill

Exa Search Integration

Quick Reference

| 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 |

Essential Patterns

Basic Search (Python)

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])

Basic Search (TypeScript)

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}`);
});

Search with Filters

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
)

Find Similar Links

similar = exa.find_similar_and_contents(
    "https://example.com/interesting-article",
    num_results=10,
    exclude_source_domain=True,
    text=True
)

Search Mode Selection

| 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 |

Common Mistakes

Using keyword for conceptual queries - Neural search understands intent better; use auto or neural for natural language questions
Not setting text=True - Search returns URLs only by default; explicitly request content with text=True
Ignoring highlights - Use highlights=True for relevant snippets without downloading full page text
Missing API key - Set EXA_API_KEY environment variable or pass explicitly to constructor
Over-filtering initially - Start with broad searches, then add domain/date filters to refine
Not using summary - For RAG applications, summary=True provides concise context without full page text
Expecting scores in auto mode - Relevance scores are only returned with type="neural"; auto mode doesn't include them

Agent Skills: Exa Search Integration

Install this agent skill to your local

Skill Files