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data-scraper-intent

Skill321 starsChanged 7 months agoMITView on GitHub

A toolkit for web data extraction and search intent analysis. Includes patterns for handling lazy-loaded content and LLM prompts for classifying search keywords.

The file

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  • Distinctive
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  1. Distinctive:

    Step 1: Use the "Keyword Intent Classifier" prompt to categorize them.

    line 31

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Files
SKILL.md

Data Scraper & Intent Analyzer

This skill provides reusable patterns and prompts for two common SEO/data tasks:

  1. Web Data Extraction: Handling tricky scenarios like lazy-loaded images, Next.js Image components, and paginated content.
  2. Search Intent Classification: Using LLMs to classify keywords into actionable content categories.

Resources Included

  1. resources/scraping_patterns.md: A guide with code snippets on how to handle common web scraping challenges using Playwright/Puppeteer.
  2. resources/intent_prompts.md: Ready-to-use LLM prompts for classifying search keywords.

Usage

1. Data Extraction Patterns

Review resources/scraping_patterns.md when you need to extract data from:

  • Websites using lazy-loading for images (e.g., loading="lazy", IntersectionObserver).
  • Next.js apps using <Image> component (srcset, blur placeholders).
  • Sites with infinite scroll or "Load More" buttons.

2. Intent Analysis

Copy the prompts from resources/intent_prompts.md and use them with your LLM of choice (GPT-4, DeepSeek, Claude) to classify keywords from Google Trends, SEMrush, or Ahrefs.

Example Workflow (Trend to Page)

  1. Input: A list of rising keywords from Google Trends.
  2. Step 1: Use the "Keyword Intent Classifier" prompt to categorize them.
  3. Step 2: For "Informational" intents, create guide pages.
  4. Step 3: For "Transactional" intents, create tool pages.
  5. Output: A prioritized list of pages to create.

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