Agent skill
scrape
Scrape any webpage as clean markdown via Bright Data Web Unlocker API. Bypasses bot detection and CAPTCHA. Requires BRIGHTDATA_API_KEY and BRIGHTDATA_UNLOCKER_ZONE environment variables.
Install this agent skill to your Project
npx add-skill https://github.com/davila7/claude-code-templates/tree/main/cli-tool/components/skills/web-data/scrape
SKILL.md
Bright Data - Web Scraper
Scrape any webpage and get clean markdown content using Bright Data's Web Unlocker API. Automatically bypasses bot detection and CAPTCHA.
Setup
1. Get your API Key: Get a key from Bright Data Dashboard.
2. Create a Web Unlocker zone: Create a zone at brightdata.com/cp by clicking "Add" (top-right), selecting "Unlocker zone".
3. Set environment variables:
export BRIGHTDATA_API_KEY="your-api-key"
export BRIGHTDATA_UNLOCKER_ZONE="your-zone-name"
Usage
bash scripts/scrape.sh "url"
Parameters:
url(required): The webpage URL to scrape
Examples:
# Scrape a news article
bash scripts/scrape.sh "https://example.com/article"
# Scrape a product page
bash scripts/scrape.sh "https://shop.example.com/product/123"
Output Format
Returns clean markdown content extracted from the webpage:
# Page Title
Main content of the page converted to markdown format...
## Section Heading
More content...
Features
- Bot Detection Bypass: Automatically handles anti-bot measures
- CAPTCHA Solving: Bypasses CAPTCHA challenges
- Clean Markdown: Returns well-formatted markdown content
- JavaScript Rendering: Handles JavaScript-heavy pages
Dependencies
curl- For API requests
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
verl-rl-training
Provides guidance for training LLMs with reinforcement learning using verl (Volcano Engine RL). Use when implementing RLHF, GRPO, PPO, or other RL algorithms for LLM post-training at scale with flexible infrastructure backends.
openrlhf-training
High-performance RLHF framework with Ray+vLLM acceleration. Use for PPO, GRPO, RLOO, DPO training of large models (7B-70B+). Built on Ray, vLLM, ZeRO-3. 2× faster than DeepSpeedChat with distributed architecture and GPU resource sharing.
gguf-quantization
GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.
Claude Code Guide
Master guide for using Claude Code effectively. Includes configuration templates, prompting strategies "Thinking" keywords, debugging techniques, and best practices for interacting with the agent.
qdrant-vector-search
High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.
behavioral-modes
AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.
Didn't find tool you were looking for?