ad-spend-optimizer
Analyze paid advertising performance across channels and recommend budget reallocation to maximize ROAS and minimize CAC. Use…
Extract structured data from websites. Use when: collecting competitor pricing; scraping product listings; extracting contact information; gathering research data; monitoring website changes
Claude Code
$ npx -y skills add guia-matthieu/clawfu-skills --skill web-scraper --agent claude-code
Codex
$ npx skills add guia-matthieu/clawfu-skills --skill web-scraper -a codex -y
Cursor
$ npx skills add guia-matthieu/clawfu-skills --skill web-scraper -a cursor -y
Gemini CLI
$ npx skills add guia-matthieu/clawfu-skills --skill web-scraper -a gemini-cli -y
GitHub Copilot
$ npx skills add guia-matthieu/clawfu-skills --skill web-scraper -a github-copilot -y
OpenCode
$ npx skills add guia-matthieu/clawfu-skills --skill web-scraper -a opencode -y
Windsurf
$ npx skills add guia-matthieu/clawfu-skills --skill web-scraper -a windsurf -y
name: web-scraper description: "Extract structured data from websites. Use when: collecting competitor pricing; scraping product listings; extracting contact information; gathering research data; monitoring website changes" license: MIT metadata: author: ClawFu version: 1.0.0 mcp-server: "@clawfu/mcp-skills"
> Extract structured data from websites using BeautifulSoup and requests - turn any webpage into usable data.
| Claude Does | You Decide | |-------------|------------| | Structures analysis frameworks | Strategic priorities | | Synthesizes market data | Competitive positioning | | Identifies opportunities | Resource allocation | | Creates strategic options | Final strategy selection | | Suggests implementation approaches | Execution decisions |
pip install beautifulsoup4 requests pandas click lxml
python scripts/main.py scrape https://example.com --selector "h1,h2,p" python scripts/main.py scrape https://example.com --selector ".product-price"
python scripts/main.py links https://example.com python scripts/main.py links https://example.com --internal-only
python scripts/main.py emails https://example.com python scripts/main.py emails https://example.com --depth 2
python scripts/main.py structured https://example.com/article --schema article python scripts/main.py structured https://example.com/product --schema product
python scripts/main.py scrape https://competitor.com/pricing --selector ".price,.plan-name" # Output: # Extracted 6 elements # 1. Starter - $29/mo # 2. Pro - $99/mo # 3. Enterprise - Contact us
python scripts/main.py structured https://blog.example.com/post --schema article
# Output: article_data.json
# {
# "title": "How to Scale Your Startup",
# "author": "Jane Doe",
# "date": "2024-01-15",
# "content": "...",
# "word_count": 1523
# }| Selector | Description | Example | |----------|-------------|---------| | `tag` | Element type | `h1`, `p`, `div` | | `.class` | Class name | `.price`, `.title` | | `#id` | Element ID | `#main-content` | | `tag.class` | Tag with class | `div.product` | | `tag[attr]` | Has attribute | `a[href]` | | `parent > child` | Direct child | `ul > li` | | `tag1, tag2` | Multiple | `h1, h2, h3` |
1. **Check robots.txt** - Respect site's scraping policy 2. **Rate limit** - Don't overload servers (1-2 req/sec) 3. **Identify yourself** - Use descriptive User-Agent 4. **Cache requests** - Don't re-scrape unchanged pages 5. **Terms of Service** - Check if scraping is allowed
category: automation subcategory: data-extraction dependencies: [beautifulsoup4, requests, pandas] difficulty: intermediate time_saved: 5+ hours/week
175 expert marketing methodologies for AI agents. Free. Open source. MIT licensed. Dunford on positioning. Schwartz on copywriting. Cialdini on persuasion. Ogilvy on advertising. Hormozi on offers. Voss on negotiation.
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