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affaan-m/ECC

exa-search

通过Exa MCP进行神经搜索，适用于网络、代码和公司研究。当用户需要网络搜索、代码示例、公司情报、人员查找，或使用Exa神经搜索引擎进行AI驱动的深度研究时使用。

69CollectingNetwork access
See how to use itView GitHub source
npx skills add https://github.com/affaan-m/ECC --skill "docs/zh-CN/skills/exa-search"
Automated source guide

Source checked Jul 28, 2026·Refresh due Oct 26, 2026

Reorganized from the pinned upstream SKILL.md

Turn exa-search's source instructions into a guide you can follow

According to the pinned SKILL.md from affaan-m/ECC: 通过 Exa MCP 服务器实现网页内容、代码、公司和人物的神经搜索。

npx skills add https://github.com/affaan-m/ECC --skill "docs/zh-CN/skills/exa-search"
Check the pinned source

Best fit

  • 通过Exa MCP进行神经搜索，适用于网络、代码和公司研究。当用户需要网络搜索、代码示例、公司情报、人员查找，或使用Exa神经搜索引擎进行AI驱动的深度研究时使用。

Bring this context

  • 从 GitHub、Stack Overflow 和文档站点查找代码示例和文档。

Expected outputs

  • A result that follows the pinned exa-search instructions.
  • A concise record of assumptions, inputs used, and unresolved questions.
  • A final check against the source workflow and relevant permission signals.

Key source sections

Read exa-search through these 5 source sections

Sections are extracted automatically from the pinned SKILL.md and link back to the source.

01

何时激活

用户需要当前网页信息或新闻 搜索代码示例、API 文档或技术参考资料 研究公司、竞争对手或市场参与者 查找特定领域的专业资料或人物 为任何开发任务进行背景调研 用户提到“搜索”、“查找”、“寻找”或“关于……的最新消息是什么”

SKILL.md · 何时激活
用户需要当前网页信息或新闻搜索代码示例、API 文档或技术参考资料研究公司、竞争对手或市场参与者
02

MCP 要求

必须配置 Exa MCP 服务器。添加到 /.claude.json：

SKILL.md · MCP 要求
必须配置 Exa MCP 服务器。添加到 /.claude.json：在 exa.ai 获取 API 密钥。 此仓库当前的 Exa 设置记录了此处公开的工具接口：websearchexa 和 getcodecontextexa。 如果你的 Exa 服务器公开了其他工具，请在文档或提示中依赖它们之前，先核实其确切名称。
03

核心工具

从 GitHub、Stack Overflow 和文档站点查找代码示例和文档。

SKILL.md · 核心工具
从 GitHub、Stack Overflow 和文档站点查找代码示例和文档。
04

web\search\exa

Review the “web\search\exa” section in the pinned source before continuing.

SKILL.md · web\search\exa
Review and apply the “web\search\exa” source section.
05

get\code\context\exa

从 GitHub、Stack Overflow 和文档站点查找代码示例和文档。

SKILL.md · get\code\context\exa
从 GitHub、Stack Overflow 和文档站点查找代码示例和文档。

SkillSignal prompt templates

Provide the task, context, and acceptance criteria

These prompts were written by SkillSignal from the source structure; they are not upstream text.

Task-start prompt

Confirm source fit, inputs, and outputs before acting.

Use exa-search to help me with: [specific task]. Context: [files, data, or background]. Constraints: [environment, scope, and prohibited actions]. Before acting, check the pinned SKILL.md and explain which sections apply, what inputs are still missing, and what you will deliver.

Source-guided execution

Make the Agent explicitly follow the key extracted sections.

Apply the pinned exa-search source to [task]. Pay particular attention to these source sections: “何时激活”, “MCP 要求”, “核心工具”, “web\search\exa”, “get\code\context\exa”. Preserve the important decision at each step. Mark facts not covered by the source as “needs confirmation” instead of inventing them. Then verify the result against my acceptance criteria: [criteria].

Result-review prompt

Check omissions, permissions, and source drift before delivery.

Review the current exa-search result: (1) does it satisfy the original task; (2) were any applicable steps or limits in the pinned SKILL.md missed; (3) did it perform any unauthorized file, command, network, or data action; and (4) which conclusions remain unverified? List issues first, then fix only what the source or user authorization supports.

Output checklist

Verify each item before delivery

The task matches the purpose documented in the SKILL.md.

The source section “何时激活” has been checked.

The source section “MCP 要求” has been checked.

The source section “核心工具” has been checked.

The source section “web\search\exa” has been checked.

Inputs, constraints, and acceptance criteria are explicit.

Unverified facts, compatibility, and outcome claims are clearly marked.

Any file, command, network, or data action has been reviewed.

Choose a different workflow

When another Skill is the better fit

exa-search

Call Exa Search (POST /search) for semantic web retrieval with ranked results, filters, freshness, highlights/text, structured output, or streaming. Use when the agent needs open-ended web search, competitor discovery, news, people, or research papers and does not already have URLs. Prefer Exa MCP web_search_exa / web_search_advanced_exa when available; otherwise raw HTTP with EXA_API_KEY. NOT for known-URL extraction (use exa-contents or firecrawl) or multi-step list-building (use company-resea

A separate implementation from MoizIbnYousaf/marketing-cli; compare its source, maintenance signals, and permission requirements.

Open source detail

exa-search

Web toolkit powered by Exa, tuned for scientific and technical content. Use this skill when the user needs to search the web or fetch/extract URL content. Covers: web search (semantic lookups, research, current info — with optional research-paper category and academic domain filtering) and URL extraction (fetching pages, articles, academic PDFs in batch). Use this skill for web-related tasks when the user wants high-quality search or scholarly filtering via category=research paper. Triggers on r

A separate implementation from K-Dense-AI/scientific-agent-skills; compare its source, maintenance signals, and permission requirements.

Open source detail

exa-search

Neural search via Exa MCP for web, code, and company research. Use when the user needs web search, code examples, company intel, people lookup, or AI-powered deep research with Exa's neural search engine.

A separate implementation from affaan-m/ECC; compare its source, maintenance signals, and permission requirements.

Open source detail

FAQ

What does exa-search do?

通过 Exa MCP 服务器实现网页内容、代码、公司和人物的神经搜索。

How do I start using exa-search?

The catalog detected this source-specific install command: npx skills add https://github.com/affaan-m/ECC --skill "docs/zh-CN/skills/exa-search". Inspect the command and pinned source before running it.

Which Agent platforms does it declare?

No dedicated Agent platform is declared in the pinned source record.

Repository stars
234,327
Repository forks
35,711
Quality
69/100
Source repository last pushed

Quality breakdown

Based on traceable docs and repository signals; stars are not treated as quality.

69/100
Documentation21/30
Specificity14/25
Maintenance20/20
Trust signals14/25

Compare before choosing

Related Agent Skills and source variants

These links are selected from shared tasks, functions, stacks, platforms, and same-name variants. Compare the source owner, documentation, permissions, and maintenance signals.

exa-search by MoizIbnYousaf

Call Exa Search (POST /search) for semantic web retrieval with ranked results, filters, freshness, highlights/text, structured output, or streaming. Use when the agent needs open-ended web search, competitor discovery, news, people, or research papers and does not already have URLs. Prefer Exa MCP web_search_exa / web_search_advanced_exa when available; otherwise raw HTTP with EXA_API_KEY. NOT for known-URL extraction (use exa-contents or firecrawl) or multi-step list-building (use company-resea

exa-search by k-dense-ai

Web toolkit powered by Exa, tuned for scientific and technical content. Use this skill when the user needs to search the web or fetch/extract URL content. Covers: web search (semantic lookups, research, current info — with optional research-paper category and academic domain filtering) and URL extraction (fetching pages, articles, academic PDFs in batch). Use this skill for web-related tasks when the user wants high-quality search or scholarly filtering via category=research paper. Triggers on r

exa-search by affaan-m

Neural search via Exa MCP for web, code, and company research. Use when the user needs web search, code examples, company intel, people lookup, or AI-powered deep research with Exa's neural search engine.

exa-search by affaan-m

Neural search via Exa MCP for web, code, and company research. Use when the user needs web search, code examples, company intel, people lookup, or AI-powered deep research with Exa's neural search engine.

exa-search by affaan-m

Exa MCPによるウェブ、コード、企業調査のためのニューラル検索。ユーザーがウェブ検索、コード例、企業情報、人物検索、またはExaのニューラル検索エンジンを使ったAI駆動の詳細調査を必要とする場合に使用します。

View original Skill.mdThis page is parsed directly from the repository SKILL.md without editorial rewriting. Collected: Jul 28, 2026 · about 1 min

Exa 搜索

通过 Exa MCP 服务器实现网页内容、代码、公司和人物的神经搜索。

何时激活

  • 用户需要当前网页信息或新闻
  • 搜索代码示例、API 文档或技术参考资料
  • 研究公司、竞争对手或市场参与者
  • 查找特定领域的专业资料或人物
  • 为任何开发任务进行背景调研
  • 用户提到“搜索”、“查找”、“寻找”或“关于……的最新消息是什么”

MCP 要求

必须配置 Exa MCP 服务器。添加到 ~/.claude.json：

"exa-web-search": {
  "command": "npx",
  "args": ["-y", "exa-mcp-server"],
  "env": { "EXA_API_KEY": "YOUR_EXA_API_KEY_HERE" }
}

在 exa.ai 获取 API 密钥。 此仓库当前的 Exa 设置记录了此处公开的工具接口：web_search_exa 和 get_code_context_exa。 如果你的 Exa 服务器公开了其他工具，请在文档或提示中依赖它们之前，先核实其确切名称。

核心工具

web_search_exa

用于当前信息、新闻或事实的通用网页搜索。

web_search_exa(query: "2026年最新人工智能发展", numResults: 5)

参数：

参数类型默认值说明
query字符串必填搜索查询
numResults数字8结果数量
type字符串auto搜索模式
livecrawl字符串fallback需要时优先使用实时爬取
category字符串无可选焦点，例如 company 或 research paper

get_code_context_exa

从 GitHub、Stack Overflow 和文档站点查找代码示例和文档。

get_code_context_exa(query: "Python asyncio patterns", tokensNum: 3000)

参数：

参数类型默认值说明
querystring必需代码或 API 搜索查询
tokensNumnumber5000内容令牌数（1000-50000）

使用模式

快速查找

web_search_exa(query: "Node.js 22 新功能", numResults: 3)

代码研究

get_code_context_exa(query: "Rust错误处理模式Result类型", tokensNum: 3000)

公司或人物研究

web_search_exa(query: "Vercel 2026年融资估值", numResults: 3, category: "company")
web_search_exa(query: "site:linkedin.com/in Anthropic AI安全研究员", numResults: 5)

技术深度研究

web_search_exa(query: "WebAssembly 组件模型状态与采用情况", numResults: 5)
get_code_context_exa(query: "WebAssembly 组件模型示例", tokensNum: 4000)

提示

  • 使用 web_search_exa 获取最新信息、公司查询和广泛发现
  • 使用 site:、引号内的短语和 intitle: 等搜索运算符来缩小结果范围
  • 对于聚焦的代码片段，使用较低的 tokensNum (1000-2000)；对于全面的上下文，使用较高的值 (5000+)
  • 当你需要 API 用法或代码示例而非通用网页时，使用 get_code_context_exa

相关技能

  • deep-research — 使用 firecrawl + exa 的完整研究工作流
  • market-research — 带有决策框架的业务导向研究
Source repo
affaan-m/ECC
Skill path
docs/zh-CN/skills/exa-search/SKILL.md
Commit SHA
4e973d3eaf92
Repository license
MIT
Data collected