Skip to main content
skill GitHub Copilot official · GitHub

competitor-ad-intelligence — GitHub Copilot skill: ad analysis

This skill finds competitors’ public ads on Meta and Google, then examines their creative and landing pages. Use it to review a paid campaign before launch or look for new ad angles.

Install into GitHub Copilot · Skills CLI (Vercel) All methods and platforms ↓
npx skills add github/awesome-copilot --skill competitor-ad-intelligence
Open on GitHub

What competitor-ad-intelligence does

The skill searches Meta Ad Library and Google Ads Transparency Center for competitor ads. It groups headlines by hook type and compares ad formats and calls to action. It can also inspect linked landing pages and campaign clusters, including how closely a page matches an ad’s promise and what action it asks visitors to take.

Start by providing competitor names and domains, your product for comparison, the channels to check, and the desired depth. The workflow uses web_search; an agent that supports fetch_webpage can use it to inspect pages. The sources are public ad libraries, so API keys and credentials are not required.

Install it when your research is about paid ads and their funnels. It is not meant for organic search research or website positioning analysis.

What it helps with

  • Find a competitor’s ads on Meta and Google
  • Group ad headlines by hook type
  • Compare creative formats and calls to action
  • Check whether landing pages match their ads
  • Cluster campaigns by destination and messaging

Example prompts for the agent

  • Analyze the paid ads for example.com on Meta and Google.
  • Find ad angles we have not tried and compare the landing pages.
  • Do a deep teardown of example.com’s paid funnel.

How to install competitor-ad-intelligence

1Skills CLI (Vercel)

npx skills add github/awesome-copilot --skill competitor-ad-intelligence

2GitHub CLI

gh skill install github/awesome-copilot competitor-ad-intelligence

3Manually: put the files in place

.github/skills/competitor-ad-intelligence/SKILL.md

From the same set554

The whole set →
git-commit official github This skill reviews Git changes, stages related files, and creates Conventional Commits. Use it when you want an agent to make one commit or split work into separate commits. GitHub Copilot 47,165installs excalidraw-diagram-generator official github Turn a plain-language description into an Excalidraw diagram. Useful for mapping processes, system structure, and relationships between entities. GitHub Copilot 31,639installs multi-stage-dockerfile official github This skill guides GitHub Copilot in writing multi-stage Dockerfiles for different languages and frameworks. Use it when the final runtime image should contain fewer build dependencies. GitHub Copilot 29,688installs documentation-writer official github Skill that turns the agent into a technical writer following the Diátaxis framework: tutorials, how-to guides, reference, and explanation. Proposes structure before writing. GitHub Copilot 27,757installs prd official github Turns a feature idea into a structured PRD with user stories, technical requirements, and risks. Use it when planning a software feature or an AI-powered one. GitHub Copilot 24,035installs refactor official github This skill reshapes existing code without changing its external behavior. Use it for gradual cleanup of large functions, duplication, weak types, and code smells. GitHub Copilot 22,321installs java-springboot official github Gives GitHub Copilot Spring Boot development practices, from project layout to tests and security. Use it when writing or reviewing Java application code. GitHub Copilot 21,272installs create-readme official github This skill reviews a project and creates a structured README.md. Use it when the repository needs clear documentation based on its actual files and code. GitHub Copilot 19,081installs

Similar

social-evidence-research Seth Hobson Builds traceable reports from public social discussion and supplied exports. Use it to compare a topic, audit research, and mark access gaps. Claude Code CX Codex Cursor 201installs market-research claude-code-skills A skill for sizing markets, planning surveys, and scoring segments. Use it when your analysis needs visible methods and assumptions. Claude Code 232installs local-seo-manager Stan Varashilov (Steffonet) This skill audits Google Business Profile, drafts neighborhood service pages and checks business details across directories. Use it for a business that serves customers at their location. Claude Code 90installs video-content-strategist Alireza Rezvani Plans video strategy, scripts long-form YouTube videos, and repurposes blog posts or webinars into short-form clips. Built for creators and founders. Claude Code 83installs seo-audit coreyhaines31 Diagnoses technical SEO issues, indexing drops, and metadata errors. Identifies why your site is losing organic search rankings in Google. Claude Code CX Codex Cursor +1 236,800installs brand claudekit Keeps brand voice, visual rules and design tokens in one markdown file, then feeds them to your agent's prompts and to your CSS variables. Claude Code CX Codex Cursor +1 39,500installs banner-design claudekit Generates banners for social media, ads, and web hero sections using HTML/CSS. Useful when you need fast visual creative assets directly in your coding agent. Claude Code CX Codex Cursor +1 39,000installs marketing-psychology coreyhaines31 Applies behavioral science and mental models to marketing decisions. It helps teams analyze buyer motivations and solve funnel bottlenecks. Claude Code CX Codex Cursor +1 164,000installs

Questions about competitor-ad-intelligence

How do I install competitor-ad-intelligence in GitHub Copilot?

Run npx skills add github/awesome-copilot --skill competitor-ad-intelligence. You can also use gh skill install github/awesome-copilot competitor-ad-intelligence.

What does competitor-ad-intelligence do?

It finds public ads on Meta and Google, then analyzes their creative and landing pages. The resulting review covers campaign themes, positioning, and funnels.

Does competitor-ad-intelligence need an API key?

No. It uses the public Meta and Google ad libraries and does not require API keys or credentials.

Source text

SKILL.md · MIT
---
name: competitor-ad-intelligence
description: 'Use this skill when the user asks to analyze, tear down, or reverse-engineer a competitor''s paid ads. Trigger for prompts like "what ads is [competitor] running", "tear down their ad strategy", "competitor ad analysis", "find ad angles we haven''t tried", or "reverse-engineer their paid funnel". Do not trigger for organic/SEO competitor research or website positioning analysis.'
license: MIT
compatibility: 'Cross-platform. Uses web search and public ad libraries (Meta Ad Library, Google Ads Transparency Center) only — no API keys or credentials required.'
metadata:
  version: "1.0"
  author: GooseWorks
  source: https://github.com/gooseworks-ai/goose-skills
---

# Competitor Ad Intelligence

Scrape competitor ads from Meta and Google, analyze creative patterns, reverse-engineer landing page funnels, and produce a full strategic teardown — hooks, formats, positioning bets, vulnerabilities, and counter-plays.

**Core principle:** A competitor's ad portfolio is a window into their growth strategy. Long-running ads reveal what converts. New ads reveal what they're testing. Landing pages reveal their positioning bets. The best ad creative teams start with evidence from what's already working, then differentiate.

## When to Use

- "What ads are my competitors running?"
- "Tear down [competitor]'s ad strategy"
- "Find new creative angles for our paid campaigns"
- "Reverse-engineer [competitor]'s paid funnel"
- "What hooks are working in [our space]?"
- "Audit the ad landscape before we launch"
- "Find weaknesses in [competitor]'s ad strategy"
- "What format — video, image, carousel — is dominant in our category?"

## Phase 0: Intake

Gather from the user:

1. **Competitor names + domains** (e.g., `apollo.io`, `clay.run`)
2. **Your product/domain** — for comparison framing
3. **Channels:** Meta only, Google only, or both? (default: both)
4. **Depth level:**
   - **Standard:** Ad scrape + creative analysis + landing page analysis
   - **Deep:** Standard + historical comparison + funnel reconstruction + counter-plays
5. **Product category** — helps frame analysis
6. **Known competitor landing pages?** — any URLs already spotted in their ads

## Phase 1: Scrape Meta Ads

For each competitor domain, scrape ads from Meta Ad Library.

Use `web_search` to find competitor ads in the Meta Ad Library (publicly accessible, no API key needed):

```
web_search: site:facebook.com/ads/library "[competitor_name]"
web_search: "[competitor_name]" Meta Ad Library active ads
web_search: "[competitor_name]" facebook ads examples
```

You can also visit the Meta Ad Library directly: `https://www.facebook.com/ads/library/?active_status=active&ad_type=all&country=US&q=<competitor_name>`

Use `fetch_webpage` on the Ad Library URL to extract ad details if your agent supports it.

> **Note:** Apify actors for Meta Ad Library scraping exist but are unreliable as of April 2026 due to Meta's anti-scraping measures. Use `web_search` as the primary method.

**Collect per ad:**
- Ad copy (headline + primary text)
- Visual type (image / video / carousel)
- CTA button text
- Landing page URL
- Active duration (first seen, still running or stopped)
- Platforms (Facebook, Instagram, Audience Network)
- Ad variations (A/B tests — same landing page, different creative)

## Phase 2: Scrape Google Ads

For each competitor domain, scrape ads from Google Ads Transparency Center.

Use `web_search` to find competitor ads in Google Ads Transparency Center (publicly accessible):

```
web_search: site:adstransparency.google.com "[competitor_name]"
web_search: "[competitor_name]" Google Ads transparency
web_search: "[competitor_name]" google search ads examples
```

You can also visit directly: `https://adstransparency.google.com/?search_text=<competitor_name>`

Use `fetch_webpage` on the Transparency Center URL to extract ad details if your agent supports it.

**Collect per ad:**
- Headline variants (up to 3)
- Description lines
- Ad type (Search / Display / YouTube / Shopping)
- Landing page URL
- Geographic targeting (if visible)

## Phase 3: Analyze Creative Patterns

After collecting all ads, perform structured analysis.

### Hook Pattern Clustering

Group all ad headlines/openers by hook type:

| Hook Type | Pattern | Example |
|-----------|---------|---------|
| **Fear/Loss** | Risk of missing out or falling behind | "Your competitors are already using AI SDRs" |
| **Outcome** | Direct result promise | "10x your pipeline in 30 days" |
| **Question** | Challenges current assumption | "Still doing outbound manually?" |
| **Social proof** | Names customers or numbers | "Join 500+ B2B teams using [product]" |
| **Contrarian** | Challenges conventional wisdom | "Cold email isn't dead. Your copy is." |
| **Empathy** | Validates their pain | "We know SDR ramp time is brutal" |
| **Product-led** | Feature as hook | "[Feature] is live — see what's new" |

Count how many ads per competitor use each hook type. This reveals their primary messaging strategy.

### Format Distribution

| Format | Meta | Google |
|--------|------|--------|
| Static image | [N] | N/A |
| Video | [N] | [N] |
| Carousel | [N] | N/A |
| Search text | N/A | [N] |
| Display banner | N/A | [N] |

### CTA Taxonomy

List all unique CTAs found. Common patterns:
- **Urgency:** "Start free", "Try now", "Get started today"
- **Low-friction:** "See how it works", "Watch demo", "Learn more"
- **Outcome:** "Book a demo", "Get your free audit", "Calculate your ROI"

## Phase 4: Landing Page & Funnel Analysis

For each unique landing page URL found in ads, fetch and analyze:

```
fetch_webpage: [landing_page_url]
```

Or use `curl` if `fetch_webpage` is unavailable.

**Extract per landing page:**
- **Hero headline** — Does it match the ad promise?
- **Subheadline** — Value prop expansion
- **Primary CTA** — What action are they driving? (Demo / Free trial / Sign up / Download)
- **Social proof** — Logos, testimonials, case study metrics
- **Pricing visibility** — Is pricing shown or hidden?
- **Form fields** — How much info do they ask for?
- **Page type** — General homepage / dedicated LP / feature page / use-case page
- **Message match score** — How well does the LP deliver on the ad's promise? (1-10)

### Campaign Clustering

Group all ads into logical campaigns by:
- **Landing page destination** — Ads pointing to the same URL = same campaign
- **Messaging theme** — Similar copy angles = same strategic bet
- **Audience signal** — Different copy for different personas

### Per-Campaign Funnel Analysis

For each campaign cluster:

| Dimension | Analysis |
|-----------|----------|
| **Strategic intent** | What is this campaign trying to achieve? (Awareness / Lead gen / Free trial / Competitive displacement) |
| **Target persona** | Who is this ad speaking to? (Role, pain, stage) |
| **Positioning bet** | What market position are they claiming? |
| **Hook strategy** | Fear / Outcome / Social proof / Contrarian / Product-led |
| **Conversion path** | Ad → LP → CTA → [Demo call / Free trial / Content download] |
| **Longevity signal** | How long has this been running? (Longer = likely working) |
| **A/B tests detected** | Multiple creatives to same LP = active testing |

### Budget Allocation Inference

Based on ad volume and platform distribution, estimate where they're concentrating spend:

| Platform | Ad Count | % of Total | Estimated Focus |
|----------|----------|-----------|-----------------|
| Meta (Facebook) | [N] | [X%] | [Awareness / Retargeting] |
| Meta (Instagram) | [N] | [X%] | [Visual / younger audience] |
| Google Search | [N] | [X%] | [Bottom-funnel capture] |
| Google Display | [N] | [X%] | [Awareness / retargeting] |
| YouTube | [N] | [X%] | [Education / awareness] |

## Phase 5: Strategic Analysis

### Creative Gap Analysis

Identify across all competitors:

1. **Angles nobody is running** — Hook types absent from competitor ads = white space
2. **Overcrowded angles** — If everyone leads with "save time", avoid it or be more specific
3. **Format opportunities** — If no one is running video in your space, it may stand out
4. **Underutilized proof** — Are competitors avoiding specific proof points you could own?
5. **CTA patterns to test** — What CTAs do the longest-running ads use?

### Vulnerability Analysis

Identify weaknesses in each competitor's ad strategy:

| Vulnerability Type | Description |
|-------------------|-------------|
| **Message-LP mismatch** | Ad promises one thing, LP delivers another |
| **Single-persona dependency** | All ads target the same persona — missing segments |
| **Platform concentration** | Heavy on one platform, absent from others |
| **No social proof** | Ads or LPs lack credibility markers |
| **Weak CTA** | Asking for too much too soon (demo before value) |
| **Generic positioning** | Claims anyone could make — not differentiated |
| **Stale creative** | Same ads running unchanged for months — fatigue risk |

### Historical Comparison (Deep Mode)

If Web Archive data exists for their landing pages:
- Has their positioning changed in the last 6-12 months?
- What campaigns did they retire? (Possible losers)
- What campaigns have they scaled up? (Possible winners)

## Phase 6: Output

```markdown
# Competitor Ad Intelligence Report — [DATE]

## Coverage
- Competitors analyzed: [list]
- Meta ads collected: [N]
- Google ads collected: [N]
- Unique landing pages analyzed: [N]
- Estimated active campaigns: [N]

---

## Executive Summary

[3-5 sentence summary: What is the competitive ad landscape? What's working? Where are the gaps and vulnerabilities?]

---

## Meta Ad Analysis

### Hook Distribution
| Hook Type | [Comp1] | [Comp2] | [Comp3] |
|-----------|---------|---------|---------|
| Fear/Loss | 40% | 10% | 0% |
| Outcome | 30% | 50% | 60% |
...

### Top Performing Ads (Longest Running)
**[Competitor] — [Ad Title/Hook]**
> [Ad copy excerpt]
- Format: [type]
- CTA: [text]
- Running since: [date]
- Why it likely works: [analysis]

---

## Google Ad Analysis

### Headline Patterns
[Top headline structures with examples]

### Most Common CTAs
[ranked list]

---

## Campaign Breakdown

### Campaign 1: [Inferred Campaign Name]
- **Competitor:** [name]
- **Ads in cluster:** [N]
- **Platform(s):** [Meta / Google / Both]
- **Strategic intent:** [Awareness / Lead gen / Competitive displacement / etc.]
- **Target persona:** [Description]
- **Hook strategy:** [Type]
- **Landing page:** [URL]
  - Hero: "[Headline text]"
  - CTA: "[Button text]"
  - Message match: [Score/10]
- **Longevity:** [First seen date → status]
- **A/B tests detected:** [Yes/No — what they're testing]

**Sample ad:**
> **Headline:** [text]
> **Body:** [text]
> **CTA:** [button]
> **Format:** [Image/Video/Carousel]

**Assessment:** [1-2 sentences — is this working? Why/why not?]

### Campaign 2: ...

---

## Funnel Map

```
[Ad: Hook/Angle] → [LP: /landing-page-url] → [CTA: Book Demo]
                                               ↓
[Ad: Different angle] → [LP: /same-or-different] → [CTA: Free Trial]
```

---

## Budget Allocation Estimate

| Platform | Share | Focus Area |
|----------|-------|-----------|
| [Platform] | [X%] | [Intent] |

---

## Creative Gap Analysis

### Angles Nobody Is Running
1. [Angle] — Why it could work for you: [reasoning]
2. [Angle] — ...

### Overcrowded Angles (Avoid or Differentiate)
- [Angle] — [N] of [N] competitors use this

### Format White Space
- [Format] is not being used by competitors on [platform]

---

## Vulnerability Report

### 1. [Vulnerability]
**Competitor:** [name]
**Evidence:** [What we observed]
**Your opportunity:** [How to exploit this gap]

### 2. ...

---

## Recommended Counter-Plays

### Counter-Play 1: [Name]
- **Target their weakness:** [Which vulnerability]
- **Your ad angle:** [Hook]
- **Platform:** [Where to run]
- **Proposed headline:** "[headline]"
- **Proposed body:** "[copy]"
- **LP strategy:** [What your landing page should emphasize]
- **Why test this:** [rationale]

### Counter-Play 2: ...
```

## Cost

| Component | Cost |
|-----------|------|
| Ad library research (web_search) | Free |
| Landing page fetching | Free |
| Web Archive lookup (deep mode) | Free |
| Analysis | Free (LLM reasoning) |
| **Total** | **Free** |

## Environment Variables

- No API keys required. This skill uses publicly accessible ad libraries and web search.

## Tools Used

- **`web_search`** — query Meta Ad Library and Google Ads Transparency Center
- **`fetch_webpage`** or **`curl`** — fetch and analyze landing pages

## Trigger Phrases

- "What ads are [competitor] running?"
- "Tear down [competitor]'s ad strategy"
- "Audit the ad landscape for [product category]"
- "Run ad intelligence for [competitors]"
- "Find new paid ad angles we haven't tried"
- "Reverse-engineer [competitor]'s paid funnel"
- "Find weaknesses in [competitor]'s ad strategy"
- "Deep competitive ad analysis on [competitor]"

© GooseWorks · MIT · github/awesome-copilot

See also

Project sponsors

Companies that keep this analytics open
Gold sponsor

Impressions, clicks and code copies — open statistics. We keep the numbers public for the same reason NeBlask itself is public. Become a sponsor