[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6ADB6WK62EVPRJW983H1HGS":3,"skill-same:01M6ADB6WK62EVPRJW983H1HGS":103},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":28,"publishedAt":55,"linkOnly":56,"markdownContent":57,"markdownBody":58,"frontMatter":59,"refName":65,"commitSha":66,"skillDirectory":67,"forksCount":68,"repositoryHtmlUrl":69,"repositoryHomepageUrl":70,"ownerHtmlUrl":71,"ownerBlogUrl":72,"ownerDescription":73,"updatedAt":74,"install":75,"resources":88},"01M6ADB6WK62EVPRJW983H1HGS","competitor-ad-intelligence",null,"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\u002FSEO competitor research or website positioning analysis.","github\u002Fawesome-copilot","github","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F9919?v=4","01M6AC83DS133TPXFSP1DHNCC6","GitHub","01M6AD3PBDYPK7NVFJNJ66Y8RS",41028,"MIT","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fcompetitor-ad-intelligence\u002FSKILL.md",[18,23],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000019","营销推广","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":26,"taxonomyTypeDesc":27},"01JBSEEDCAT000000000000035","市场营销","PROFESSION","适用职业",[29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,9],"competitor","ad","intelligence","competitor ad intelligence","credentials","paid","when","api keys","positioning","engineer","only","analyze","ads","web search","api","google","analysis","paid ads","Meta","library","https","website","search","libraries","web","research","2026-11-10 10:12:30",false,"---\nname: competitor-ad-intelligence\ndescription: '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\u002FSEO competitor research or website positioning analysis.'\nlicense: MIT\ncompatibility: 'Cross-platform. Uses web search and public ad libraries (Meta Ad Library, Google Ads Transparency Center) only — no API keys or credentials required.'\nmetadata:\n  version: \"1.0\"\n  author: GooseWorks\n  source: https:\u002F\u002Fgithub.com\u002Fgooseworks-ai\u002Fgoose-skills\n---\n\n# Competitor Ad Intelligence\n\nScrape 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.\n\n**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.\n\n## When to Use\n\n- \"What ads are my competitors running?\"\n- \"Tear down [competitor]'s ad strategy\"\n- \"Find new creative angles for our paid campaigns\"\n- \"Reverse-engineer [competitor]'s paid funnel\"\n- \"What hooks are working in [our space]?\"\n- \"Audit the ad landscape before we launch\"\n- \"Find weaknesses in [competitor]'s ad strategy\"\n- \"What format — video, image, carousel — is dominant in our category?\"\n\n## Phase 0: Intake\n\nGather from the user:\n\n1. **Competitor names + domains** (e.g., `apollo.io`, `clay.run`)\n2. **Your product\u002Fdomain** — for comparison framing\n3. **Channels:** Meta only, Google only, or both? (default: both)\n4. **Depth level:**\n   - **Standard:** Ad scrape + creative analysis + landing page analysis\n   - **Deep:** Standard + historical comparison + funnel reconstruction + counter-plays\n5. **Product category** — helps frame analysis\n6. **Known competitor landing pages?** — any URLs already spotted in their ads\n\n## Phase 1: Scrape Meta Ads\n\nFor each competitor domain, scrape ads from Meta Ad Library.\n\nUse `web_search` to find competitor ads in the Meta Ad Library (publicly accessible, no API key needed):\n\n```\nweb_search: site:facebook.com\u002Fads\u002Flibrary \"[competitor_name]\"\nweb_search: \"[competitor_name]\" Meta Ad Library active ads\nweb_search: \"[competitor_name]\" facebook ads examples\n```\n\nYou can also visit the Meta Ad Library directly: `https:\u002F\u002Fwww.facebook.com\u002Fads\u002Flibrary\u002F?active_status=active&ad_type=all&country=US&q=\u003Ccompetitor_name>`\n\nUse `fetch_webpage` on the Ad Library URL to extract ad details if your agent supports it.\n\n> **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.\n\n**Collect per ad:**\n- Ad copy (headline + primary text)\n- Visual type (image \u002F video \u002F carousel)\n- CTA button text\n- Landing page URL\n- Active duration (first seen, still running or stopped)\n- Platforms (Facebook, Instagram, Audience Network)\n- Ad variations (A\u002FB tests — same landing page, different creative)\n\n## Phase 2: Scrape Google Ads\n\nFor each competitor domain, scrape ads from Google Ads Transparency Center.\n\nUse `web_search` to find competitor ads in Google Ads Transparency Center (publicly accessible):\n\n```\nweb_search: site:adstransparency.google.com \"[competitor_name]\"\nweb_search: \"[competitor_name]\" Google Ads transparency\nweb_search: \"[competitor_name]\" google search ads examples\n```\n\nYou can also visit directly: `https:\u002F\u002Fadstransparency.google.com\u002F?search_text=\u003Ccompetitor_name>`\n\nUse `fetch_webpage` on the Transparency Center URL to extract ad details if your agent supports it.\n\n**Collect per ad:**\n- Headline variants (up to 3)\n- Description lines\n- Ad type (Search \u002F Display \u002F YouTube \u002F Shopping)\n- Landing page URL\n- Geographic targeting (if visible)\n\n## Phase 3: Analyze Creative Patterns\n\nAfter collecting all ads, perform structured analysis.\n\n### Hook Pattern Clustering\n\nGroup all ad headlines\u002Fopeners by hook type:\n\n| Hook Type | Pattern | Example |\n|-----------|---------|---------|\n| **Fear\u002FLoss** | Risk of missing out or falling behind | \"Your competitors are already using AI SDRs\" |\n| **Outcome** | Direct result promise | \"10x your pipeline in 30 days\" |\n| **Question** | Challenges current assumption | \"Still doing outbound manually?\" |\n| **Social proof** | Names customers or numbers | \"Join 500+ B2B teams using [product]\" |\n| **Contrarian** | Challenges conventional wisdom | \"Cold email isn't dead. Your copy is.\" |\n| **Empathy** | Validates their pain | \"We know SDR ramp time is brutal\" |\n| **Product-led** | Feature as hook | \"[Feature] is live — see what's new\" |\n\nCount how many ads per competitor use each hook type. This reveals their primary messaging strategy.\n\n### Format Distribution\n\n| Format | Meta | Google |\n|--------|------|--------|\n| Static image | [N] | N\u002FA |\n| Video | [N] | [N] |\n| Carousel | [N] | N\u002FA |\n| Search text | N\u002FA | [N] |\n| Display banner | N\u002FA | [N] |\n\n### CTA Taxonomy\n\nList all unique CTAs found. Common patterns:\n- **Urgency:** \"Start free\", \"Try now\", \"Get started today\"\n- **Low-friction:** \"See how it works\", \"Watch demo\", \"Learn more\"\n- **Outcome:** \"Book a demo\", \"Get your free audit\", \"Calculate your ROI\"\n\n## Phase 4: Landing Page & Funnel Analysis\n\nFor each unique landing page URL found in ads, fetch and analyze:\n\n```\nfetch_webpage: [landing_page_url]\n```\n\nOr use `curl` if `fetch_webpage` is unavailable.\n\n**Extract per landing page:**\n- **Hero headline** — Does it match the ad promise?\n- **Subheadline** — Value prop expansion\n- **Primary CTA** — What action are they driving? (Demo \u002F Free trial \u002F Sign up \u002F Download)\n- **Social proof** — Logos, testimonials, case study metrics\n- **Pricing visibility** — Is pricing shown or hidden?\n- **Form fields** — How much info do they ask for?\n- **Page type** — General homepage \u002F dedicated LP \u002F feature page \u002F use-case page\n- **Message match score** — How well does the LP deliver on the ad's promise? (1-10)\n\n### Campaign Clustering\n\nGroup all ads into logical campaigns by:\n- **Landing page destination** — Ads pointing to the same URL = same campaign\n- **Messaging theme** — Similar copy angles = same strategic bet\n- **Audience signal** — Different copy for different personas\n\n### Per-Campaign Funnel Analysis\n\nFor each campaign cluster:\n\n| Dimension | Analysis |\n|-----------|----------|\n| **Strategic intent** | What is this campaign trying to achieve? (Awareness \u002F Lead gen \u002F Free trial \u002F Competitive displacement) |\n| **Target persona** | Who is this ad speaking to? (Role, pain, stage) |\n| **Positioning bet** | What market position are they claiming? |\n| **Hook strategy** | Fear \u002F Outcome \u002F Social proof \u002F Contrarian \u002F Product-led |\n| **Conversion path** | Ad → LP → CTA → [Demo call \u002F Free trial \u002F Content download] |\n| **Longevity signal** | How long has this been running? (Longer = likely working) |\n| **A\u002FB tests detected** | Multiple creatives to same LP = active testing |\n\n### Budget Allocation Inference\n\nBased on ad volume and platform distribution, estimate where they're concentrating spend:\n\n| Platform | Ad Count | % of Total | Estimated Focus |\n|----------|----------|-----------|-----------------|\n| Meta (Facebook) | [N] | [X%] | [Awareness \u002F Retargeting] |\n| Meta (Instagram) | [N] | [X%] | [Visual \u002F younger audience] |\n| Google Search | [N] | [X%] | [Bottom-funnel capture] |\n| Google Display | [N] | [X%] | [Awareness \u002F retargeting] |\n| YouTube | [N] | [X%] | [Education \u002F awareness] |\n\n## Phase 5: Strategic Analysis\n\n### Creative Gap Analysis\n\nIdentify across all competitors:\n\n1. **Angles nobody is running** — Hook types absent from competitor ads = white space\n2. **Overcrowded angles** — If everyone leads with \"save time\", avoid it or be more specific\n3. **Format opportunities** — If no one is running video in your space, it may stand out\n4. **Underutilized proof** — Are competitors avoiding specific proof points you could own?\n5. **CTA patterns to test** — What CTAs do the longest-running ads use?\n\n### Vulnerability Analysis\n\nIdentify weaknesses in each competitor's ad strategy:\n\n| Vulnerability Type | Description |\n|-------------------|-------------|\n| **Message-LP mismatch** | Ad promises one thing, LP delivers another |\n| **Single-persona dependency** | All ads target the same persona — missing segments |\n| **Platform concentration** | Heavy on one platform, absent from others |\n| **No social proof** | Ads or LPs lack credibility markers |\n| **Weak CTA** | Asking for too much too soon (demo before value) |\n| **Generic positioning** | Claims anyone could make — not differentiated |\n| **Stale creative** | Same ads running unchanged for months — fatigue risk |\n\n### Historical Comparison (Deep Mode)\n\nIf Web Archive data exists for their landing pages:\n- Has their positioning changed in the last 6-12 months?\n- What campaigns did they retire? (Possible losers)\n- What campaigns have they scaled up? (Possible winners)\n\n## Phase 6: Output\n\n```markdown\n# Competitor Ad Intelligence Report — [DATE]\n\n## Coverage\n- Competitors analyzed: [list]\n- Meta ads collected: [N]\n- Google ads collected: [N]\n- Unique landing pages analyzed: [N]\n- Estimated active campaigns: [N]\n\n---\n\n## Executive Summary\n\n[3-5 sentence summary: What is the competitive ad landscape? What's working? Where are the gaps and vulnerabilities?]\n\n---\n\n## Meta Ad Analysis\n\n### Hook Distribution\n| Hook Type | [Comp1] | [Comp2] | [Comp3] |\n|-----------|---------|---------|---------|\n| Fear\u002FLoss | 40% | 10% | 0% |\n| Outcome | 30% | 50% | 60% |\n...\n\n### Top Performing Ads (Longest Running)\n**[Competitor] — [Ad Title\u002FHook]**\n> [Ad copy excerpt]\n- Format: [type]\n- CTA: [text]\n- Running since: [date]\n- Why it likely works: [analysis]\n\n---\n\n## Google Ad Analysis\n\n### Headline Patterns\n[Top headline structures with examples]\n\n### Most Common CTAs\n[ranked list]\n\n---\n\n## Campaign Breakdown\n\n### Campaign 1: [Inferred Campaign Name]\n- **Competitor:** [name]\n- **Ads in cluster:** [N]\n- **Platform(s):** [Meta \u002F Google \u002F Both]\n- **Strategic intent:** [Awareness \u002F Lead gen \u002F Competitive displacement \u002F etc.]\n- **Target persona:** [Description]\n- **Hook strategy:** [Type]\n- **Landing page:** [URL]\n  - Hero: \"[Headline text]\"\n  - CTA: \"[Button text]\"\n  - Message match: [Score\u002F10]\n- **Longevity:** [First seen date → status]\n- **A\u002FB tests detected:** [Yes\u002FNo — what they're testing]\n\n**Sample ad:**\n> **Headline:** [text]\n> **Body:** [text]\n> **CTA:** [button]\n> **Format:** [Image\u002FVideo\u002FCarousel]\n\n**Assessment:** [1-2 sentences — is this working? Why\u002Fwhy not?]\n\n### Campaign 2: ...\n\n---\n\n## Funnel Map\n\n```\n[Ad: Hook\u002FAngle] → [LP: \u002Flanding-page-url] → [CTA: Book Demo]\n                                               ↓\n[Ad: Different angle] → [LP: \u002Fsame-or-different] → [CTA: Free Trial]\n```\n\n---\n\n## Budget Allocation Estimate\n\n| Platform | Share | Focus Area |\n|----------|-------|-----------|\n| [Platform] | [X%] | [Intent] |\n\n---\n\n## Creative Gap Analysis\n\n### Angles Nobody Is Running\n1. [Angle] — Why it could work for you: [reasoning]\n2. [Angle] — ...\n\n### Overcrowded Angles (Avoid or Differentiate)\n- [Angle] — [N] of [N] competitors use this\n\n### Format White Space\n- [Format] is not being used by competitors on [platform]\n\n---\n\n## Vulnerability Report\n\n### 1. [Vulnerability]\n**Competitor:** [name]\n**Evidence:** [What we observed]\n**Your opportunity:** [How to exploit this gap]\n\n### 2. ...\n\n---\n\n## Recommended Counter-Plays\n\n### Counter-Play 1: [Name]\n- **Target their weakness:** [Which vulnerability]\n- **Your ad angle:** [Hook]\n- **Platform:** [Where to run]\n- **Proposed headline:** \"[headline]\"\n- **Proposed body:** \"[copy]\"\n- **LP strategy:** [What your landing page should emphasize]\n- **Why test this:** [rationale]\n\n### Counter-Play 2: ...\n```\n\n## Cost\n\n| Component | Cost |\n|-----------|------|\n| Ad library research (web_search) | Free |\n| Landing page fetching | Free |\n| Web Archive lookup (deep mode) | Free |\n| Analysis | Free (LLM reasoning) |\n| **Total** | **Free** |\n\n## Environment Variables\n\n- No API keys required. This skill uses publicly accessible ad libraries and web search.\n\n## Tools Used\n\n- **`web_search`** — query Meta Ad Library and Google Ads Transparency Center\n- **`fetch_webpage`** or **`curl`** — fetch and analyze landing pages\n\n## Trigger Phrases\n\n- \"What ads are [competitor] running?\"\n- \"Tear down [competitor]'s ad strategy\"\n- \"Audit the ad landscape for [product category]\"\n- \"Run ad intelligence for [competitors]\"\n- \"Find new paid ad angles we haven't tried\"\n- \"Reverse-engineer [competitor]'s paid funnel\"\n- \"Find weaknesses in [competitor]'s ad strategy\"\n- \"Deep competitive ad analysis on [competitor]\"\n","# Competitor Ad Intelligence\n\nScrape 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.\n\n**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.\n\n## When to Use\n\n- \"What ads are my competitors running?\"\n- \"Tear down [competitor]'s ad strategy\"\n- \"Find new creative angles for our paid campaigns\"\n- \"Reverse-engineer [competitor]'s paid funnel\"\n- \"What hooks are working in [our space]?\"\n- \"Audit the ad landscape before we launch\"\n- \"Find weaknesses in [competitor]'s ad strategy\"\n- \"What format — video, image, carousel — is dominant in our category?\"\n\n## Phase 0: Intake\n\nGather from the user:\n\n1. **Competitor names + domains** (e.g., `apollo.io`, `clay.run`)\n2. **Your product\u002Fdomain** — for comparison framing\n3. **Channels:** Meta only, Google only, or both? (default: both)\n4. **Depth level:**\n   - **Standard:** Ad scrape + creative analysis + landing page analysis\n   - **Deep:** Standard + historical comparison + funnel reconstruction + counter-plays\n5. **Product category** — helps frame analysis\n6. **Known competitor landing pages?** — any URLs already spotted in their ads\n\n## Phase 1: Scrape Meta Ads\n\nFor each competitor domain, scrape ads from Meta Ad Library.\n\nUse `web_search` to find competitor ads in the Meta Ad Library (publicly accessible, no API key needed):\n\n```\nweb_search: site:facebook.com\u002Fads\u002Flibrary \"[competitor_name]\"\nweb_search: \"[competitor_name]\" Meta Ad Library active ads\nweb_search: \"[competitor_name]\" facebook ads examples\n```\n\nYou can also visit the Meta Ad Library directly: `https:\u002F\u002Fwww.facebook.com\u002Fads\u002Flibrary\u002F?active_status=active&ad_type=all&country=US&q=\u003Ccompetitor_name>`\n\nUse `fetch_webpage` on the Ad Library URL to extract ad details if your agent supports it.\n\n> **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.\n\n**Collect per ad:**\n- Ad copy (headline + primary text)\n- Visual type (image \u002F video \u002F carousel)\n- CTA button text\n- Landing page URL\n- Active duration (first seen, still running or stopped)\n- Platforms (Facebook, Instagram, Audience Network)\n- Ad variations (A\u002FB tests — same landing page, different creative)\n\n## Phase 2: Scrape Google Ads\n\nFor each competitor domain, scrape ads from Google Ads Transparency Center.\n\nUse `web_search` to find competitor ads in Google Ads Transparency Center (publicly accessible):\n\n```\nweb_search: site:adstransparency.google.com \"[competitor_name]\"\nweb_search: \"[competitor_name]\" Google Ads transparency\nweb_search: \"[competitor_name]\" google search ads examples\n```\n\nYou can also visit directly: `https:\u002F\u002Fadstransparency.google.com\u002F?search_text=\u003Ccompetitor_name>`\n\nUse `fetch_webpage` on the Transparency Center URL to extract ad details if your agent supports it.\n\n**Collect per ad:**\n- Headline variants (up to 3)\n- Description lines\n- Ad type (Search \u002F Display \u002F YouTube \u002F Shopping)\n- Landing page URL\n- Geographic targeting (if visible)\n\n## Phase 3: Analyze Creative Patterns\n\nAfter collecting all ads, perform structured analysis.\n\n### Hook Pattern Clustering\n\nGroup all ad headlines\u002Fopeners by hook type:\n\n| Hook Type | Pattern | Example |\n|-----------|---------|---------|\n| **Fear\u002FLoss** | Risk of missing out or falling behind | \"Your competitors are already using AI SDRs\" |\n| **Outcome** | Direct result promise | \"10x your pipeline in 30 days\" |\n| **Question** | Challenges current assumption | \"Still doing outbound manually?\" |\n| **Social proof** | Names customers or numbers | \"Join 500+ B2B teams using [product]\" |\n| **Contrarian** | Challenges conventional wisdom | \"Cold email isn't dead. Your copy is.\" |\n| **Empathy** | Validates their pain | \"We know SDR ramp time is brutal\" |\n| **Product-led** | Feature as hook | \"[Feature] is live — see what's new\" |\n\nCount how many ads per competitor use each hook type. This reveals their primary messaging strategy.\n\n### Format Distribution\n\n| Format | Meta | Google |\n|--------|------|--------|\n| Static image | [N] | N\u002FA |\n| Video | [N] | [N] |\n| Carousel | [N] | N\u002FA |\n| Search text | N\u002FA | [N] |\n| Display banner | N\u002FA | [N] |\n\n### CTA Taxonomy\n\nList all unique CTAs found. Common patterns:\n- **Urgency:** \"Start free\", \"Try now\", \"Get started today\"\n- **Low-friction:** \"See how it works\", \"Watch demo\", \"Learn more\"\n- **Outcome:** \"Book a demo\", \"Get your free audit\", \"Calculate your ROI\"\n\n## Phase 4: Landing Page & Funnel Analysis\n\nFor each unique landing page URL found in ads, fetch and analyze:\n\n```\nfetch_webpage: [landing_page_url]\n```\n\nOr use `curl` if `fetch_webpage` is unavailable.\n\n**Extract per landing page:**\n- **Hero headline** — Does it match the ad promise?\n- **Subheadline** — Value prop expansion\n- **Primary CTA** — What action are they driving? (Demo \u002F Free trial \u002F Sign up \u002F Download)\n- **Social proof** — Logos, testimonials, case study metrics\n- **Pricing visibility** — Is pricing shown or hidden?\n- **Form fields** — How much info do they ask for?\n- **Page type** — General homepage \u002F dedicated LP \u002F feature page \u002F use-case page\n- **Message match score** — How well does the LP deliver on the ad's promise? (1-10)\n\n### Campaign Clustering\n\nGroup all ads into logical campaigns by:\n- **Landing page destination** — Ads pointing to the same URL = same campaign\n- **Messaging theme** — Similar copy angles = same strategic bet\n- **Audience signal** — Different copy for different personas\n\n### Per-Campaign Funnel Analysis\n\nFor each campaign cluster:\n\n| Dimension | Analysis |\n|-----------|----------|\n| **Strategic intent** | What is this campaign trying to achieve? (Awareness \u002F Lead gen \u002F Free trial \u002F Competitive displacement) |\n| **Target persona** | Who is this ad speaking to? (Role, pain, stage) |\n| **Positioning bet** | What market position are they claiming? |\n| **Hook strategy** | Fear \u002F Outcome \u002F Social proof \u002F Contrarian \u002F Product-led |\n| **Conversion path** | Ad → LP → CTA → [Demo call \u002F Free trial \u002F Content download] |\n| **Longevity signal** | How long has this been running? (Longer = likely working) |\n| **A\u002FB tests detected** | Multiple creatives to same LP = active testing |\n\n### Budget Allocation Inference\n\nBased on ad volume and platform distribution, estimate where they're concentrating spend:\n\n| Platform | Ad Count | % of Total | Estimated Focus |\n|----------|----------|-----------|-----------------|\n| Meta (Facebook) | [N] | [X%] | [Awareness \u002F Retargeting] |\n| Meta (Instagram) | [N] | [X%] | [Visual \u002F younger audience] |\n| Google Search | [N] | [X%] | [Bottom-funnel capture] |\n| Google Display | [N] | [X%] | [Awareness \u002F retargeting] |\n| YouTube | [N] | [X%] | [Education \u002F awareness] |\n\n## Phase 5: Strategic Analysis\n\n### Creative Gap Analysis\n\nIdentify across all competitors:\n\n1. **Angles nobody is running** — Hook types absent from competitor ads = white space\n2. **Overcrowded angles** — If everyone leads with \"save time\", avoid it or be more specific\n3. **Format opportunities** — If no one is running video in your space, it may stand out\n4. **Underutilized proof** — Are competitors avoiding specific proof points you could own?\n5. **CTA patterns to test** — What CTAs do the longest-running ads use?\n\n### Vulnerability Analysis\n\nIdentify weaknesses in each competitor's ad strategy:\n\n| Vulnerability Type | Description |\n|-------------------|-------------|\n| **Message-LP mismatch** | Ad promises one thing, LP delivers another |\n| **Single-persona dependency** | All ads target the same persona — missing segments |\n| **Platform concentration** | Heavy on one platform, absent from others |\n| **No social proof** | Ads or LPs lack credibility markers |\n| **Weak CTA** | Asking for too much too soon (demo before value) |\n| **Generic positioning** | Claims anyone could make — not differentiated |\n| **Stale creative** | Same ads running unchanged for months — fatigue risk |\n\n### Historical Comparison (Deep Mode)\n\nIf Web Archive data exists for their landing pages:\n- Has their positioning changed in the last 6-12 months?\n- What campaigns did they retire? (Possible losers)\n- What campaigns have they scaled up? (Possible winners)\n\n## Phase 6: Output\n\n```markdown\n# Competitor Ad Intelligence Report — [DATE]\n\n## Coverage\n- Competitors analyzed: [list]\n- Meta ads collected: [N]\n- Google ads collected: [N]\n- Unique landing pages analyzed: [N]\n- Estimated active campaigns: [N]\n\n---\n\n## Executive Summary\n\n[3-5 sentence summary: What is the competitive ad landscape? What's working? Where are the gaps and vulnerabilities?]\n\n---\n\n## Meta Ad Analysis\n\n### Hook Distribution\n| Hook Type | [Comp1] | [Comp2] | [Comp3] |\n|-----------|---------|---------|---------|\n| Fear\u002FLoss | 40% | 10% | 0% |\n| Outcome | 30% | 50% | 60% |\n...\n\n### Top Performing Ads (Longest Running)\n**[Competitor] — [Ad Title\u002FHook]**\n> [Ad copy excerpt]\n- Format: [type]\n- CTA: [text]\n- Running since: [date]\n- Why it likely works: [analysis]\n\n---\n\n## Google Ad Analysis\n\n### Headline Patterns\n[Top headline structures with examples]\n\n### Most Common CTAs\n[ranked list]\n\n---\n\n## Campaign Breakdown\n\n### Campaign 1: [Inferred Campaign Name]\n- **Competitor:** [name]\n- **Ads in cluster:** [N]\n- **Platform(s):** [Meta \u002F Google \u002F Both]\n- **Strategic intent:** [Awareness \u002F Lead gen \u002F Competitive displacement \u002F etc.]\n- **Target persona:** [Description]\n- **Hook strategy:** [Type]\n- **Landing page:** [URL]\n  - Hero: \"[Headline text]\"\n  - CTA: \"[Button text]\"\n  - Message match: [Score\u002F10]\n- **Longevity:** [First seen date → status]\n- **A\u002FB tests detected:** [Yes\u002FNo — what they're testing]\n\n**Sample ad:**\n> **Headline:** [text]\n> **Body:** [text]\n> **CTA:** [button]\n> **Format:** [Image\u002FVideo\u002FCarousel]\n\n**Assessment:** [1-2 sentences — is this working? Why\u002Fwhy not?]\n\n### Campaign 2: ...\n\n---\n\n## Funnel Map\n\n```\n[Ad: Hook\u002FAngle] → [LP: \u002Flanding-page-url] → [CTA: Book Demo]\n                                               ↓\n[Ad: Different angle] → [LP: \u002Fsame-or-different] → [CTA: Free Trial]\n```\n\n---\n\n## Budget Allocation Estimate\n\n| Platform | Share | Focus Area |\n|----------|-------|-----------|\n| [Platform] | [X%] | [Intent] |\n\n---\n\n## Creative Gap Analysis\n\n### Angles Nobody Is Running\n1. [Angle] — Why it could work for you: [reasoning]\n2. [Angle] — ...\n\n### Overcrowded Angles (Avoid or Differentiate)\n- [Angle] — [N] of [N] competitors use this\n\n### Format White Space\n- [Format] is not being used by competitors on [platform]\n\n---\n\n## Vulnerability Report\n\n### 1. [Vulnerability]\n**Competitor:** [name]\n**Evidence:** [What we observed]\n**Your opportunity:** [How to exploit this gap]\n\n### 2. ...\n\n---\n\n## Recommended Counter-Plays\n\n### Counter-Play 1: [Name]\n- **Target their weakness:** [Which vulnerability]\n- **Your ad angle:** [Hook]\n- **Platform:** [Where to run]\n- **Proposed headline:** \"[headline]\"\n- **Proposed body:** \"[copy]\"\n- **LP strategy:** [What your landing page should emphasize]\n- **Why test this:** [rationale]\n\n### Counter-Play 2: ...\n```\n\n## Cost\n\n| Component | Cost |\n|-----------|------|\n| Ad library research (web_search) | Free |\n| Landing page fetching | Free |\n| Web Archive lookup (deep mode) | Free |\n| Analysis | Free (LLM reasoning) |\n| **Total** | **Free** |\n\n## Environment Variables\n\n- No API keys required. This skill uses publicly accessible ad libraries and web search.\n\n## Tools Used\n\n- **`web_search`** — query Meta Ad Library and Google Ads Transparency Center\n- **`fetch_webpage`** or **`curl`** — fetch and analyze landing pages\n\n## Trigger Phrases\n\n- \"What ads are [competitor] running?\"\n- \"Tear down [competitor]'s ad strategy\"\n- \"Audit the ad landscape for [product category]\"\n- \"Run ad intelligence for [competitors]\"\n- \"Find new paid ad angles we haven't tried\"\n- \"Reverse-engineer [competitor]'s paid funnel\"\n- \"Find weaknesses in [competitor]'s ad strategy\"\n- \"Deep competitive ad analysis on [competitor]\"\n",{"name":5,"license":15,"metadata":60,"description":7,"compatibility":64},{"author":61,"source":62,"version":63},"GooseWorks","https:\u002F\u002Fgithub.com\u002Fgooseworks-ai\u002Fgoose-skills","1.0","Cross-platform. Uses web search and public ad libraries (Meta Ad Library, Google Ads Transparency Center) only — no API keys or credentials required.","main","5269f7ea2d6c3a9bfda5ed878b6726cf509121fd","skills\u002Fcompetitor-ad-intelligence",5335,"https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot","https:\u002F\u002Fawesome-copilot.github.com\u002F","https:\u002F\u002Fgithub.com\u002Fgithub","https:\u002F\u002Fgithub.com\u002Fabout","How people build software.","2026-11-11 11:59:04",{"source":8,"skillName":5,"commands":76,"prompt":86,"zipAvailable":87},[77,80,83],{"tool":78,"command":79},"npx","npx skills add github\u002Fawesome-copilot --skill competitor-ad-intelligence",{"tool":81,"command":82},"bunx","bunx skills add github\u002Fawesome-copilot --skill competitor-ad-intelligence",{"tool":84,"command":85},"pnpm","pnpm dlx skills add github\u002Fawesome-copilot --skill competitor-ad-intelligence","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fcompetitor-ad-intelligence\u002FSKILL.md",true,[89,95,99],{"path":90,"resourceType":91,"resourceTypeDesc":92,"sizeBytes":93,"sourceHtmlUrl":94},"agents\u002Fopenai.yaml","REFERENCE","参考文档",102,"https:\u002F\u002Fgithub.com\u002Ftdortman\u002Fdotfiles\u002Fblob\u002Fmain\u002Fhome\u002Fdot_agents\u002Fskills\u002Fcodebase-design\u002Fagents\u002Fopenai.yaml",{"path":96,"resourceType":91,"resourceTypeDesc":92,"sizeBytes":97,"sourceHtmlUrl":98},"DEEPENING.md",2553,"https:\u002F\u002Fgithub.com\u002Ftdortman\u002Fdotfiles\u002Fblob\u002Fmain\u002Fhome\u002Fdot_agents\u002Fskills\u002Fcodebase-design\u002FDEEPENING.md",{"path":100,"resourceType":91,"resourceTypeDesc":92,"sizeBytes":101,"sourceHtmlUrl":102},"DESIGN-IT-TWICE.md",2665,"https:\u002F\u002Fgithub.com\u002Ftdortman\u002Fdotfiles\u002Fblob\u002Fmain\u002Fhome\u002Fdot_agents\u002Fskills\u002Fcodebase-design\u002FDESIGN-IT-TWICE.md",[104,136,164,192,224,240],{"skillNo":105,"name":106,"nameZh":6,"description":107,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":108,"categories":109,"keywords":116,"publishedAt":55},"01M70KXZNX9ES38N2A8M58ZZMZ","supabase-rls-policies","Write, review, and test Supabase Row Level Security (RLS) policies so that one user cannot read or change another user's rows. Use when creating or changing tables, policies, views, or security definer functions in a Supabase project, when reviewing a migration that touches RLS, or when asked to prove user isolation with pgTAP tests that sign in as two users.","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fsupabase-rls-policies\u002FSKILL.md",[110,113],{"categoryNo":111,"categoryName":112,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":114,"categoryName":115,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[117,118,119,120,121,35,122,123,124,125,126,127,128,129,130,131,132,133,134,135],"supabase","rls","supabase rls","supabase rls policies","project","review","change","read","write","security","isolation","tables","as","tests","prove","use","users","functions","with",{"skillNo":137,"name":138,"nameZh":6,"description":139,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":140,"categories":141,"keywords":143,"publishedAt":55},"01M70KWA5YWXDV6V8DZ19E3T2Y","skill-distribution-audit","Audit a skill collection before release or investigate installer omissions, archived\u002Ftemplate leakage, duplicate identities, and manifest drift. Reconcile the intended public source set, distribution manifest, and actual discovery output for a specified consumer version. Includes a deterministic set-comparison helper.","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fskill-distribution-audit\u002FSKILL.md",[142],{"categoryNo":114,"categoryName":115,"taxonomyType":21,"taxonomyTypeDesc":22},[144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163],"distribution","skill distribution audit","audit","SET","deterministic","installer","for","discovery","comparison","helper","manifest","version","collection","drift","output","investigate","duplicate","template","release","reconcile",{"skillNo":165,"name":166,"nameZh":6,"description":167,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":168,"sourceHtmlUrl":169,"categories":170,"keywords":174,"publishedAt":55},"01M70KCJPFVW7PPQ49CC5R8JGK","logicapps-custom-code-net10-migration","Migrate Azure Logic Apps Standard local-function custom-code projects from .NET 8 to .NET 10. Use for legacy Logic Apps custom-code workspace upgrades, project\u002Fpackage configuration, custom-worker settings, publication, and integrated VS Code debugging. Not for ordinary .NET applications, standalone Azure Functions, Consumption workflows, or cloud deployment.","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Flogicapps-custom-code-net10-migration\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Flogicapps-custom-code-net10-migration\u002FSKILL.md",[171],{"categoryNo":172,"categoryName":173,"taxonomyType":26,"taxonomyTypeDesc":27},"01JBSEEDCAT000000000000030","开发工程师",[175,176,177,178,179,180,150,121,181,182,183,184,185,186,187,132,188,189,190,191],"custom","code","logicapps custom code net10 migration","migration","projects","standalone","deployment","applications","local","azure","worker","upgrades","package","apps","Legacy","debugging","workflows",{"skillNo":193,"name":194,"nameZh":6,"description":195,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":196,"sourceHtmlUrl":197,"categories":198,"keywords":203,"publishedAt":55},"01M6AEBN37RQMXJ3298PEY7PG1","winmd-api-search","Find and explore Windows desktop APIs. Use when building features that need platform capabilities — camera, file access, notifications, UI controls, AI\u002FML, sensors, networking, etc. Discovers the right API for a task and retrieves full type details (methods, properties, events, enumeration values).","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fwinmd-api-search\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fwinmd-api-search\u002FSKILL.md",[199,202],{"categoryNo":200,"categoryName":201,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":172,"categoryName":173,"taxonomyType":26,"taxonomyTypeDesc":27},[204,51,43,205,206,207,208,209,210,211,212,213,214,215,216,35,217,218,219,220,221,150,222,223],"winmd api search","windows","desktop","file access","enumeration","ui","ml","file","networking","capabilities","notifications","explore","access","features","full","camera","events","platform","methods","controls",{"skillNo":225,"name":226,"nameZh":6,"description":227,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":228,"licenseFileUrl":229,"sourceHtmlUrl":230,"categories":231,"keywords":237,"publishedAt":55},"01M6AE571R3SC1ZGE202B3NB5S","resemble-detect","Deepfake detection and media safety — detect AI-generated audio, images, video, and text, trace synthesis sources, apply watermarks, verify speaker identity, and analyze media intelligence using Resemble AI","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fresemble-detect\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fresemble-detect\u002FSKILL.md",[232,233,236],{"categoryNo":200,"categoryName":201,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":234,"categoryName":235,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":114,"categoryName":115,"taxonomyType":21,"taxonomyTypeDesc":22},[238,147,211,49,239],"resemble detect","identity",{"skillNo":241,"name":242,"nameZh":6,"description":243,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":228,"licenseFileUrl":244,"sourceHtmlUrl":245,"categories":246,"keywords":251,"publishedAt":55},"01M6AE30BSK2HCY4TQQ22Z8JRD","quality-playbook","Run a complete quality engineering audit on any codebase. Derives behavioral requirements from the code, generates spec-traced functional tests, runs a three-pass code review with regression tests, executes a multi-model spec audit (Council of Three), and produces a consolidated bug report with TDD-verified patches. Finds the 35% of real defects that structural code review alone cannot catch. Works with any language. Trigger on 'quality playbook', 'spec audit', 'Council of Three', 'fitness-to-purpose', or 'coverage theater'.","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fquality-playbook\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fquality-playbook\u002FSKILL.md",[247,250],{"categoryNo":248,"categoryName":249,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000007","代码审查",{"categoryNo":114,"categoryName":115,"taxonomyType":21,"taxonomyTypeDesc":22},[252,253,254,255,176,122,9,146,256,257,49,258,259,260,261,262,263,264,265,266,267,268,130,269,270,271,272],"playbook","quality playbook","quality","code review","tdd","run","report","spec","bug report","council","engineering","functional","spec audit","bug","verified","multi-model","three","coverage","model","regression","structural"]