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技能库 智客分类:写作与研究 web-search-exa OpenClaw

Web Search Exa

神经网络搜索,内容提取,公司和人员研究,代码搜索,以及通过Exa MCP服务器进行深层研究. 需要时使用:(1)以语义理解搜索网络——不只是关键词,(2)找到研究论文,新闻,微博,公司,或人,(3)从URL中提取干净的内容,(4)发现与已知URL的相近的页面,(5)获得代码示例和文件,(6)用报告进行深入多步骤研究,(7)通过引用获得快速综合答案. 不用于: 本地文件操作,非网络任务,或不涉及网页搜索或内容检索的任何东西.

1066 安装量 · 44 星标

官方网址:ClawHub

技能介绍

先看中文介绍;官方 description 原文单独保留,不改写 SKILL.md。

做什么

神经网络搜索、内容提取、公司和人员研究、代码搜索,以及通过Exa MCP服务器进行深入研究

何时用

官方 description 未单独写出 Use when。按规范,代理会在用户任务与这段 description 的关键词匹配时激活本技能。

代理如何加载

按 Agent Skills 渐进披露:启动时只加载 name 与 description(约 100 token);任务匹配后才读入整份 SKILL.md 正文;scripts/、references/、assets/ 仅在需要时再读。 本文件正文结构:Exa — Neural Web Search & Research、Setup、OpenClaw、Tool Reference、Default tools (available without API key)、Optional tools (enable via `tools` param, need API key for some)。 其中含规范建议的小节:输入输出示例。

文件分析

文件分析:这是一份仅含 SKILL.md 的指令型技能,代理激活后整份正文进入上下文。

官方 description(原文)

Neural web search, content extraction, company and people research, code search, and deep research via the Exa MCP server. Use when you need to: (1) search the web with semantic understanding — not just keywords, (2) find research papers, news, tweets, companies, or people, (3) extract clean content from URLs, (4) find semantically similar pages to a known URL, (5) get code examples and documentation, (6) run deep multi-step research with a report, (7) get a quick synthesized answer with citations. NOT for: local file operations, non-web tasks, or anything that doesn't involve web search or content retrieval.

Exa — Neural Web Search & ResearchSetupOpenClawTool ReferenceDefault tools (available without API key)Optional tools (enable via `tools` param, need API key for some)web_search_exaweb_search_advanced_exaExamplescompany_research_exapeople_search_exaget_code_context_exa

来源分类:ClawHub Web Search

SKILL.md 与 Agent 调用

官方规范 ↗
name
web-search-exa
description
Neural web search, content extraction, company and people research, code search, and deep research via the Exa MCP server. Use when you need to: (1) search the web with semantic understanding — not just keywords, (2) find research papers, news, tweets, companies, or people, (3) extract clean content from URLs, (4) find semantically similar pages to a known URL, (5) get code examples and documentation, (6) run deep multi-step research with a report, (7) get a quick synthesized answer with citations. NOT for: local file operations, non-web tasks, or anything that doesn't involve web search or content retrieval.
  1. 发现技能客户端向 Agent 提供名称与描述目录。
  2. 匹配与调用用户指定或任务匹配后,载入 SKILL.md 指令。
  3. 按需加载按步骤读取参考文档、使用脚本与素材。

具体调用语法与可用工具以目标 Agent 客户端为准。 查看调用机制说明 ↗

安装这个技能

Skills CLI ↗

先选择目标 Agent 和安装范围,保留技能包的附属文件,安装后检查客户端能否发现该技能。

交给 Agent 安装

复制安装指令给支持 Agent Skills 的代理,确认其中的目标目录与客户端匹配。

把 Agent Skill「web-search-exa」安装到我的项目:SKILL.md 原文与官方 description 见 https://zicq.com/zh/skills/skl-d2c5acc50a8929d8-Web-Search-Exa.html
请存为 .cursor/skills/web-search-exa/SKILL.md 或 .claude/skills/web-search-exa/SKILL.md,frontmatter 的 name 与 description 保持原样,不要改写。

当前没有明确的 GitHub 技能包地址,请按来源页面的安装器说明操作。

ClawHub ↗

阅读排版

name: web-search-exa description: "Neural web search, content extraction, company and people research, code search, and deep research via the Exa MCP server. Use when you need to: (1) search the web with semantic understanding — not just keywords, (2) find research papers, news, tweets, companies, or people, (3) extract clean content from URLs, (4) find semantically similar pages to a known URL, (5) get code examples and documentation, (6) run deep multi-step research with a report, (7) get a quick synthesized answer with citations. NOT for: local file operations, non-web tasks, or anything that doesn't involve web search or content retrieval."

Exa — Neural Web Search & Research

Exa is a neural search engine. Unlike keyword-based search, it understands meaning — you describe the page you're looking for and it finds it. Returns clean, LLM-ready content with no scraping needed.

MCP server: https://mcp.exa.ai/mcp Free tier: generous rate limits, no key needed for basic tools API key: dashboard.exa.ai/api-keys — unlocks higher limits + all tools Docs: exa.ai/docs GitHub: github.com/exa-labs/exa-mcp-server

Setup

Add the MCP server to your agent config:

# OpenClaw
openclaw mcp add exa --url "https://mcp.exa.ai/mcp"

Or in any MCP config JSON:

{
  "mcpServers": {
    "exa": {
      "url": "https://mcp.exa.ai/mcp"
    }
  }
}

To unlock all tools and remove rate limits, append your API key:

https://mcp.exa.ai/mcp?exaApiKey=YOUR_EXA_KEY

To enable specific optional tools:

https://mcp.exa.ai/mcp?exaApiKey=YOUR_KEY&tools=web_search_exa,web_search_advanced_exa,people_search_exa,crawling_exa,company_research_exa,get_code_context_exa,deep_researcher_start,deep_researcher_check,deep_search_exa

Tool Reference

Default tools (available without API key)

| Tool | What it does | |------|-------------| | web_search_exa | General-purpose web search — clean content, fast | | get_code_context_exa | Code examples + docs from GitHub, Stack Overflow, official docs | | company_research_exa | Company overview, news, funding, competitors |

Optional tools (enable via tools param, need API key for some)

| Tool | What it does | |------|-------------| | web_search_advanced_exa | Full-control search: domain filters, date ranges, categories, content modes | | crawling_exa | Extract full page content from a known URL — handles JS, PDFs, complex layouts | | people_search_exa | Find LinkedIn profiles, professional backgrounds, experts | | deep_researcher_start | Kick off an async multi-step research agent → detailed report | | deep_researcher_check | Poll status / retrieve results from deep research | | deep_search_exa | Single-call deep search with synthesized answer + citations (needs API key) |


web_search_exa

Fast general search. Describe what you're looking for in natural language.

Parameters:

  • query (string, required) — describe the page you want to find
  • numResults (int) — number of results, default 10
  • type — auto (best quality), fast (lower latency), deep (multi-step reasoning)
  • livecrawl — fallback (default) or preferred (always fetch fresh)
  • contextMaxCharacters (int) — cap the returned content size
web_search_exa {
  "query": "blog posts about using vector databases for recommendation systems",
  "numResults": 8
}
web_search_exa {
  "query": "latest OpenAI announcements March 2026",
  "numResults": 5,
  "type": "fast"
}

web_search_advanced_exa

The power-user tool. Everything web_search_exa does, plus domain filters, date filters, category targeting, and content extraction modes.

Extra parameters beyond basic search:

| Parameter | Type | What it does | |-----------|------|-------------| | includeDomains | string[] | Only return results from these domains (max 1200) | | excludeDomains | string[] | Block results from these domains | | category | string | Target content type — see table below | | startPublishedDate | string | ISO date, results published after this | | endPublishedDate | string | ISO date, results published before this | | maxAgeHours | int | Content freshness — 0 = always livecrawl, -1 = cache only, 24 = cache if <24h | | contents.highlights | object | Extractive snippets relevant to query. Set maxCharacters to control size | | contents.text | object | Full page as clean markdown. Set maxCharacters to cap | | contents.summary | object | LLM-generated summary. Supports query and JSON schema for structured extraction |

Categories:

| Category | Best for | |----------|---------| | company | Company pages, LinkedIn company profiles | | people | LinkedIn profiles, professional bios, personal sites | | research paper | arXiv, academic papers, peer-reviewed research | | news | Current events, journalism | | tweet | Posts from X/Twitter | | personal site | Blogs, personal pages | | financial report | SEC filings, earnings reports |

Examples

Research papers:

web_search_advanced_exa {
  "query": "transformer architecture improvements for long-context windows",
  "category": "research paper",
  "numResults": 15,
  "contents": { "highlights": { "maxCharacters": 3000 } }
}

Company list building with structured extraction:

web_search_advanced_exa {
  "query": "Series A B2B SaaS companies in climate tech founded after 2022",
  "category": "company",
  "numResults": 25,
  "contents": {
    "summary": {
      "query": "company name, what they do, funding stage, location",
      "schema": {
        "type": "object",
        "properties": {
          "name": { "type": "string" },
          "description": { "type": "string" },
          "funding": { "type": "string" },
          "location": { "type": "string" }
        }
      }
    }
  }
}

People search — find candidates with specific profiles:

web_search_advanced_exa {
  "query": "machine learning engineers at fintech startups in NYC with experience in fraud detection",
  "category": "people",
  "numResults": 20,
  "contents": { "highlights": { "maxCharacters": 2000 } }
}

Finding pages similar to a known URL: Use the URL itself as the query — Exa will find semantically similar pages:

web_search_advanced_exa {
  "query": "https://linkedin.com/in/some-candidate-profile",
  "numResults": 15,
  "contents": { "highlights": { "maxCharacters": 2000 } }
}

Recent news with freshness control:

web_search_advanced_exa {
  "query": "AI regulation policy updates",
  "category": "news",
  "maxAgeHours": 72,
  "numResults": 10,
  "contents": { "highlights": { "maxCharacters": 4000 } }
}

Scoped domain search:

web_search_advanced_exa {
  "query": "authentication best practices",
  "includeDomains": ["owasp.org", "auth0.com", "docs.github.com"],
  "numResults": 10,
  "contents": { "text": { "maxCharacters": 5000 } }
}

company_research_exa

One-call company research. Returns business overview, recent news, funding, and competitive landscape.

company_research_exa { "query": "Stripe payments company overview and recent news" }
company_research_exa { "query": "what does Anduril Industries do and who are their competitors" }

people_search_exa

Find professionals by role, company, location, expertise. Returns LinkedIn profiles and bios.

people_search_exa { "query": "VP of Engineering at healthcare startups in San Francisco" }
people_search_exa { "query": "AI researchers specializing in multimodal models" }

get_code_context_exa

Search GitHub repos, Stack Overflow, and documentation for code examples and API usage patterns.

get_code_context_exa { "query": "how to implement rate limiting in Express.js with Redis" }
get_code_context_exa { "query": "Python asyncio connection pooling example with aiohttp" }

crawling_exa

Extract clean content from a specific URL. Handles JavaScript-rendered pages, PDFs, and complex layouts. Returns markdown.

crawling_exa { "url": "https://arxiv.org/abs/2301.07041" }

Good for when you already have the URL and want to read the page.


deep_researcher_start + deep_researcher_check

Long-running async research. Exa's research agent searches, reads, and compiles a detailed report.

Start a research task:

deep_researcher_start {
  "query": "competitive landscape of AI code generation tools in 2026 — key players, pricing, technical approaches, market share"
}

Check status (use the researchId from the start response):

deep_researcher_check { "researchId": "abc123..." }

Poll deep_researcher_check until status is completed. The final response includes the full report.


deep_search_exa

Single-call deep search: expands your query across multiple angles, searches, reads results, and returns a synthesized answer with grounded citations. Requires API key.

deep_search_exa { "query": "what are the leading approaches to multimodal RAG in production systems" }

Supports structured output via outputSchema:

deep_search_exa {
  "query": "top 10 aerospace companies by revenue",
  "type": "deep",
  "outputSchema": {
    "type": "object",
    "required": ["companies"],
    "properties": {
      "companies": {
        "type": "array",
        "items": {
          "type": "object",
          "properties": {
            "name": { "type": "string" },
            "revenue": { "type": "string" },
            "hq": { "type": "string" }
          }
        }
      }
    }
  }
}

Query Craft

Exa is neural — it matches on meaning, not keywords. Write queries like you'd describe the ideal page to a colleague.

Do: "blog post about using embeddings for product recommendations at scale" Don't: "embeddings product recommendations"

Do: "Stripe payments company San Francisco fintech" Don't: "Stripe" (too ambiguous)

  • Use category when you know the content type — it makes a big difference.
  • For broader coverage, run 2-3 query variations in parallel and deduplicate results.
  • For agentic workflows, use highlights instead of full text — it's 10x more token-efficient while keeping the relevant parts.

Token Efficiency

| Content mode | When to use | |-------------|------------| | highlights | Agent workflows, factual lookups, multi-step pipelines — most token-efficient | | text | Deep analysis, when you need full page context | | summary | Quick overviews, structured extraction with JSON schema |

Set maxCharacters on any content mode to control output size.

When to Reach for Which Tool

| I need to... | Use | |-------------|-----| | Quick web lookup | web_search_exa | | Research papers, academic search | web_search_advanced_exa + category: "research paper" | | Company intel, competitive analysis | company_research_exa or advanced + category: "company" | | Find people, candidates, experts | people_search_exa or advanced + category: "people" | | Code examples, API docs | get_code_context_exa | | Read a specific URL | crawling_exa | | Find pages similar to a URL | web_search_advanced_exa with URL as query | | Recent news / tweets | Advanced + category: "news" or "tweet" + maxAgeHours | | Detailed research report | deep_researcher_start → deep_researcher_check | | Quick answer with citations | deep_search_exa |


Docs: exa.ai/docs — Dashboard: dashboard.exa.ai — Support: [email protected]

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