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.

24,269 stars

Best use case

data-feeds is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

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.

Teams using data-feeds should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/data-feeds/SKILL.md --create-dirs "https://raw.githubusercontent.com/davila7/claude-code-templates/main/cli-tool/components/skills/web-data/data-feeds/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/data-feeds/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How data-feeds Compares

Feature / Agentdata-feedsStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# 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)
```bash
export BRIGHTDATA_API_KEY="your-api-key"
```

### Optional
```bash
export BRIGHTDATA_POLLING_TIMEOUT=600  # Max seconds to wait (default: 600)
```

Get your API key from [Bright Data Dashboard](https://brightdata.com/cp).

## Usage

```bash
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 |

### Instagram

| 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 |

### Facebook

| 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 |
| Reddit | `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
bash scripts/datasets.sh linkedin_person_profile "https://www.linkedin.com/in/satyanadella/"
```

### Get Amazon Product
```bash
bash scripts/datasets.sh amazon_product "https://www.amazon.com/dp/B09V3KXJPB"
```

### Get Instagram Profile
```bash
bash scripts/datasets.sh instagram_profiles "https://www.instagram.com/natgeo/"
```

### Get YouTube Comments
```bash
bash scripts/datasets.sh youtube_comments "https://www.youtube.com/watch?v=dQw4w9WgXcQ" 20
```

### Search Amazon
```bash
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:

```json
{
  "name": "Satya Nadella",
  "headline": "Chairman and CEO at Microsoft",
  "location": "Greater Seattle Area",
  "connections": "500+",
  "experience": [...],
  "education": [...],
  "skills": [...]
}
```

## How It Works

1. **Trigger**: Sends URL to Bright Data's Web Data API
2. **Poll**: Waits for data collection to complete (checks every second)
3. **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
bash scripts/fetch.sh <dataset_id> '<json_input>'
```

Example:
```bash
bash scripts/fetch.sh gd_l1viktl72bvl7bjuj0 '{"url":"https://linkedin.com/in/someone"}'
```

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