Install
openclaw skills install @browseract-cli/facebook-ads-library-searchSearches Meta Ad Library (Facebook/Instagram/WhatsApp ads) by keyword or Facebook page ID and extracts ad details including creatives, copy, CTA, publisher platforms, spend, impressions, reach estimates, and page transparency info. Use when user mentions Meta Ad Library, Facebook ads scraper, Instagram ads data, FB ad library, search Facebook ads, get ads from a Facebook page, scrape Meta ads, Facebook advertising data, ad creative extraction, competitor ads analysis, brand ads monitoring, Meta advertising transparency, political ads Facebook, housing ads Facebook, view all ads from a page, facebook ads search, fb ads library api, facebook ad archive, instagram ad data, get ad creatives.
openclaw skills install @browseract-cli/facebook-ads-library-searchkeyword or page ID → ad list with creatives, metrics, and pagination cursor
All process output to user (progress updates, process notifications) follows the user's language.
Fetch ads from Meta Ad Library for a keyword search or a specific Facebook page, returning structured ad data with all available fields.
https://www.facebook.com/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.
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 viaeval "$(python scripts/xxx.py {params})".$(...)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.
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 10Output example:
{
"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
}
]
}
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" sectionOutput example: same structure as keyword search above.
--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]
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.
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)
spend, impressions_with_index, reach_estimate fields are frequently null — Meta only discloses these for political/social issue ads or at their discretionad_id is often null — ad_archive_id is the reliable unique identifierdoc_id (27201872659451053) is a compiled query ID that may change when Meta updates their frontend; if errors occur, re-explore to find the updated IDPath: {working-directory}/browser-act-skill-forge-memories/facebook-ads-scraper-facebook-ads-library-search.memory.md (working directory is determined by the Agent running the Skill, typically the project root or current working directory)
Before execution: If the file exists, read it first — it records unexpected situations encountered during past executions (e.g., a strategy has become ineffective); adjust strategy order accordingly.
After execution: If an unexpected situation is encountered (strategy became ineffective, page redesigned, anti-scraping upgraded, better path discovered), append a line:
{YYYY-MM-DD}: {what happened} -> {conclusion}
Normal execution does not write to the file. Do not record what keywords were used or how many results were returned — those are task outputs, not experience.