exa search
by @kennyzir
Advanced web search with precise date filtering and content type selection. Use when you need academic papers, GitHub repositories, research content, or spec...
clawhub install exa-search-proπ About This Skill
name: Exa Search description: > Advanced web search with precise date filtering and content type selection. Use when you need academic papers, GitHub repositories, research content, or specific date ranges. Handles neural search (semantic understanding), keyword search, and content type filtering (research papers, GitHub, news, PDFs). Perfect for research, competitive analysis, and content discovery. metadata: requires: env: - CLAW0X_API_KEY
Exa Search
Cloud skill by Claw0x β powered by Claw0x Gateway API.
Advanced web search with precise date filtering, content type selection, and neural search. Perfect for research, competitive analysis, and specialized content discovery.
> Requires Claw0x API key. Sign up at claw0x.com to get your key.
Prerequisites
1. Sign up at claw0x.com 2. Create API key in Dashboard 3. Set environment variable:
# Add to ~/.openclaw/.env
CLAW0X_API_KEY=ck_live_...
Pricing
$0.005 per successful call. Failed calls are free.
Quick Reference
| When This Happens | Do This | What You Get |
|-------------------|---------|--------------|
| Need academic papers from specific dates | Use category: "research paper" + date range | Filtered research results |
| Find GitHub projects from 2024 | Use category: "github" + start_published_date: "2024-01-01" | Recent open-source projects |
| Semantic search for concepts | Use search_type: "neural" | Intent-based results |
| Exact keyword matching | Use search_type: "keyword" | Traditional search results |
5-Minute Quickstart
Step 1: Get API Key (30 seconds)
Sign up at claw0x.com β Dashboard β Create API KeyStep 2: Set Environment Variable (30 seconds)
export CLAW0X_API_KEY="ck_live_..."
Step 3: Install Skill (30 seconds)
openclaw skills install exa-search
Step 4: Use Skill (1 minute)
const result = await agent.run('exa-search', {
query: 'transformer architecture improvements',
category: 'research paper',
start_published_date: '2024-01-01',
end_published_date: '2024-03-31',
search_type: 'neural',
num_results: 5
});console.log(Found ${result.result_count} papers);
result.results.forEach(paper => {
console.log(${paper.title} (${paper.published_date}));
});
Real-World Use Cases
Scenario 1: Academic Research
Problem: Find transformer papers from Q1 2024 Solution: Use precise date filtering + research paper category Example:{
query: "transformer architecture improvements",
category: "research paper",
start_published_date: "2024-01-01",
end_published_date: "2024-03-31"
}
Scenario 2: GitHub Discovery
Problem: Find Rust web frameworks created in 2024 Solution: Use GitHub category + date filtering Example:{
query: "rust web framework",
category: "github",
start_published_date: "2024-01-01"
}
Scenario 3: Competitive Analysis
Problem: Find similar companies in AI agent space Solution: Use company category + domain exclusion Example:{
query: "AI agent platforms",
category: "company",
exclude_domains: ["competitor.com"]
}
Integration Recipes
OpenClaw Agent
import { Claw0xClient } from '@claw0x/sdk';const claw0x = new Claw0xClient(process.env.CLAW0X_API_KEY);
const papers = await claw0x.call('exa-search', {
query: 'large language model reasoning',
category: 'research paper',
start_published_date: '2024-01-01',
search_type: 'neural'
});
LangChain Agent
from claw0x import Claw0xClientclient = Claw0xClient(api_key=os.environ['CLAW0X_API_KEY'])
repos = client.call('exa-search', {
'query': 'rust web framework',
'category': 'github',
'start_published_date': '2024-01-01'
})
Custom Agent
const response = await fetch('https://api.claw0x.com/v1/call', {
method: 'POST',
headers: {
'Authorization': Bearer ${process.env.CLAW0X_API_KEY},
'Content-Type': 'application/json'
},
body: JSON.stringify({
skill: 'exa-search',
input: {
query: 'AI regulation news',
category: 'news',
start_published_date: '2024-03-15',
end_published_date: '2024-03-22'
}
})
});
Exa vs Tavily Comparison
| Feature | Tavily | Exa | |---------|--------|-----| | Date filtering | time_range (coarse) | start/end date (precise) | | Search mode | basic/advanced (depth) | neural/keyword (algorithm) | | Content types | general/news | 7+ types (papers, GitHub, PDF) | | AI answer | β Built-in | β Not available | | Best for | Quick lookups, general info | Research, specialized content |
Use Tavily when: You need a quick answer or general web search.
Use Exa when: You need precise dates, specific content types, or semantic search.
Why Use Via Claw0x?
About Claw0x
Claw0x is the native skills layer for AI agents β providing unified API access, atomic billing, and quality control.
Explore more skills: claw0x.com/skills
GitHub: github.com/kennyzir/exa-search
βοΈ Configuration
1. Sign up at claw0x.com 2. Create API key in Dashboard 3. Set environment variable:
# Add to ~/.openclaw/.env
CLAW0X_API_KEY=ck_live_...