competitive-ads-extractor

composiohq/awesome-claude-skills · updated Apr 8, 2026

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$npx skills add https://github.com/composiohq/awesome-claude-skills --skill competitive-ads-extractor
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summary

Extract and analyze competitors' ads from ad libraries to identify successful messaging, creative patterns, and positioning strategies.

  • Scrapes ads from Facebook Ad Library, LinkedIn, and other platforms, capturing screenshots and analyzing messaging themes, pain points, and value propositions
  • Identifies patterns in successful ads by categorizing them by theme, audience, and format, then explains why certain approaches likely perform well
  • Supports competitive set analysis across mult
skill.md

Competitive Ads Extractor

This skill extracts your competitors' ads from ad libraries and analyzes what's working—the problems they're highlighting, use cases they're targeting, and copy/creative that's resonating.

When to Use This Skill

  • Researching competitor ad strategies
  • Finding inspiration for your own ads
  • Understanding market positioning
  • Identifying successful ad patterns
  • Analyzing messaging that works
  • Discovering new use cases or pain points
  • Planning ad campaigns with proven concepts

What This Skill Does

  1. Extracts Ads: Scrapes ads from Facebook Ad Library, LinkedIn, etc.
  2. Captures Screenshots: Saves visual copies of all ads
  3. Analyzes Messaging: Identifies problems, use cases, and value props
  4. Categorizes Ads: Groups by theme, audience, or format
  5. Identifies Patterns: Finds common successful approaches
  6. Provides Insights: Explains why certain ads likely perform well

How to Use

Basic Extraction

Extract all current ads from [Competitor Name] on Facebook Ad Library
Scrape ads from [Company] and analyze their messaging

Specific Analysis

Get all ads from [Competitor] focusing on their messaging 
about [specific problem]. What pain points are they highlighting?

Competitive Set

Extract ads from these 5 competitors: [list]. 
Compare their approaches and tell me what's working.

Specific Platform

Get LinkedIn ads from [Competitor] and analyze their 
B2B positioning strategy

Example

User: "Extract ads from Notion on Facebook Ad Library and tell me what messaging is working for them."

Process:

Accessing Facebook Ad Library...
Searching for: Notion
Found: 23 active ads

Extracting screenshots...
[████████████████████] 100%

Saved to: competitor-ads/notion/
- ad-001-collaboration.png
- ad-002-productivity.png
- ad-003-templates.png
...

Analyzing messaging...

Output:

# Notion Ad Analysis

## Overview
- Total Ads: 23 active
- Primary Themes: Productivity (35%), Collaboration (30%), 
  Templates (20%), AI Features (15%)
- Ad Formats: Static images (60%), Video (40%)
- CTA Patterns: "Try for free", "Get started"

## Key Problems They're Highlighting

1. **Scattered Information** (8 ads)
   Copy: "Stop switching between 10 different tools"
   Why it works: Direct pain point many teams face

2. **Meeting Overload** (5 ads)
   Copy: "Replace unnecessary meetings with async updates"
   Why it works: Post-COVID remote work pain point

3. **Lost Documentation** (4 ads)
   Copy: "Never ask 'where is that doc?' again"
   Why it works: Universal workplace frustration

## Successful Creative Patterns

### Pattern 1: Before/After Split
- Shows chaotic tool landscape → Clean Notion workspace
- Used in 6 high-performing ads
- Visual metaphor is immediately clear

### Pattern 2: Feature Showcase
- GIF of actual product usage
- Shows specific feature in 5 seconds
- Used for new features (AI, templates)

### Pattern 3: Social Proof
- "Join 20M users" messaging
- Customer logos
- Used in 4 ads targeting enterprise

## Copy That's Working

Best Headlines:
1. "Your team's knowledge, finally in one place"
   → Benefit-focused, addresses pain directly
   
2. "The all-in-one workspace"
   → Clear positioning, broad appeal
   
3. "AI that actually helps you work"
   → Addresses AI skepticism, practical angle

Best Body Copy Patterns:
- Short sentences (under 10 words)
- Focus on outcomes not features
- Include specific numbers ("Cut meetings by 50%")

## Audience Targeting Insights

Based on ad variations:
- Startup founders: Solo productivity angle
- Team leads: Collaboration and alignment
- Enterprise: Security and compliance mentions
- Students: Free plan, templates, organization

## Recommendations for Your Ads

1. **Test the "tool sprawl" pain point**
   → Strong resonance based on their ad frequency

2. **Use product screenshots over abstract visuals**
   → All their top ads show actual UI

3. **Lead with the problem, not the solution**
   → "Tired of X?" performs better than "Introducing Y"

4. **Keep copy under 100 characters**
   → Their shortest ads seem most frequent

5. **Test before/after visual formats**
   → Proven pattern in their creative

## Files Saved
- All ads: ~/competitor-ads/notion/
- Analysis: ~/competitor-ads/notion/analysis.md
- Best performers: ~/competitor-ads/notion/top-10/

Inspired by: Sumant Subrahmanya's use case from Lenny's Newsletter

What You Can Learn

Messaging Analysis

  • What problems they emphasize
  • How they position against competition
  • Value propositions that resonate
  • Target audience segments

Creative Patterns

  • Visual styles that work
  • Video vs. static image performance
  • Color schemes and branding
  • Layout patterns

Copy Formulas

  • Headline structures
  • Call-to-action patterns
  • Length and tone
  • Emotional triggers

Campaign Strategy

  • Seasonal campaigns
  • Product launch approaches
  • Feature announcement tactics
  • Retargeting patterns

Best Practices

Legal & Ethical

✓ Only use for research and inspiration ✓ Don't copy ads directly ✓ Respect intellectual property ✓ Use insights to inform original creative ✗ Don't plagiarize copy or steal designs

Analysis Tips

  1. Look for patterns: What themes repeat?
  2. Track over time: Save ads monthly to see evolution
  3. Test hypotheses: Adapt successful patterns for your brand
  4. Segment by audience: Different messages for different targets
  5. Compare platforms: LinkedIn vs Facebook messaging differs

Advanced Features

Trend Tracking

Compare [Competitor]'s ads from Q1 vs Q2. 
What messaging has changed?

Multi-Competitor Analysis

Extract ads from [Company A], [Company B], [Company C]. 
What are the common patterns? Where do they differ?

Industry Benchmarks

Show me ad patterns across the top 10 project management 
tools. What problems do they all focus on?

Format Analysis

Analyze video ads vs static image ads from [Competitor]. 
Which gets more engagement? (if data available)

Common Workflows

Ad Campaign Planning

  1. Extract competitor ads
  2. Identify successful patterns
  3. Note gaps in their messaging
  4. Brainstorm unique angles
  5. Draft test ad variations

Positioning Research

  1. Get ads from 5 competitors
  2. Map their positioning
  3. Find underserved angles
  4. Develop differentiated messaging
  5. Test against their approaches

Creative Inspiration

  1. Extract ads by theme
  2. Analyze visual patterns
  3. Note color and layout trends
  4. Adapt successful patterns
  5. Create original variations

Tips for Success

  1. Regular Monitoring: Check monthly for changes
  2. Broad Research: Look at adjacent competitors too
  3. Save Everything: Build a reference library
  4. Test Insights: Run your own experiments
  5. Track Performance: A/B test inspired concepts
  6. Stay Original: Use for inspiration, not copying
  7. Multiple Platforms: Compare Facebook, LinkedIn, TikTok, etc.

Output Formats

  • Screenshots: All ads saved as images
  • Analysis Report: Markdown summary of insights
  • Spreadsheet: CSV with ad copy, CTAs, themes
  • Presentation: Visual deck of top performers
  • Pattern Library: Categorized by approach

Related Use Cases

  • Writing better ad copy for your campaigns
  • Understanding market positioning
  • Finding content gaps in your messaging
  • Discovering new use cases for your product
  • Planning product marketing strategy
  • Inspiring social media content
how to use competitive-ads-extractor

How to use competitive-ads-extractor on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add competitive-ads-extractor
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/composiohq/awesome-claude-skills --skill competitive-ads-extractor

The skills CLI fetches competitive-ads-extractor from GitHub repository composiohq/awesome-claude-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/competitive-ads-extractor

Reload or restart Cursor to activate competitive-ads-extractor. Access the skill through slash commands (e.g., /competitive-ads-extractor) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.436 reviews
  • Aisha Kim· Dec 28, 2024

    competitive-ads-extractor has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Chinedu Jain· Dec 28, 2024

    competitive-ads-extractor reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Chinedu Anderson· Dec 20, 2024

    Solid pick for teams standardizing on skills: competitive-ads-extractor is focused, and the summary matches what you get after install.

  • Kofi Mehta· Nov 19, 2024

    competitive-ads-extractor fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Aarav Sethi· Nov 19, 2024

    Solid pick for teams standardizing on skills: competitive-ads-extractor is focused, and the summary matches what you get after install.

  • Chinedu Reddy· Nov 11, 2024

    We added competitive-ads-extractor from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Luis Huang· Oct 10, 2024

    We added competitive-ads-extractor from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Aarav Haddad· Oct 10, 2024

    competitive-ads-extractor has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Mei Rao· Oct 2, 2024

    competitive-ads-extractor fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Chen Menon· Sep 21, 2024

    I recommend competitive-ads-extractor for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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