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Get Started Free →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.
.claude/skills/davila7-data-feeds/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 65% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 34% | 0% |
| case-04 | ✗→✓ | ▲ Improved | -12% | 0% |
| case-05 | ✗→✓ | ▲ Improved | -35% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 319% | 0% |
Extract structured data from major websites with automatic parsing. No scraping logic needed - just provide a URL and get clean JSON data.
bashexport BRIGHTDATA_API_KEY="your-api-key"
bashexport BRIGHTDATA_POLLING_TIMEOUT=600 # Max seconds to wait (default: 600)
Get your API key from Bright Data Dashboard.
bashbash scripts/datasets.sh <dataset_type> <url> [additional_params...]
| 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 |
| 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 |
| 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 |
| 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) |
| Dataset | Command | Description | |---------|---------|-------------| | X (Twitter) | datasets.sh x_posts <url> | Tweet data | | Reddit | datasets.sh reddit_posts <url> | Post and comment data |
| 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 |
| 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 |
bashbash scripts/datasets.sh linkedin_person_profile "https://www.linkedin.com/in/satyanadella/"
bashbash scripts/datasets.sh amazon_product "https://www.amazon.com/dp/B09V3KXJPB"
bashbash scripts/datasets.sh instagram_profiles "https://www.instagram.com/natgeo/"
bashbash scripts/datasets.sh youtube_comments "https://www.youtube.com/watch?v=dQw4w9WgXcQ" 20
bashbash scripts/datasets.sh amazon_product_search "wireless headphones" "https://www.amazon.com"
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": [...] }
The polling mechanism handles rate limits and ensures data quality by waiting for full extraction.
For custom dataset IDs or advanced use cases:
bashbash scripts/fetch.sh <dataset_id> '<json_input>'
Example:
bashbash scripts/fetch.sh gd_l1viktl72bvl7bjuj0 '{"url":"https://linkedin.com/in/someone"}'
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-22 | pass→pass | 11,731 | 5,824 | -50% | 1 | 1 | 0% | 2,015 | 2,656 | +32% | 0 | 0 | — |
case-01 | fail→pass | 6,222 | 4,402 | -29% | 1 | 1 | 0% | 1,165 | 1,921 | +65% | 0 | 0 | — |
case-02 | fail→fail | 11,073 | 6,036 | -45% | 1 | 1 | 0% | 2,361 | 1,907 | -19% | 0 | 0 | — |
case-03 | fail→pass | 6,794 | 4,804 | -29% | 1 | 1 | 0% | 1,444 | 1,937 | +34% | 0 | 0 | — |
case-04 | fail→pass | 11,280 | 1,850 | -84% | 1 | 1 | 0% | 2,268 | 2,001 | -12% | 0 | 0 | — |
case-05 | fail→pass | 15,038 | 1,418 | -91% | 1 | 1 | 0% | 2,980 | 1,935 | -35% | 0 | 0 | — |
case-06 | fail→pass | 3,971 | 6,472 | +63% | 1 | 1 | 0% | 663 | 2,775 | +319% | 0 | 0 | — |
case-07 | fail→pass | 3,560 | 1,755 | -51% | 1 | 1 | 0% | 525 | 1,949 | +271% | 0 | 0 | — |
case-08 | fail→pass | 5,647 | 1,529 | -73% | 1 | 1 | 0% | 852 | 1,925 | +126% | 0 | 0 | — |
case-09 | fail→pass | 2,329 | 1,473 | -37% | 1 | 1 | 0% | 344 | 1,865 | +442% | 0 | 0 | — |
case-10 | fail→pass | 8,845 | 1,790 | -80% | 1 | 1 | 0% | 1,971 | 1,998 | +1% | 0 | 0 | — |
case-11 | fail→pass | 4,477 | 2,080 | -54% | 1 | 1 | 0% | 828 | 1,864 | +125% | 0 | 0 | — |
case-12 | fail→pass | 13,006 | 2,611 | -80% | 1 | 1 | 0% | 2,202 | 2,145 | -3% | 0 | 0 | — |
case-13 | fail→pass | 4,445 | 1,778 | -60% | 1 | 1 | 0% | 619 | 1,888 | +205% | 0 | 0 | — |
case-14 | fail→pass | 3,019 | 4,331 | +43% | 1 | 1 | 0% | 477 | 1,881 | +294% | 0 | 0 | — |
case-15 | fail→pass | 5,926 | 1,447 | -76% | 1 | 1 | 0% | 1,336 | 1,888 | +41% | 0 | 0 | — |
case-16 | fail→fail | 10,130 | 4,752 | -53% | 1 | 1 | 0% | 1,712 | 1,907 | +11% | 0 | 0 | — |
case-17 | fail→pass | 8,264 | 4,108 | -50% | 1 | 1 | 0% | 1,255 | 1,909 | +52% | 0 | 0 | — |
case-18 | fail→fail | 7,406 | 5,408 | -27% | 1 | 1 | 0% | 1,477 | 1,894 | +28% | 0 | 0 | — |
case-19 | fail→pass | 3,985 | 2,465 | -38% | 1 | 1 | 0% | 632 | 2,009 | +218% | 0 | 0 | — |
case-20 | pass→pass | 11,416 | 8,772 | -23% | 1 | 1 | 0% | 2,204 | 3,337 | +51% | 0 | 0 | — |
case-21 | pass→pass | 8,928 | 5,505 | -38% | 1 | 1 | 0% | 1,704 | 2,654 | +56% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 19 counted toward the lift figure. The other 3 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +73 percentage points is the difference between those two pass rates over the 19 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.