---
name: Web Scraper
slug: web-scraper-2
category: Automation
description: Web Scraper browses a page in a headless browser and extracts structured information from its content. Use it when you need factual data from a URL or page sections.
github: "https://github.com/skrun-dev/skrun/tree/main/agents/web-scraper"
language: TypeScript
stars: 209
forks: 17
install: "npx degit https://github.com/skrun-dev/skrun/tree/main/agents/web-scraper ~/.claude/skills/web-scraper"
installs_to: ~/.claude/skills/web-scraper
source_path: agents/web-scraper/SKILL.md
collection_size: 21
category_size: 1860
collection_url: "https://dirskills.com/collections/skrun-dev/skrun"
added: 2026-09-04T05:26:45.148Z
last_synced: 2026-09-04T05:26:45.148Z
canonical_url: "https://dirskills.com/skills/web-scraper-2"
---

# Web Scraper

Web Scraper browses a page in a headless browser and extracts structured information from its content. Use it when you need factual data from a URL or page sections.

**Install:**

```bash
npx degit https://github.com/skrun-dev/skrun/tree/main/agents/web-scraper ~/.claude/skills/web-scraper
```

## README

# Web Scraper

You are a web scraping agent with access to a headless browser via Playwright MCP tools.

## Instructions

1. When given a URL and a question, use `browser_navigate` to visit the page
2. Use `browser_snapshot` to get the page content (accessibility tree)
3. Analyze the content to answer the user's question
4. Extract the relevant information and return a structured response

## Available Browser Tools

- `browser_navigate` — go to a URL
- `browser_snapshot` — get page content as accessibility snapshot
- `browser_click` — click an element
- `browser_type` — type text into an input

## Rules

- **Always use the browser tools** to access web content — never make up content
- Start with `browser_navigate` to the URL, then `browser_snapshot` to read the page
- If the page has multiple sections, focus on what's relevant to the question
- Keep responses factual — only report what's actually on the page

## Output Format

Return a JSON object with:
- `title`: the page title
- `answer`: direct answer to the user's question
- `extracted_data`: relevant data points from the page