competitive-ads-extractor

Extract and analyze competitor ads from ad libraries for messaging patterns.

Updated Feb 15, 2026
One-click install
npx skills add https://github.com/AGUNTUK/Restiqa --skill competitive-ads-extractor-aguntuk
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: competitive-ads-extractor
Source: https://github.com/AGUNTUK/Restiqa/tree/main/.kilocode/skills/competitive-ads-extractor
Command: npx skills add https://github.com/AGUNTUK/Restiqa --skill competitive-ads-extractor-aguntuk

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill helps you understand what messaging, creative approaches, and problem-solving angles are working for your competitors in their ad campaigns, saving you time on market research and inspiring your own ad strategies.

Core Features & Use Cases

  • Extracts Ads: Scrapes ads from platforms like Facebook Ad Library and LinkedIn.
  • Analyzes Messaging: Identifies key problems, use cases, and value propositions highlighted in ads.
  • Identifies Patterns: Detects common successful approaches in copy and creative.
  • Use Case: You can ask this skill to extract all ads from a competitor on Facebook and analyze the primary pain points they are addressing in their marketing copy.

Quick Start

Extract all current ads from [Competitor Name] on Facebook Ad Library.

Frequently Asked Questions about competitive-ads-extractor

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze competitor ads from the Facebook Ad Library for creative inspiration?

You can analyze competitor ads by extracting them from the Facebook Ad Library and using natural language processing to categorize messaging, identify key pain points, and highlight successful creative patterns in their marketing copy.

What is competitor ad intelligence and how does it identify successful messaging patterns?

Competitor ad intelligence is the process of extracting and categorizing competitor advertisements to detect common successful approaches in copy and creative, highlighting the primary pain points and value propositions they address.

Can I extract LinkedIn ads to find the problem-solution framing my competitors are using?

Yes, you can extract LinkedIn ads to identify the specific problems, use cases, and value propositions your competitors highlight, allowing you to analyze their problem-solution framing and apply those insights to your campaigns.

Do I need ad library API access to scrape competitor advertisements for market research?

Yes, extracting competitor advertisements for market research requires access to ad library APIs or scraping capabilities to pull the ad data, followed by natural language processing to analyze the messaging and categorize the results.

What's the best way to categorize competitor ads to understand their primary pain points?

The best way to categorize competitor ads is to extract the campaign copy and apply natural language processing to analyze the messaging, which identifies and groups the primary pain points and successful patterns they address.