A comprehensive browser-based tool for discovering and scraping TikTok profile data, engagement metrics, and thumbnails without API keys.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install tiktok-scraper-2
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install tiktok-scraper-2 using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The TikTok Profile Scraper is a production-ready skill designed for the Openclaw Skills ecosystem, enabling developers and marketers to gather rich social media intelligence. It utilizes Python and Playwright to simulate human browsing behavior, bypassing the need for official API keys while ensuring high data accuracy. By combining advanced browser fingerprinting with stealth scripts, this skill provides a robust solution for extracting profile details, follower counts, and content thumbnails.
This tool is particularly valuable for those looking to scale their influencer research or market analysis within the Openclaw Skills framework. It offers a two-phase workflow that first discovers potential targets based on geographical location and category, then systematically scrapes detailed metrics, making it an essential asset for data-driven social media strategies.
Ensure you have Python 3 and Chromium installed on your system.
# Navigate to your agent's skill directory
# Install dependencies
pip install -r requirements.txt
playwright install chromium
# Discover profiles by location and category
discover --location "Miami" --category "dance" --output json
# Scrape a specific profile
scrape --username charlidamelio --output json
| Field | Type | Description |
|---|---|---|
| username | String | The unique TikTok handle |
| followers | Integer | Total count of followers |
| bio | String | The profile's biography text |
| influencer_tier | String | Categorization (nano, micro, mid, macro, mega) |
| profile_pic_local | String | Local path to the downloaded profile image |
| video_views | Array | View counts and display strings for recent content |
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