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exa-search-proexa 搜索专业版

Agent Skill

exa-search-pro 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

4,187

周安装

178

GitHub Stars

公开资料未说明

下载量

1,467
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:exa-search-pro(exa 搜索专业版)
来源仓库:https://github.com/kennyzir/exa-search-pro
安装命令:
openclaw skills install exa-search-pro
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install exa-search-pro

简介

exa-search-pro 用于查找、检索和筛选相关信息,适合快速定位内容。

  • 适用于基于关键词或任务场景的信息搜索与筛选需求。
  • 通过 clawhub 安装,需结合来源仓库和 README 核验具体用法。
  • 安装前建议确认权限范围、维护状态及是否触发联网或命令执行。
  • 提供高级网络搜索,支持精确日期过滤与内容类型选择。

SKILL.md

name
Exa Search
description
>
metadata
requires
env

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:
   # 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 HappensDo ThisWhat You Get
Need academic papers from specific datesUse category: "research paper" + date rangeFiltered research results
Find GitHub projects from 2024Use category: "github" + start_published_date: "2024-01-01"Recent open-source projects
Semantic search for conceptsUse search_type: "neural"Intent-based results
Exact keyword matchingUse 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

FeatureTavilyExa
Date filteringtime_range (coarse)start/end date (precise)
Search modebasic/advanced (depth)neural/keyword (algorithm)
Content typesgeneral/news7+ types (papers, GitHub, PDF)
AI answer✅ Built-in❌ Not available
Best forQuick lookups, general infoResearch, 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

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

98.61%
按下载量换算1,447

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

可疑

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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