Install
openclaw skills install @browseract-cli/instagram-place-postsScrapes Instagram posts tagged at a specific location or place, returning media items with captions, like/comment counts, media URLs and user info. Use when user mentions Instagram location posts, posts from a place on Instagram, Instagram geotag scraping, posts tagged at location, Instagram place feed, get posts from a venue on Instagram, Instagram location data, posts near me Instagram, place-based Instagram content, tagged location posts.
openclaw skills install @browseract-cli/instagram-place-postslocation name/ID → paginated list of posts tagged at that location
All process output to user (progress updates, process notifications) follows the user's language.
Search for a location by name, then fetch posts tagged at that location using the internal locations sections API with cursor-based pagination.
https://www.instagram.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.
If login status for Instagram has been confirmed in the current session → skip this step.
Otherwise: open https://www.instagram.com/ and observe the page login status:
User refuses or cannot log in → terminate execution.
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 "$(python scripts/search-location.py '{keyword}')"
Parameters:
New York, Eiffel Tower, Times Square)Output example:
{
"venues": [
{
"id": "212988663",
"name": "New York, New York",
"address": "New York, NY",
"lat": 40.7128,
"lng": -74.0059
}
]
}
eval "$(python scripts/get-place-posts.py '{location_id}' --tab ranked --max-id '{cursor}' --session-id '{session_id}')"
Parameters:
ranked (top posts, default) or recent (chronological)next_max_id from previous response for subsequent pagessession-001)Output example:
{
"items": [
{
"pk": "3904677093853259503",
"code": "DYwMyEFumbv",
"media_type": 2,
"taken_at": 1779686199,
"like_count": 1203,
"comment_count": 48,
"caption": "NYC skyline at sunset 🌆",
"thumbnail_url": "https://scontent.cdninstagram.com/...",
"video_url": "https://scontent.cdninstagram.com/...",
"username": "nyc_photos",
"user_id": "330873185",
"location_name": "New York, New York"
}
],
"more_available": true,
"next_max_id": "32120594f3584430b0d3a4e72372c376"
}
navigate https://www.instagram.com/ → wait stableeval "$(python scripts/search-location.py '{location_name}')" → select the best-matching venue, extract its id as location_ideval "$(python scripts/get-place-posts.py '{location_id}' --session-id 'session-001')" → collect items, note more_available and next_max_idmore_available is true:
a. eval "$(python scripts/get-place-posts.py '{location_id}' --max-id '{next_max_id}' --session-id 'session-001')" → accumulate itemsAPI Pagination: max_id, type: cursor, start value: empty string. Next page value source: next_max_id field in response. Termination: more_available is false or next_max_id is null. Keep session_id consistent across all pages for the same scraping session.
result count >= 1 AND items[0].pk non-null AND items[0].location_name non-null
Path: {working-directory}/browser-act-skill-forge-memories/instagram-scraper-instagram-place-posts.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.