ReddRadar
Agent skill
data-feeds
Extract structured data from 40+ websites including Amazon, LinkedIn, Instagram, TikTok, Facebook, YouTube, and more. Uses Bright Data's Web Data APIs with automatic polling. Returns clean JSON with product details, profiles, reviews, posts, and comments.
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/data-feeds
SKILL.md
Bright Data - Structured Data Feeds
Extract structured data from major websites with automatic parsing. No scraping logic needed - just provide a URL and get clean JSON data.
Setup
Environment Variables (Required)
export BRIGHTDATA_API_KEY="your-api-key"
Optional
export BRIGHTDATA_POLLING_TIMEOUT=600 # Max seconds to wait (default: 600)
Get your API key from Bright Data Dashboard.
Usage
bash scripts/datasets.sh <dataset_type> <url> [additional_params...]
Available Datasets
E-Commerce
| Dataset | Command | Description |
|---|---|---|
| Amazon Product | datasets.sh amazon_product <url> |
Product details, pricing, ratings |
| Amazon Reviews | datasets.sh amazon_product_reviews <url> |
Customer reviews for a product |
| Amazon Search | datasets.sh amazon_product_search <keyword> <domain_url> |
Search results |
| Walmart Product | datasets.sh walmart_product <url> |
Product details from Walmart |
| Walmart Seller | datasets.sh walmart_seller <url> |
Seller information |
| eBay Product | datasets.sh ebay_product <url> |
eBay listing details |
| Home Depot | datasets.sh homedepot_products <url> |
Home Depot product data |
| Zara | datasets.sh zara_products <url> |
Zara product details |
| Etsy | datasets.sh etsy_products <url> |
Etsy listing data |
| Best Buy | datasets.sh bestbuy_products <url> |
Best Buy product info |
Professional Networks
| Dataset | Command | Description |
|---|---|---|
| LinkedIn Person | datasets.sh linkedin_person_profile <url> |
Profile data (experience, skills) |
| LinkedIn Company | datasets.sh linkedin_company_profile <url> |
Company page data |
| LinkedIn Jobs | datasets.sh linkedin_job_listings <url> |
Job posting details |
| LinkedIn Posts | datasets.sh linkedin_posts <url> |
Post content and engagement |
| LinkedIn Search | datasets.sh linkedin_people_search <url> <first> <last> |
Find people |
| Crunchbase | datasets.sh crunchbase_company <url> |
Company funding, employees |
| ZoomInfo | datasets.sh zoominfo_company_profile <url> |
Company profile data |
| Dataset | Command | Description |
|---|---|---|
| Profiles | datasets.sh instagram_profiles <url> |
Bio, followers, following |
| Posts | datasets.sh instagram_posts <url> |
Post details, likes, captions |
| Reels | datasets.sh instagram_reels <url> |
Reel data and metrics |
| Comments | datasets.sh instagram_comments <url> |
Post comments |
| Dataset | Command | Description |
|---|---|---|
| Posts | datasets.sh facebook_posts <url> |
Post content and reactions |
| Marketplace | datasets.sh facebook_marketplace_listings <url> |
Listing details |
| Reviews | datasets.sh facebook_company_reviews <url> [num] |
Company reviews |
| Events | datasets.sh facebook_events <url> |
Event details |
TikTok
| Dataset | Command | Description |
|---|---|---|
| Profiles | datasets.sh tiktok_profiles <url> |
Creator profile data |
| Posts | datasets.sh tiktok_posts <url> |
Video details and metrics |
| Shop | datasets.sh tiktok_shop <url> |
TikTok Shop product data |
| Comments | datasets.sh tiktok_comments <url> |
Video comments |
YouTube
| Dataset | Command | Description |
|---|---|---|
| Profiles | datasets.sh youtube_profiles <url> |
Channel data |
| Videos | datasets.sh youtube_videos <url> |
Video details and stats |
| Comments | datasets.sh youtube_comments <url> [num] |
Video comments (default: 10) |
Other Social
| Dataset | Command | Description |
|---|---|---|
| X (Twitter) | datasets.sh x_posts <url> |
Tweet data |
datasets.sh reddit_posts <url> |
Post and comment data |
Google Services
| Dataset | Command | Description |
|---|---|---|
| Maps Reviews | datasets.sh google_maps_reviews <url> [days] |
Business reviews (default: 3 days) |
| Shopping | datasets.sh google_shopping <url> |
Product comparison data |
| Play Store | datasets.sh google_play_store <url> |
App details and reviews |
Other
| Dataset | Command | Description |
|---|---|---|
| Apple App Store | datasets.sh apple_app_store <url> |
iOS app data |
| Reuters News | datasets.sh reuter_news <url> |
News article content |
| GitHub | datasets.sh github_repository_file <url> |
Repository file data |
| Yahoo Finance | datasets.sh yahoo_finance_business <url> |
Stock and company data |
| Zillow | datasets.sh zillow_properties_listing <url> |
Property listing details |
| Booking.com | datasets.sh booking_hotel_listings <url> |
Hotel listing data |
Examples
Get LinkedIn Profile
bash scripts/datasets.sh linkedin_person_profile "https://www.linkedin.com/in/satyanadella/"
Get Amazon Product
bash scripts/datasets.sh amazon_product "https://www.amazon.com/dp/B09V3KXJPB"
Get Instagram Profile
bash scripts/datasets.sh instagram_profiles "https://www.instagram.com/natgeo/"
Get YouTube Comments
bash scripts/datasets.sh youtube_comments "https://www.youtube.com/watch?v=dQw4w9WgXcQ" 20
Search Amazon
bash scripts/datasets.sh amazon_product_search "wireless headphones" "https://www.amazon.com"
Output Format
Returns structured JSON with website-specific fields. Example for LinkedIn profile:
{
"name": "Satya Nadella",
"headline": "Chairman and CEO at Microsoft",
"location": "Greater Seattle Area",
"connections": "500+",
"experience": [...],
"education": [...],
"skills": [...]
}
How It Works
- Trigger: Sends URL to Bright Data's Web Data API
- Poll: Waits for data collection to complete (checks every second)
- Return: Outputs structured JSON when ready
The polling mechanism handles rate limits and ensures data quality by waiting for full extraction.
Advanced: Direct Fetch
For custom dataset IDs or advanced use cases:
bash scripts/fetch.sh <dataset_id> '<json_input>'
Example:
bash scripts/fetch.sh gd_l1viktl72bvl7bjuj0 '{"url":"https://linkedin.com/in/someone"}'
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
davila7/claude-code-templates
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.
davila7/claude-code-templates
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.
davila7/claude-code-templates
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.
davila7/claude-code-templates
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.
davila7/claude-code-templates
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.
davila7/claude-code-templates
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?