Agent skill · Data & Analytics

youtube-api-skill

This skill helps users automatically extract detailed video metrics and channel information from YouTube based on keyword searches using the BrowserAct API. The Agent should proactively apply this skill when users express needs such as extract specific keyword YouTube video detailed data, monitor the latest video performance of competitor channels, collect comment and like counts for videos on a specific topic, find AI agent tutorials published this week and extract metrics, evaluate total views and subscriber info for specific videos, scrape detailed metrics of marketing campaign videos, trac

browser-actgithub.com/browser-actGitHub ↗
claude-codecodexcursorships scriptsMIT
Install
npx skills add browser-act/skills --skill youtube-api-skill --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 6 KB
Bundled scripts: yes
Path: solutions/video-platforms/youtube-api-skill/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 5,160
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# YouTube API Automated Extraction Skill ## 📖 Skill Introduction This skill provides users with an automated data extraction service through BrowserAct's YouTube API template. It can directly extract structured video metrics and channel information from YouTube. By simply inputting search keywords and upload date filters, it traverses the video results list, opens each video detail page, and directly returns clean, ready-to-use data. ## ✨ Features 1. **No Hallucinations, Ensuring Stable and Accurate Data Extraction**: Pre-set workflow avoids AI-generated hallucinations. 2. **No CAPTCHA Issues**: No need to handle reCAPTCHA or other verification challenges. 3. **No IP Restrictions and Geofencing**: No need to deal with regional IP restrictions. 4. **Faster Execution Speed**: Compared to pure AI-driven browser automation solutions, task execution is faster. 5. **Extremely High Cost-Effectiveness**: Compared to AI solutions that consume a large amount of tokens, it can significantly reduce data acquisition costs. ## 🔑 API Key Guide Flow Before running, you need to check the `BROWSERACT_API_KEY` environment variable. If it is not set, do not take any other actions first. You should r

What's inside
Steps it walks through
  1. 📖 Skill Introduction
  2. ✨ Features
  3. 🔑 API Key Guide Flow
  4. 🛠️ Input Parameters
  5. 🚀 Invocation Method (Recommended)
  6. ⏳ Execution Status Monitoring
  7. 📊 Data Output Description
  8. ⚠️ Error Handling & Retry
  9. 🌟 Typical Use Cases
Ships with 1 file
  • scripts/youtube_api.py
Commands it runs
Invocation example
python -u ./scripts/youtube_api.py "keywords" "upload_date"
More from skills
All skills →
About this skill
What does the youtube-api-skill skill do?

This skill helps users automatically extract detailed video metrics and channel information from YouTube based on keyword searches using the BrowserAct API. The Agent should proactively apply this skill when users express needs such as extract specific keyword YouTube video detailed data, monitor the latest video performance of competitor channels, collect comment and like counts for videos on a specific topic, find AI agent tutorials published this week and extract metrics, evaluate total views and subscriber info for specific videos, scrape detailed metrics of marketing campaign videos, trac

How do I install it?

Run `npx skills add browser-act/skills --skill youtube-api-skill --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From browser-act/skills, a repository with 5,160 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going