LaunchKit · 2026
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youtube-scrapper

A skill for discovering and scraping YouTube channels based on categories and locations without requiring API keys.

2
639 downloads
by @arulmozhiv

Setup & Installation

openclaw skills install @arulmozhiv/youtube-scrapper

Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:

npx clawhub install youtube-scrapper

Version History

v0.1.1Feb 26, 2026 - Version note by skill developer:

- Major documentation update: SKILL.md completely rewritten and expanded. - Clearer overview of capabilities, features, configuration, and anti-detection strategies. - Structured usage examples and JSON output samples for easy agent integration. - Enhanced description of residential proxy support with recommendations. - README.md removed (consolidated into SKILL.md).

What This Skill Does

Discovers and scrapes YouTube channel data using browser automation, no YouTube API key required. Works in two phases: finding channels via Google Search, then extracting public profile data, subscriber counts, video stats, and thumbnails. Supports resumable sessions and regional configs for 200+ cities across 6 regions.

Bypasses the YouTube Data API entirely, avoiding its daily quota limits that cap large-scale data collection at a few hundred channels.

When to use it

  • Building an influencer database by region and content category
  • Finding micro and nano influencers for brand outreach campaigns
  • Tracking subscriber counts and engagement across competitor channels
  • Auditing YouTube presence in a specific geographic market
  • Collecting channel metadata and thumbnails for marketing research

Example Workflow

Here's how your AI assistant might use this skill in practice.

INPUT

User asks: find tech YouTube channels in India and export their stats

AGENT
  1. 1Run youtube_channel_discovery.py with --categories tech --locations India to search Google and build a queue file
  2. 2Queue file is saved to data/queue/ with discovered channel handles and progress state
  3. 3Run youtube_channel_scraper.py against the queue to visit each channel page
  4. 4Scraper collects subscribers, views, video count, recent video data, and downloads profile and banner thumbnails
  5. 5Results are written as per-channel JSON files in data/output/
OUTPUT

JSON files per channel with name, subscriber count, total views, recent video titles and view counts, joined date, country, influencer tier, and local thumbnail paths

Requirements

Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.

Residential proxy credentials for large-scale scraping (optional) from providers such as Bright Data, IProyal, Storm Proxies, or NetNut