跳到正文
cccskills
免费在 GitHub 公开

extract-webpage-data

Extract structured data from web pages using AI

中文简介正在准备中。当前显示原文说明。

集成工具LinkedInStripe

实测评分 未实测

查看安装方法

包含的文件(2)

  • SKILL.md7.3 KB
  • skill.meta.json295 B

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Extract Webpage Data

Setup

Read your credentials from ~/.gooseworks/credentials.json:

export GOOSEWORKS_API_KEY=$(python3 -c "import json;print(json.load(open('$HOME/.gooseworks/credentials.json'))['api_key'])")
export GOOSEWORKS_API_BASE=$(python3 -c "import json;print(json.load(open('$HOME/.gooseworks/credentials.json')).get('api_base','https://api.gooseworks.ai'))")

If ~/.gooseworks/credentials.json does not exist, tell the user to run: npx gooseworks login

All endpoints use Bearer auth: -H "Authorization: Bearer $GOOSEWORKS_API_KEY"

Extract structured data from any web page using AI. Turn messy HTML into clean, organized data.

When to Use

  • User wants to extract specific data from a website
  • User asks to scrape information from a page
  • User needs structured data from unstructured content
  • User wants to pull product info, contact details, etc.
  • Converting web content to usable data

How It Works

Uses Olostep, Scrapegraph, or Riveter APIs for AI-powered data extraction.

Usage

Simple Scrape with Olostep

curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"olostep","path":"/v1/scrapes","body":{"url_to_scrape":"https://example.com/products"}}'

AI-Powered Extraction with Scrapegraph

curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"scrapegraph","path":"/v1/smartscraper","body":{"website_url":"https://example.com/team","user_prompt":"Extract all team members with their names, titles, and LinkedIn URLs"}}'

Schema-Based Extraction with Riveter

curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"riveter","path":"/v1/scrape","body":{"url":"https://example.com","schema":{"name":"string","price":"number","description":"string"}}}'

Get AI Answer from Web

curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"olostep","path":"/v1/answers","body":{"task":"Find the pricing for Notion Teams plan from their website"}}'

Crawl Multiple Pages

curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"olostep","path":"/v1/crawls","body":{"start_url":"https://example.com","max_pages":10}}'

Parameters

Olostep Scrape

  • url_to_scrape (required) - URL to scrape
  • formats - Output formats (markdown, html, text)

Scrapegraph

  • website_url (required) - URL to scrape
  • user_prompt (required) - Natural language description of what to extract

Riveter

  • url (required) - URL to scrape
  • schema - JSON schema defining the data structure to extract

Olostep Answer

  • task (required) - Natural language task/question

Response

Olostep Response

Returns a scrape object:

  • id (string) - Scrape ID (e.g., scrape_z926lxxon3)
  • result.markdown_content (string|null) - Page content as markdown
  • result.html_content (string|null) - Raw HTML (if requested via formats)
  • result.text_content (string|null) - Plain text (if requested)
  • result.markdown_hosted_url (string|null) - S3 URL for large content
  • result.links_on_page (array) - Links found on the page
  • result.screenshot_hosted_url (string|null) - Screenshot URL (if requested)
  • result.page_metadata (object) - status_code of the page
  • credits_consumed (integer) - Credits used for this scrape

Async crawls: POST /v1/crawls returns an id. Poll with GET /v1/crawls/{id} until complete.

Scrapegraph Response

Returns structured extraction result:

  • request_id (string) - Unique request identifier
  • status (string) - completed or pending
  • result (object) - AI-extracted data matching your prompt (dynamic keys)
  • error (string) - Empty on success, error message on failure

Note: For large pages, the POST may return status: "pending". Poll with GET /v1/smartscraper/{request_id} until status is completed.

Riveter Response

Returns scrape result:

  • request_status (string) - success or error
  • message (string) - Human-readable status
  • text (string) - Extracted page text content
  • url (string) - URL that was scraped
  • status_code (integer) - HTTP status of the page
  • run_key (string) - Unique run identifier
  • base_url_for_links (string) - Base URL for resolving relative links
  • riveter_app_link (string) - Link to view run in Riveter dashboard
  • credit_used (integer) - Credits consumed

Examples

User: "Get all the product names and prices from this page"

curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"scrapegraph","path":"/v1/smartscraper","body":{"website_url":"https://example.com/products","user_prompt":"Extract all products with name, price, and description"}}'

User: "Scrape the team page and get everyone's info"

curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"scrapegraph","path":"/v1/smartscraper","body":{"website_url":"https://example.com/about/team","user_prompt":"Extract team members: name, role, bio, photo URL, LinkedIn"}}'

User: "What are Stripe's API pricing details?"

curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"olostep","path":"/v1/answers","body":{"task":"Find Stripe API pricing breakdown from stripe.com/pricing"}}'

User: "Get all blog post titles and dates from this blog"

curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"riveter","path":"/v1/scrape","body":{"url":"https://blog.example.com","schema":{"posts":[{"title":"string","date":"string","url":"string"}]}}}'

Error Handling

  • 504 - Olostep timeout on slow pages — retry or try a simpler URL
  • 400 - Missing required parameters (url_to_scrape for Olostep, website_url + user_prompt for Scrapegraph, url for Riveter)
  • Scrapegraph returns error field in response body — check it even on 200 status
  • Riveter returns request_status: "error" with details in message
  • Some sites block automated scraping — try a different API if one fails

Tips

  • Scrapegraph is best for natural language extraction
  • Riveter is best when you know the exact schema you want
  • Olostep is great for general scraping and AI answers
  • For dynamic sites (JavaScript-heavy), these tools handle rendering
  • Be specific in your prompts for better extraction results
  • Some sites may block automated access

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Research supported advertising promises from a specific buyer's context, current product facts, customer language and observed ads. Turn them into static, video or copy ideas; match video ideas to actual recipes and save a product-scoped angle bank for write-video-ad-script. Product-led discovery can use verified facts without reviews. Reference persistence and reach are observations, not proof of performance.

中文简介正在准备中。当前显示原文说明。

gooseworks-ai/goose-skills12632026年10月23日 更新

Analyze ad campaign performance data (Google, Meta, LinkedIn) to identify what's working, what's wasting budget, and specific cut/scale/test recommendations. Runs statistical analysis, funnel diagnostics, and multi-channel budget reallocation with specific dollar-amount shift recommendations and scenario modeling.

中文简介正在准备中。当前显示原文说明。

gooseworks-ai/goose-skills12632026年10月23日 更新

For paid lead-gen and participant-recruitment ads, replaces vanity CPA with true CAC per qualified lead by joining ad-platform data with downstream funnel events, surfaces tracking gaps, and classifies every creative into Scale / Keep / Investigate / Cut.

中文简介正在准备中。当前显示原文说明。

gooseworks-ai/goose-skills12632026年10月23日 更新

The intake stage of a Meta ad harness. Researches the brand first, states what it assumes, and asks only what it cannot infer and what would change money, claims or legal exposure if guessed wrong — at most four questions a turn, in plain business language. Writes the brand's stable facts (ads/brand.md), the campaign brief, and a log of what was asked vs assumed. Use it when someone wants to run Meta ads and the brand's ad facts are not yet recorded.

中文简介正在准备中。当前显示原文说明。

gooseworks-ai/goose-skills12632026年10月23日 更新

Checks paid ads against the ad platform's rules (Meta, TikTok, Google, LinkedIn and others) and the brand's category rules: the copy, on-image or on-screen text, pictures and people. Rewrites what can be fixed honestly, adds the disclosures that are needed, and flags anything that needs a human or legal review, with one pass, fixed or flag line per ad and platform. Use alone when you already have the ad text or images and know where they will run; otherwise run the playbook for the job (e.g. make-static-ads, make-content, email-lifecycle).

中文简介正在准备中。当前显示原文说明。

gooseworks-ai/goose-skills12632026年10月23日 更新

Analyze the message match between your ads and landing pages. Checks if the promise in the ad copy carries through to the landing page headline, body, and CTA. Flags disconnects that kill conversion rates. Works with Google, Meta, and LinkedIn ads.

中文简介正在准备中。当前显示原文说明。

gooseworks-ai/goose-skills12632026年10月23日 更新

查看 gooseworks-ai 的全部技能

报告此技能的问题