ad-library-teardown
About ad-library-teardown
A marketing skill for analyzing public ads in Meta, Google, and LinkedIn libraries. It organizes competitor messaging, offers, and creative angles into practical findings and test ideas.
Key features
- 01Search ads and advertisers
- 02Extract copy, CTAs, and offers
- 03Analyze video ad transcripts
- 04Group ads by messaging angle
- 05Suggest tests from repeated patterns
Use cases
- 01Compare competitor ad messaging
- 02Collect hooks and landing-page angles
- 03Extract messaging from video ads
- 04Plan tests based on competitor ads
Install
Copy the command and run it in a terminal.
npx skills add https:/ / github.com/ scrapecreators/ social-media-research-skills --skill ad-library-teardownAfter installing, type/ad-library-teardownin Claude Code to confirm it loaded.
Details
From the project READMEAd Library Teardown
Overview
Analyze public ads to understand a competitor's messaging, offers, creative strategy, and testing angles. The output should be a practical teardown marketers can use to write better ads or decide what to test.
When to Use
Use this skill when the user asks to:
- analyze a competitor's active ads
- search Meta/Facebook, Google, or LinkedIn ad libraries
- extract ad hooks, CTAs, claims, offers, and landing page angles
- compare ad messaging across competitors
- summarize video ad transcripts
- generate ad test ideas from competitor ads
Data Sources
| Ad library | Search/list endpoint | Detail endpoint | Transcript endpoint |
|---|---|---|---|
| Meta/Facebook | /v1/facebook/adLibrary/search/ads, /v1/facebook/adLibrary/company/ads, /v1/facebook/adLibrary/search/companies | /v1/facebook/adLibrary/ad | /v1/facebook/adLibrary/ad/transcript |
/v1/google/adLibrary/advertisers/search, /v1/google/company/ads | /v1/google/ad | n/a | |
/v1/linkedin/ads/search | /v1/linkedin/ad | n/a |
Workflow
-
Find the advertiser
- Use company search endpoints when the user provides only a brand name.
- Use domain/advertiser/page IDs when available.
-
Fetch active ads
- Prefer active ads unless the user asks for historical analysis.
- Capture platform, advertiser/page, ad ID, start date, creative type, text, headline, CTA, destination URL, and source URL.
-
Fetch details for representative ads
- Enrich the ads with detail endpoints.
- For video Meta ads, fetch transcripts when available.
-
Cluster messaging Group ads by:
- pain point
- persona
- offer
- proof/social proof
- feature/benefit
- objection handled
- comparison/alternative angle
- urgency/discount
-
Extract swipeable elements
- hooks
- headlines
- primary text patterns
- CTAs
- claims
- offers
- visual/creative concepts
-
Recommend tests Suggest tests based on repeated patterns and gaps, not random ideas.
Output Format
# Ad Library Teardown: {brand}
## Summary
- Ads analyzed: {count}
- Platforms: Meta / Google / LinkedIn
- Main positioning:
- Strongest repeated offer:
## Messaging Angles
| Angle | Evidence | Example ads | Notes |
|---|---|---|---|
## Hooks and Headlines Swipe File
- "..."
- "..."
## Offers and CTAs
| Offer | CTA | Platform | Example |
|---|---|---|---|
## Video Transcript Notes
- [Ad](url): summary, hook, best quote
## What They Appear to Be Testing
1. ...
2. ...
## Recommended Tests for Us
1. ...
2. ...
3. ...
## Sources
- [Ad](url)
Common Pitfalls
- Do not claim an ad is winning just because it is active. Say it is active or repeated; performance is not public unless the endpoint returns it.
- Do not ignore repeated ads. Repetition is often a useful signal.
- Do not invent spend, conversion rate, or targeting unless public data includes it.
- Do not skip video transcripts when the user asks for hooks or messaging from video ads.