Install
openclaw skills install @browseract-cli/airbnb-search-listingExtracts 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.
openclaw skills install @browseract-cli/airbnb-search-listingNavigate to Airbnb search URL → extract listing results from SSR-embedded data
All process output to user (progress updates, process notifications) follows the user's language.
Extract accommodation listing results from an Airbnb search page using SSR-embedded niobeClientData JSON.
https://www.airbnb.com/s/{destination}/homesIf 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. 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.
Navigate to the search URL first, wait for the page to load, then run:
eval "$(python scripts/search-listing.py)"
URL construction pattern:
https://www.airbnb.com/s/{destination}/homes?checkin={YYYY-MM-DD}&checkout={YYYY-MM-DD}&adults={N}&children={N}&infants={N}&pets={N}&price_min={N}&price_max={N}&min_beds={N}&min_bedrooms={N}&min_bathrooms={N}&cursor={base64_cursor}
All URL parameters are optional except destination. Omit any parameter to use the Airbnb default.
Full invocation sequence:
navigate https://www.airbnb.com/s/{destination}/homes?{params}wait stableeval "$(python scripts/search-listing.py)"Output example:
{
"items": [
{
"id": "5476930",
"url": "https://www.airbnb.com/rooms/5476930",
"name": "Bright Studio in Notting Hill",
"lat": 51.5101,
"lng": -0.1949,
"rating": "4.85",
"title": "Entire studio in London",
"price_total": "$120 total",
"price_qualifier": "before taxes",
"photos": ["https://a0.muscache.com/im/pictures/...jpeg"],
"badges": ["Guest favorite"]
}
],
"count": 18,
"total_pages": 13,
"cursors": ["eyJzZWN0aW9uX29mZnNldCI6MCwiaXRlbXNfb2Zmc2V0IjoxOCwidmVyc2lvbiI6MX0="]
}
Error handling: If error: true is returned, verify the current page is an Airbnb search results page (URL contains /s/ and /homes), then retry once after wait stable. If niobeClientData is not found, the page may still be loading — wait and retry.
URL Pagination: URL pattern https://www.airbnb.com/s/{destination}/homes?{filters}&cursor={cursor}. Each page returns a cursors array where cursors[0] is the current page, cursors[1] is page 2, cursors[2] is page 3, etc. total_pages equals the length of cursors. Termination: index >= total_pages OR count is 0.
Paginate by taking the cursor from the previous result and navigating:
cursors array from resultnavigate https://www.airbnb.com/s/{destination}/homes?{filters}&cursor={cursors[1]}wait stableeval "$(python scripts/search-listing.py)"cursors[N-1] from the original page-1 cursors arraycount >= 1 AND items[0].id is not null AND items[0].url is not null
rating may be null for new listings with no reviewsprice_total is null when no dates are specified in searchPath: {working-directory}/browser-act-skill-forge-memories/airbnb-scraper-airbnb-search-listing.memory.md
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.