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exa search

Advanced web search with precise date filtering and content type selection. Use when you need academic papers, GitHub repositories, research content, or spec...
高级网页搜索,支持精确的日期过滤和内容类型筛选。适用于查找学术论文、GitHub仓库、研究资料或规范。
kennyzir
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概述

Exa Search

Cloud skill by Claw0x — 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:

```bash

# Add to ~/.openclaw/.env

CLAW0X_API_KEY=ck_live_...

```

Pricing

$0.005 per successful call. Failed calls are free.

  • Pay only for successful responses (2xx status)
  • No monthly fees, no subscriptions
  • Get started with $5 free credit

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 → Dashboard → Create API Key

Step 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 Claw0xClient

client = 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 | ✅ Built-in | ❌ 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?

  • Unified billing: One API key for all skills
  • Atomic pricing: Pay per call, not per month
  • Zero cost on failure: Failed calls don't charge
  • Production-ready: 99.9% uptime, <100ms latency
  • Security scanned: OSV.dev integration
  • No Exa API key needed: Claw0x handles upstream authentication

About Claw0x

Claw0x is the native skills layer for AI agents — providing unified API access, atomic billing, and quality control.

Explore more skills: claw0x.com/skills

GitHub: github.com/kennyzir/exa-search

版本历史

共 1 个版本

  • v1.0.0 当前
    2026-03-31 16:55 安全 安全

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