Competitor ad intelligence
Skill ranbot-ai/awesome-skills/skills/competitor-ad-intelligence
Research public competitor ads, analyze creative patterns and landing pages, and produce an evidence-labeled strategic teardown.From its SKILL.md
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SKILL.md
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Competitor Ad Intelligence
Overview
Research competitor ads from Meta and Google, analyze creative patterns, map observable landing-page funnels, and produce a strategic teardown — hooks, formats, positioning bets, vulnerabilities, and counter-plays.
Core principle: A competitor's public ad portfolio is partial evidence about its growth strategy. Long-running ads can indicate continued investment, but public libraries do not expose conversion performance or spend. Separate observations from hypotheses, cite every observed ad or page, and label all performance and budget inferences explicitly.
When to Use This Skill
- "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:
- Competitor names + domains (e.g.,
apollo.io,clay.run) - Your product/domain — for comparison framing
- Channels: Meta only, Google only, or both? (default: both)
- Depth level:
- Standard: Ad scrape + creative analysis + landing page analysis
- Deep: Standard + historical comparison + funnel reconstruction + counter-plays
- Product category — helps frame analysis
- Known competitor landing pages? — any URLs already spotted in their ads
Phase 1: Research Meta Ads
For each competitor domain, research ads visible in Meta Ad Library and public search results.
Use web_search only to discover first-party library pages and candidate references:
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>
Prefer manual browser research. Use automated collection only when the platform expressly permits it and the user has authorized it; comply with current terms, robots directives, and rate limits. If the page is blocked, incomplete, dynamic-only, or requires authentication, report the coverage gap; do not bypass the control or invent missing ads or attributes.
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: Research Google Ads
For each competitor domain, research ads visible in 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>
Prefer manual browser research. Treat search snippets and third-party examples as secondary evidence and identify them as such. Use automated fetching only when permitted and authorized.
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 | |
|---|---|---|
| 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 mo
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.
Gives 0 of the 12 instructions most research analysis skills give in ~1.1k tokens
Counted across 1,063 of the 1,754 authors here whose files we hold, read 2026-08-07
- Generate a markdown reportin 32 of 1063, across 23 files
- Cite each claim's sourcein 30 of 1063, across 15 files
- Define the ideal customer profilein 20 of 1063, across 2 files
- Search for companies matching the criteriain 20 of 1063, across 2 files
- Assign a fit score from one to tenin 20 of 1063, across 2 files
- Analyze the codebase to understand the productin 19 of 1063, across 1 file
- Ask clarifying questions about the value propositionin 19 of 1063, across 1 file
- Look for signals of immediate needin 19 of 1063, across 1 file
- Identify the target decision maker rolein 19 of 1063, across 1 file
- Suggest a personalized contact strategyin 19 of 1063, across 1 file
- Provide conversation starters for outreachin 19 of 1063, across 1 file
- Format results in a scannable markdown templatein 19 of 1063, across 1 file
Said here and by no other author read
- collect ad copy and visual format
- extract CTA text and landing page URL
- record active ad duration and platforms
- cluster headlines by hook type
- count ads per hook type per competitor
- categorize unique CTAs found
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.