ScrapeCreators/social-media-research-skills

What it solves

This project provides a library of pre-built research workflows for AI agents to analyze social media data. Instead of manually scraping or searching, you can instruct your agent to perform complex tasks like identifying viral content patterns, mining audience comments for product feedback, or tearing down competitor ad strategies across platforms like TikTok, Instagram, YouTube, Reddit, and X.

How it works

The project uses the Agent Skills specification to give your AI agent a set of specialized tools. You install the skills into your agent environment (such as Claude Code or Cursor) and provide a ScrapeCreators API key. When you give the agent a prompt, it selects the appropriate skill—such as transcript-intelligence or ad-library-teardown—to fetch public data and process it into actionable business artifacts like reports, CSVs, or content strategy recommendations.

Who it’s for

This is designed for developers and power users who want to automate social media research and competitive intelligence using AI agents. It is ideal for those who need to turn raw social data into structured insights without building custom data pipelines from scratch.

Highlights

• Workflow-focused: Designed to deliver business outcomes like "competitor briefs" rather than just raw data.
• Broad Platform Support: Works across major social networks including TikTok, Instagram, YouTube, Reddit, X, LinkedIn, Facebook, and more.
• Actionable Outputs: Generates useful artifacts like content pillars, prospect lists, and exact audience language quotes.
• Baseline-Aware: Analyzes performance relative to a creator's typical output rather than just raw view counts.
• Compatible: Integrates with popular agent environments like Cursor, Claude Code, GitHub Copilot, and VS Code.