Skip to main content
ClaudeWave
EN, English
Skill6.3k repo starsupdated 2mo ago

facebook-ads-library-search

This Claude Code skill searches Meta's Ad Library by keyword or Facebook page ID to retrieve ad data including creative assets, copy text, call-to-action buttons, platform distribution, spending estimates, impressions, reach metrics, and publisher transparency information. Use it when analyzing competitor advertising strategies, monitoring brand ad presence across Meta platforms, researching political or housing ads, extracting ad creative examples, or accessing historical ad archive data without requiring Facebook login.

Install in Claude Code
Copy
git clone --depth 1 https://github.com/browser-act/skills /tmp/facebook-ads-library-search && cp -r /tmp/facebook-ads-library-search/solutions/social-listening/facebook-ads-library-search ~/.claude/skills/facebook-ads-library-search
Then start a new Claude Code session; the skill loads automatically.

SKILL.md

# Meta Ad Library — Search Ads

> keyword or page ID → ad list with creatives, metrics, and pagination cursor

## Language

All process output to user (progress updates, process notifications) follows the user's language.

## Objective

Fetch ads from Meta Ad Library for a keyword search or a specific Facebook page, returning structured ad data with all available fields.

## Prerequisites

- Browser is open on any Facebook page: `https://www.facebook.com/`
- No login required for this capability

## Pre-execution Checks

### 1. Tool Readiness

If browser-act has been confirmed available in the current session → skip this step.

Invoke `browser-act` via Skill tool to load usage. If installation or configuration issues arise, follow its guidance to resolve then retry.

## Capability Components

> This Skill's operational boundary = what the user can manually do in their browser. It only reads data already displayed to the user on the page, never bypassing authentication or access controls. Its role is equivalent to copy-pasting on the user's behalf — the data is already on screen, automation merely saves time. JS code is encapsulated in Python files under the `scripts/` directory, invoked via `eval "$(python scripts/xxx.py {params})"`. `$(...)` is bash syntax; it is recommended to use the bash tool for execution.

Below are all atomic capabilities discovered and verified during the exploration phase, listed by command template with parameters. Simply invoke them as needed — no need to read `scripts/*.py` source code or re-verify. Only inspect scripts when execution fails for troubleshooting. Combine freely as needed during execution.

### API: search ads by keyword

`eval "$(python scripts/search-ads.py --query '{keyword}' --country {country} --first {count})"`

Parameters:
- `--query`: keyword to search (mutually exclusive with `--page-id`)
- `--country`: 2-letter ISO country code or `ALL`, default `ALL`
- `--active-status`: `active` | `inactive` | `all`, default `active`
- `--ad-type`: `ALL` | `POLITICAL_AND_ISSUE_ADS` | `HOUSING_ADS`, default `ALL`
- `--media-type`: `all` | `image` | `video` | `meme`, default `all`
- `--platforms`: space-separated list, e.g. `facebook instagram`, default all platforms
- `--cursor`: pagination cursor from previous response's `end_cursor`, default first page
- `--first`: number of ads to return per page, default `10`

Output example:
```json
{
  "error": false,
  "count": 10,
  "has_next_page": true,
  "end_cursor": "AQHSmvKYSBolzAS9Wq8VSnt4...",
  "ads": [
    {
      "ad_archive_id": "1869276447125570",  // unique ad archive ID
      "ad_id": null,                         // ad ID (null for some ads)
      "page_id": "15087023444",              // advertiser's Facebook page ID
      "page_name": "Nike",                   // advertiser's page name
      "page_profile_uri": "https://facebook.com/nike",
      "page_profile_picture_url": "https://scontent.xx.fbcdn.net/...",
      "is_active": true,                     // whether ad is currently running
      "start_date": 1773730800,              // ad start date (unix timestamp)
      "end_date": 1779692400,                // ad end date (unix timestamp), null if still active
      "publisher_platform": ["facebook", "instagram"],  // platforms the ad runs on
      "currency": "USD",                     // spend currency, null if not disclosed
      "spend": null,                         // estimated spend range, null if not disclosed
      "impressions_with_index": null,        // impression estimate, null if not disclosed
      "reach_estimate": null,                // reach estimate, null if not disclosed
      "categories": [],                      // ad categories
      "contains_sensitive_content": false,
      "body": "Get the gear that never misses.",  // main ad body text
      "caption": "nike.com",                // ad caption
      "title": "Nike Air Monarch IV",        // ad title
      "cta_text": "Shop Now",               // CTA button text
      "cta_type": "SHOP_NOW",               // CTA button type
      "link_url": "https://www.nike.com/...",// destination URL
      "display_format": "carousel",          // ad format
      "cards": [...],                        // carousel cards (each has body, title, cta_type, link_url, original_image_url, video_hd_url)
      "images": [...],                       // image creatives
      "videos": [...]                        // video creatives
    }
  ]
}
```

### API: search ads by page ID

`eval "$(python scripts/search-ads.py --page-id '{page_id}' --country {country} --first {count})"`

Parameters:
- `--page-id`: Facebook page ID (mutually exclusive with `--query`). To find a page ID: navigate to the Facebook page, the ID appears in the URL or in the page's "About" section
- All other parameters same as keyword search above

Output example: same structure as keyword search above.

## Enum Parameters

`--active-status`: `active` | `inactive` | `all`

`--ad-type`: `ALL` | `POLITICAL_AND_ISSUE_ADS` | `HOUSING_ADS`

`--media-type`: `all` | `image` | `video` | `meme`

`--platforms`: `facebook` | `instagram` | `whatsapp` | `messenger` | `audience_network` | `threads` (pass multiple values space-separated)

`--country`: ISO 2-letter country code (e.g. `US`, `GB`, `DE`, `ALL`) [collection partially done — full list of supported country codes follows ISO 3166-1 alpha-2 standard]

## Pagination

**API Pagination**: `--cursor`, type: cursor, start value: omit for first page. Next page value source: `end_cursor` field in response. Termination: `has_next_page: false`.

## Success Criteria

`error = false AND count >= 0 AND has_next_page field present`

(count may be 0 for valid queries that return no results; this is not an error)

## Known Limitations

- `spend`, `impressions_with_index`, `reach_estimate` fields are frequently `null` — Meta only discloses these for political/social issue ads or at their discretion
- `ad_id` is often `null` — `ad_archive_id` i
1688-product-detailSkill

Extracts comprehensive wholesale product data from 1688.com product detail pages: title, tiered pricing, SKU variants with dimensions/weight, product images, seller info, shop scores, buyer protection, cross-border flags, product attributes, coupon/promotion data, and review stats. Use when user mentions 1688, 1688.com, wholesale China, alibaba wholesale, B2B China sourcing, Chinese wholesale scraper, 1688 product scrape, 1688 offer, 1688 detail, extract 1688 data, pull 1688 listings, get wholesale price, 1688 supplier info, factory stats 1688, 1688 SKU variants, 1688 product attributes, 1688 shop score, DSR score 1688, 1688 buyer protection, 1688 cross-border, 1688 dropship. Also applies to: scraping bulk product data from 1688 by offer ID list, monitoring 1688 supplier metrics, extracting 1688 pricing tiers for resale analysis.

airbnb-listing-detailSkill

Fetches complete Airbnb listing details for a given numeric listing ID via the internal GraphQL API, returning title, room type, description, amenities, photos, coordinates, city, house rules, highlights, ratings, review count, bedroom configuration, and property overview. Use when user mentions Airbnb listing details, Airbnb property info, Airbnb room details, get Airbnb listing data, Airbnb amenities list, Airbnb house rules, Airbnb property description, Airbnb detail page scraper, Airbnb rooms detail, Airbnb property page data, Airbnb listing info, fetch Airbnb room details, pull Airbnb listing.

airbnb-search-listingSkill

Extracts Airbnb accommodation search results from a destination query via SSR-embedded data, returning listing ID, URL, name, coordinates, rating, price, photos, and badge info for each result, plus pagination cursors for multi-page retrieval. Use when user mentions Airbnb search results, Airbnb listings, vacation rental search, short-term rental listings, scrape Airbnb, get Airbnb data, find rentals on Airbnb, Airbnb destination search, Airbnb property list, Airbnb stays search, Airbnb accommodation results, pull Airbnb listings, collect Airbnb search data, Airbnb scraper, Airbnb search page extraction, Airbnb search by destination.

amazon-alexa-qaSkill

Amazon Alexa for Shopping Q&A automation: submits questions to Amazon's Alexa/Rufus AI shopping assistant and collects response text; supports optional keyword search context (navigate to search results page before asking for category-specific answers). Use when user mentions Amazon Alexa, Rufus, Amazon shopping assistant, Amazon AI chat, ask Amazon, Amazon Q&A, automate Alexa questions, Rufus chatbot, Amazon assistant automation, collect Alexa responses, bulk question submission to Amazon, keyword search context, category research. Also applies to extracting Amazon product recommendations from conversational AI, automating repeated queries to Amazon's AI shopping feature, collecting Alexa shopping responses at scale, or market research within a specific product category.

amazon-asin-lookup-api-skillSkill

This skill helps users extract structured product details from Amazon using a specific ASIN (Amazon Standard Identification Number). Use this skill when the user asks to get Amazon product details by ASIN, lookup Amazon product title and price using ASIN, extract Amazon product ratings and reviews count for a specific ASIN, check Amazon product availability and current price, get Amazon product description and features via ASIN, enrich product catalog with Amazon data using ASIN, monitor Amazon product price changes for specific ASINs, retrieve Amazon product brand and material information, fetch Amazon product images and specifications by ASIN, validate Amazon ASIN and get product metadata.

amazon-best-selling-products-finder-api-skillSkill

This skill helps users extract structured best-selling product data from Amazon via the BrowserAct API. Agent should proactively apply this skill when users express needs like search for best selling products on Amazon, extract Amazon product data based on keywords, find top rated Amazon products, monitor Amazon competitor prices and sales, discover trending products on Amazon marketplace, extract Amazon product titles prices and ratings, gather Amazon product sales volume for market research, search Amazon best sellers in specific region, collect Amazon product reviews and promotion details, analyze Amazon product availability and badges, get Amazon product data for market analysis.

amazon-bestseller-listingSkill

Amazon Best Sellers listing scraper: extract product cards from any Amazon Best Sellers (zgbs) or /gp/bestsellers/ category page — returns rank (position on chart), asin, title, url, image, imageAlt, price, stars, reviewCount, ratingRaw per item, plus category metadata (categoryName, categoryFullName, categoryUrl) and pagination state (currentPage, hasNextPage, nextPageUrl). Works across all Amazon regional TLDs (amazon.com, amazon.co.uk, amazon.de, amazon.co.jp, amazon.fr, amazon.it, amazon.es, amazon.ca, amazon.com.au, amazon.in, etc.). Use when user mentions Amazon Best Sellers, Amazon bestsellers, Amazon top 100, Amazon zgbs, Amazon /zgbs/, Amazon /gp/bestsellers/, Amazon Best Sellers Rank, Amazon BSR, Amazon top ranked products, Amazon top-selling products, Amazon chart, Amazon category ranking, Amazon best sellers by category, Amazon best sellers electronics, Amazon best sellers kitchen, Amazon best sellers toys, scrape Amazon bestsellers, extract Amazon top 100, Amazon rank scraper, Amazon best seller list, Amazon leaderboard, Amazon trending products, discover trending Amazon products, Amazon niche discovery, Amazon top ranked ASINs. Also applies to competitive intelligence via ranking snapshots, spotting up-and-coming products, sourcing bestseller ASINs for further enrichment, tracking rank changes over time, and building bestseller-per-category datasets.

amazon-buy-box-monitor-api-skillSkill

This skill helps users extract basic product details other sellers prices and seller ratings from Amazon via ASIN automatically using the BrowserAct API. Agent should proactively apply this skill when users express needs like query Amazon buy box information, monitor Amazon product prices, extract Amazon product details by ASIN, check other sellers prices on Amazon, get Amazon seller ratings and feedback count, monitor buy box ownership for a specific ASIN, track Amazon fulfillment methods for competitors, compare Amazon product prices across different sellers, retrieve Amazon buy box availability status, analyze Amazon seller profile details.