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Agent Skill · 研究检索

data-extraction(数据提取)

用于辅助数据整理、表格处理、CSV/Excel 分析、指标计算和图表准备。它适合让 Agent 清洗字段、汇总数据、发现异常、生成统计口径或把分析结果转成可读说明。使用时需要确认数据来源、字段含义和时间范围,避免把样本数据当全量事实;涉及敏感数据、导出文件或批量写回时,应先确认权限和脱敏边界。

data-extraction 是研究检索类 Agent Skill,可用宿主为 Local Agent,通过unknown获取,权限为调用外部服务;许可证信息还不明确,暂无第三方扫描结果,按安装量在研究检索类的 73,675 个 Skill 里排第 68,884。

总安装 222周安装 9下载 70核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
许可证
unknown

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:data-extraction(数据提取)
来源仓库:https://cbskills.xcloudzen.com
仓库路径:data-extraction
安装命令:
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。当前暂无明确安装命令,请以来源页面说明为准。

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于从网页中提取结构化 JSON 数据的高效工具。优先尝试 JSON-LD 微数据抓取,失败时降级解析 DOM。支持商品、文章、活动等各类页面 schema 识别。对列表页与 SPA 动态内容提供备用解析策略。返回空结果时应及时切换更高阶解析方法。

data-extraction 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:data-extraction

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Local Agent;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    没有现成安装命令,按unknown的说明从来源页面获取,仓库路径是 data-extraction。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

data-extraction 怎么安装?

公开资料没有给出可以直接复制的命令,需要按来源页面说明手动安装,仓库内路径为 data-extraction。

data-extraction 支持哪些 AI 工具?

公开资料标注支持 Local Agent。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

data-extraction 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

data-extraction 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

data-extraction 用的人多吗?

公开数据是累计安装 222 次,近一周安装 9 次,下载 70 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

data-extraction 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 Local Agent 一种宿主,触发方式和使用习惯不用来回切换。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Local Agent,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 要求有安全扫描结论才肯安装的团队。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
data-extraction

数据提取 · 本页

222—调用外部服务未明确未收录

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Data Extraction — Structured Data from Pages

Goal: turn a rendered page into clean JSON. Always try the lightest-weight tool first; escalate only when it returns empty or wrong data.

Priority order

  1. page_schema(tab_id?) — JSON-LD + microdata. Products, recipes, events, articles, local-business listings usually embed complete structured data. One call, often zero parsing. Caveat: returns {"schemas": []} on plenty of pages — disambiguation / list pages (Wikipedia), Google search results, Instagram profile pages, most SPAs without server-side rendering. Don't assume schema exists; fall through to the next tool if empty.
  2. page_article(tab_id?, max_wait=10000) — Mozilla Readability + SPA wait. Returns {title, author, date, image, content} for editorial pages. Use for anything you'd call "an article." Increase max_wait to 15000 for heavy SPAs.
  3. page_headings(tab_id?) — h1–h6 outline. Cheap. Use to plan a targeted extraction before dumping the whole page.
  4. execute_script — custom DOM extractor. Use when the data you want isn't in schema and isn't article prose (price badges, review counts, custom data attributes, tabular data).
  5. page_markdown(tab_id?) — full-page Markdown dump. Includes nav/footer/sidebar. Last resort when page_article errors (dashboards, search results, listings).
  6. page_source(tab_id?) / page_text(tab_id?) — raw HTML / plain text. Fallback when selectors misbehave or paywalls are CSS-only.

Reusable scripts

Each capability has a focused JS file under scripts/. To use one:

  1. Read the script file to load it as a string.
  2. Pass the contents as the code argument to mcp__chrome-bridge__execute_script.
  3. The script returns a structured object — see the header comment at the top of each file for the exact return shape.
TaskPre-conditionScriptNotes
Product DOM fallbackpage_schema() returned [] or sparse Productscripts/product_dom_fields.jsAdapt the right-hand selectors per site.
TablesPage renderedscripts/tables_extract.jsReturns every table as {headers, rows}. Use instead of page_markdown() — markdown mangles tables.
Listing linksOn a listing/index pagescripts/listing_links.jsScoped to article h2 a, article h3 a. Edit the selector for sites that use a different wrapper.

Pattern: schema-first

navigate(url='https://www.example.com/product/xyz')
# wait for ready
data = page_schema()
# If data contains a @type=Product entry with name/price/offers, you're done.

When schema is missing or sparse, fall through to the DOM fallback:

execute_script(code=<contents of scripts/product_dom_fields.js>)

Pattern: articles

For news, blogs, docs, Substack, Medium — try page_article first:

navigate(url='https://...')
# wait
article = page_article()
# → { title, author, date, image, content } (Markdown body)

If page_article returns {error:...} (dashboards, listing pages, custom layouts), fall through to page_schema then page_markdown.

Pattern: tables

execute_script(code=<contents of scripts/tables_extract.js>)
# → [{ index, caption, headers, rows }, ...] one entry per <table>

Pattern: links / listings

execute_script(code=<contents of scripts/listing_links.js>)
# → [{ title, url }, ...]

Dynamic content

Content injected after load (infinite scroll, "Read more" expanders):

# trigger the load
execute_script(code="(function(){ window.scrollTo(0, document.body.scrollHeight); return 'scrolled'; })()")
# wait a few seconds, then re-extract
page_schema()   # or whichever tool

If content only appears after a click:

dom_click('button.expand-all')
# wait, re-extract

Return shape

Every extractor should return a plain JSON-serializable object. Good shapes:

{ source_url, captured_at, items: [{ title, url, price, ... }] }

Always include the source_url and a timestamp so downstream consumers can audit staleness. Don't return DOM nodes, HTML blobs, or images — extract the field you need and return that.

VERBATIM RULE — never summarize a body field

When the user asks for a body, description, content, full text, article, excerpt, or anything similar, the value MUST be the actual text returned by page_text / page_article().content / page_markdown — copied as-is (you may trim trailing site chrome like "RELATED NEWS", "Top Articles", "Follow Us", "Comments", footer links). You may NOT:

  • write a summary in your own words
  • paraphrase or condense
  • substitute a description like "Article covers Q1 results and analyst commentary"
  • substitute placeholder text like "Full article text can be fetched on request" or "Retrieved live content from source"
  • return only the title or only the first paragraph when the request was the body

Field names like full_text, body, content, description, excerpt are content slots, not metadata slots. If you don't have the verbatim text yet, navigate to the item and call page_text before answering.

Examples — body field

// ✓ CORRECT: the value is the actual returned text from page_text()
{
  "url": "https://news.site/q1-results",
  "full_text": "Acme Corp posted Q1 revenue of $4.2B, up 18% YoY, beating analyst consensus of $3.9B. CEO Jane Doe attributed the gain to enterprise contract renewals and a 12% lift in international bookings. Operating margin expanded to 23.4% from 21.1% a year ago, helped by lower customer-acquisition spend. The company guided FY revenue to $17–18B, in line with the Street. Shares rose 6% in after-hours trading. ..."
}

// ✗ WRONG: summary disguised as body
{
  "url": "https://news.site/q1-results",
  "full_text": "Article on Acme's Q1 earnings covering revenue beat, margin expansion, and full-year guidance."
}

// ✗ WRONG: placeholder
{
  "url": "https://news.site/q1-results",
  "full_text": "Q1 earnings article — full text available on the source page."
}

// ✗ WRONG: title repeated as body
{
  "url": "https://news.site/q1-results",
  "full_text": "Acme Corp Q1 Earnings"
}

Common failures

SignalCauseFix
page_schema returns []Site has no structured dataSkip to page_article or custom extractor
page_article returns {error}Not an article pageUse page_schema / page_markdown / custom extractor instead
Selectors match nothingPage not yet hydratedPoll document.readyState or a known element; scroll to trigger lazy load
execute_script returns undefinedBare return at top levelWrap the code in (function(){...})() (the scripts in scripts/ already do this)
execute_script errors with Invalid \escapeJS regex backslashes not double-escaped for JSONPass scripts as file contents (no JSON encoding) — the scripts/ files don't need escaping. If you must inline regex, prefer indexOf() / includes().
execute_script times out (HTTP 504)Script does something slow (image fetch, big loop)Trim the logic; return fewer fields; avoid fetch() inside the script
Paywalled content hiddenSome paywalls only hide via CSSTry page_text — the body text is often still in the DOM

平台分布

Local Agent

85%
按下载量换算60

安全审计

暂无安全审计结果可展示。

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。目前只有一个公开来源,建议同时核对源仓库。

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