Do I need to manage Python environments manually?

No, the skill uses 'uv' scripts with inline metadata, which automatically handles dependency installation and management every time a script is run.

Is this skill compatible with authenticated APIs?

Yes, it provides implementation patterns for API authentication, including the secure use of environment variables for tokens and keys.

How does this skill help reduce token usage?

Instead of feeding thousands of lines of raw HTML into the AI's context, this skill writes and executes a local Python script that extracts only the necessary data points, returning a tiny, structured JSON object instead.

Can I scrape sites that require JavaScript to load?

Yes, the skill includes a specific pattern for Browser-Required Sites using Playwright, allowing you to scrape dynamic content and single-page applications effectively.

Efficient Web Scraping

Name: Efficient Web Scraping
Author: ClementWalter

byClementWalter

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网络抓取与数据收集

Optimizes data extraction from websites and APIs using specialized Python scripts to maximize performance and minimize token consumption.

关于

Efficient Web Scraping is a specialized Claude Code skill designed to handle complex data extraction tasks without bloating the conversation context. By utilizing programmatic extraction through uv-managed Python scripts, this skill enables Claude to target specific fields and return structured JSON rather than reading thousands of lines of raw HTML. It includes robust patterns for handling static pages, authenticated APIs, and dynamic JavaScript content via Playwright, resulting in up to a 100x reduction in token usage while maintaining high data integrity and reasoning accuracy.

主要功能

Automated dependency management using uv inline metadata
Structured JSON output for immediate programmatic use
Context-aware token optimization for massive data reduction
Built-in error handling and rate-limiting best practices
Pre-defined patterns for static, dynamic, and API-based scraping
2 GitHub stars

使用场景

Extracting specific profile data and recent activity from social media platforms
Filtering and processing large API responses to extract only essential data points
Aggregating product information and pricing from multi-page e-commerce sites

关于

主要功能

Automated dependency management using uv inline metadata
Structured JSON output for immediate programmatic use
Context-aware token optimization for massive data reduction
Built-in error handling and rate-limiting best practices
Pre-defined patterns for static, dynamic, and API-based scraping
2 GitHub stars

使用场景

Extracting specific profile data and recent activity from social media platforms
Filtering and processing large API responses to extract only essential data points
Aggregating product information and pricing from multi-page e-commerce sites