Manually collecting YouTube video and channel data is slow and error-prone. This skill automates structured extraction of views, likes, comments, and subscriber counts via the BrowserAct API.

Manually searching for social media profiles across multiple platforms is time-consuming and inefficient. This skill automates the process using the BrowserAct API to find profiles for individuals, brands, and businesses across Facebook, Twitter, Instagram, LinkedIn, and more.

Finding key decision-makers across industries and platforms takes hours of manual searching. This skill automates contact discovery by extracting structured profile data from social platforms through the BrowserAct API.

Manually collecting business data from Google Maps is slow and error-prone. This skill automates extraction of business names, addresses, ratings, and contact details through the BrowserAct API for fast, structured results.

Manually collecting customer reviews from Google Maps is slow and error-prone. This skill automates review extraction using the BrowserAct API, returning structured data with ratings, review text, dates, and author profiles.

Manually collecting business data from Google Maps is slow and error-prone. This skill automates the extraction of business names, addresses, phone numbers, ratings, and website URLs from Google Maps using the BrowserAct API.

Finding official websites and social media profiles for businesses is time-consuming manual work. This skill automates the process by searching company names or scraping websites to extract verified social media links and contact information.

This skill solves the problem of repetitive website data extraction and automation. It explores websites to discover API endpoints and DOM structures, then packages them into reusable, callable Skill packages for one-click execution.

Collecting Amazon product reviews manually requires building crawlers, handling captchas, and managing IP restrictions. This skill automates review extraction through BrowserAct's API, delivering structured review data from any Amazon ASIN without an Amazon account or custom scraping infrastructure.

Manually collecting structured product data from Amazon is time-consuming and error-prone. This skill automates Amazon product search data extraction through the BrowserAct API, delivering structured results without captchas or IP restrictions.

Manually collecting Amazon product data is slow and inconsistent. This skill automates structured data extraction from Amazon search results, returning titles, prices, ratings, and specifications in a clean format.

Amazon sellers struggle to understand why competitor listings outperform theirs and where market opportunities exist. This skill extracts real competitor listing data via BrowserAct API and applies a structured analysis framework to uncover content gaps, keyword opportunities, and strategic positioning insights you can act on.

Manually comparing Amazon products across multiple listings is slow and inconsistent. This skill automates competitive analysis by extracting pricing, ratings, reviews, and specifications from Amazon product pages using the BrowserAct API and generates structured comparison reports.

Amazon seller data is hard to extract due to CAPTCHAs, IP blocks, and anti-scraping measures. This skill uses the BrowserAct API to reliably retrieve buy box ownership, competitor pricing, fulfillment methods, and seller ratings for any ASIN without managing proxies or browser automation.

This skill retrieves structured Amazon product data using an ASIN number. It eliminates the need for manual browsing or custom web scraping solutions.

Managing complex data workflows across ETL processes, analytics, and feature engineering requires coordinated orchestration and quality enforcement. This skill acts as a CTO-Data role, coordinating data tasks while maintaining 95 percent minimum quality standards.

This skill provides ready-to-use SQLAlchemy 2.0+ patterns for async database operations. It includes type-safe models, CRUD operations, relationships, and performance optimizations for building robust data services.

Data analysis often requires custom Python code for specific datasets and visualization needs. This skill uses AI to generate tailored pandas and matplotlib code that processes your data and creates professional charts in sandbox environments.

Database queries require switching between code editors and terminal windows. This skill lets you execute SQL queries and psql meta-commands directly from your AI assistant without leaving your workflow.

This skill provides safe BigQuery CLI patterns for exploring tables and schemas without accessing sensitive data. It includes INFORMATION_SCHEMA queries, row count checks, and data sensitivity guidelines for responsible data analysis.