Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
- Updated SKILL.md to bump the documented version from 1.0.3 to 1.0.6. - No code or feature changes; changelog reflects documentation version update only.
What This Skill Does
Discovers and scrapes Instagram profiles in two phases: location-based discovery via Google search, then full browser simulation to collect profile data, stats, and engagement metrics. Exports results as JSON or CSV with downloaded thumbnails. Anti-detection includes browser fingerprinting and human behavior simulation.
Requires no Instagram API access or approval, using browser simulation to collect data that the official API restricts or does not expose.
When to use it
- Finding fitness influencers in specific cities for brand outreach
- Pulling follower counts and engagement rates for influencer vetting
- Building a CSV list of local food bloggers by location and category
- Collecting profile thumbnails and bios for influencer marketing reports
- Resuming large-scale scraping jobs after interruptions
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Find mid-tier fitness influencers in Miami and export their profiles
- 1Run discover --location "Miami" --category "fitness" to find matching Instagram handles via Google search
- 2Filter out private accounts, profiles under 1,000 followers, and already-scraped usernames
- 3Run scrape for each discovered handle to collect bio, follower count, post engagement, and thumbnails
- 4Export results to data/export_{timestamp}.csv
CSV file with username, follower count, influencer tier, bio, engagement stats, and local thumbnail paths for each qualifying profile
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.