Ad Intelligence Skill

A two-phase competitive ad intelligence skill for marketing companies and ecommerce owners to research how competitors run ads across Meta, Google, and LinkedIn.

Quick Reference: What Data Is Available

⚠️ No platform exposes: exact spend, CTR, conversion rates, ROAS, or detailed audience targeting.

Workflow

Step 1: Understand the Request

Gather from the user (ask if not provided):

• Competitor name or domain (e.g., "Nike" or "nike.com")
• Target platform(s): Meta / Google / LinkedIn (default: all three)
• Phase: Phase 1 (quick, no API keys) or Phase 2 (deeper, requires API keys)
• Country/region filter (optional, e.g., "US", "IN", "EU")
• Date range (optional, e.g., "last 30 days")
• Ad format filter (optional: image / video / carousel / text)

If the user hasn't said which phase they want, ask. If they're just exploring, start with Phase 1.

Step 2: Execute the Right Phase

Read the platform reference files for code, endpoints, and examples:

• Meta: references/meta.md
• Google: references/google.md
• LinkedIn: references/linkedin.md

Each reference contains:

• Phase 1: Python scraping code (no API key needed)
• Phase 2a: Official/free API instructions
• Phase 2b: Third-party paid API options (SerpAPI, SearchAPI, Adyntel, Apify)
• Sample output JSON
• Known limitations

Step 3: Format the Output

Always deliver both:

A. Human-Readable Summary Report

## Ad Intelligence Report: [Company Name]
**Platforms Searched:** Meta, Google, LinkedIn
**Date:** [today]
**Phase:** 1 (Scrape) / 2 (API)
**Country:** [region]

### 📊 Overview
- Total ads found: X
- Active ads: X | Inactive: X
- Formats: X% image, X% video, X% carousel

### 🎯 Platform Breakdown
[Per platform: count, date range, notable trends]

### ✍️ Creative Themes & Messaging Patterns
[Summarize recurring hooks, CTAs, offers, tone]