Marketing Os
Yuzzyuk/marketing-os
A complete marketing department in one skill. An agent skill from Yuzzyuk/marketing-os.
A skill your agent uses when the user asks to analyze, tear down, or reverse-engineer a competitor's paid ads.
Install Competitor Ad Intelligence
$ npx skills add github/awesome-copilot --skill competitor-ad-intelligence -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install github/awesome-copilot competitor-ad-intelligence --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/github/awesome-copilot.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/competitor-ad-intelligence .claude/skills/competitor-ad-intelligence && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "competitor-ad-intelligence" agent skill from https://github.com/github/awesome-copilot/tree/main/skills/competitor-ad-intelligence into .claude/skills/competitor-ad-intelligence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "competitor-ad-intelligence", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/github/awesome-copilot/tree/main/skills/competitor-ad-intelligenceType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add github/awesome-copilot --skill competitor-ad-intelligence -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install github/awesome-copilot competitor-ad-intelligence --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/github/awesome-copilot.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/competitor-ad-intelligence .agents/skills/competitor-ad-intelligence && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "competitor-ad-intelligence" agent skill from https://github.com/github/awesome-copilot/tree/main/skills/competitor-ad-intelligence into .agents/skills/competitor-ad-intelligence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "competitor-ad-intelligence", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add github/awesome-copilot --skill competitor-ad-intelligence -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install github/awesome-copilot competitor-ad-intelligence --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/github/awesome-copilot.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/competitor-ad-intelligence .cursor/skills/competitor-ad-intelligence && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "competitor-ad-intelligence" agent skill from https://github.com/github/awesome-copilot/tree/main/skills/competitor-ad-intelligence into .cursor/skills/competitor-ad-intelligence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "competitor-ad-intelligence", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/github/awesome-copilot.git --path skills/competitor-ad-intelligence--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add github/awesome-copilot --skill competitor-ad-intelligence -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install github/awesome-copilot competitor-ad-intelligence --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/github/awesome-copilot.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/competitor-ad-intelligence .gemini/skills/competitor-ad-intelligence && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "competitor-ad-intelligence" agent skill from https://github.com/github/awesome-copilot/tree/main/skills/competitor-ad-intelligence into .gemini/skills/competitor-ad-intelligence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "competitor-ad-intelligence", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install github/awesome-copilot competitor-ad-intelligenceInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add github/awesome-copilot --skill competitor-ad-intelligence -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/github/awesome-copilot.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/competitor-ad-intelligence .github/skills/competitor-ad-intelligence && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "competitor-ad-intelligence" agent skill from https://github.com/github/awesome-copilot/tree/main/skills/competitor-ad-intelligence into .github/skills/competitor-ad-intelligence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "competitor-ad-intelligence", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add github/awesome-copilot --skill competitor-ad-intelligence -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install github/awesome-copilot competitor-ad-intelligence --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/github/awesome-copilot.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/competitor-ad-intelligence .opencode/skills/competitor-ad-intelligence && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "competitor-ad-intelligence" agent skill from https://github.com/github/awesome-copilot/tree/main/skills/competitor-ad-intelligence into .opencode/skills/competitor-ad-intelligence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "competitor-ad-intelligence", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
competitor-ad-intelligence- GitHub stars
- 40k
- Used in
- 1 other repo
- Token cost
- ~3.2k tokens
- SKILL.md length
- 1,167 words
- Files
- 1
- Skills in repo
- 417
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when the user asks to analyze, tear down, or reverse-engineer a competitor's paid ads.
- Works in 7 steps: Intake → Scrape Meta Ads → Scrape Google Ads → …
- The user asks to analyze
- SKILL.md covers When to Use, Phase 0: Intake, Phase 1: Scrape Meta Ads and Phase 2: Scrape Google Ads, plus 8 more sections
- Reaches facebook.com and adstransparency.google.com
What it does
Competitor Ad Intelligence is an agent skill from github/awesome-copilot, published by the product's own GitHub organization. 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.
Its SKILL.md is about 3.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Cross-platform. Uses web search and public ad libraries (Meta Ad Library, Google Ads Transparency Center) only — no API keys or credentials required.
It sits in Marketing & SEO, covering Paid advertising, Web scraping and Competitor analysis. The repository describes itself as: Community-contributed instructions, agents, skills, and configurations to help you make the most of GitHub Copilot. The licence is MIT.
When your agent uses it
- The user asks to analyze
- Reverse-engineer a competitors paid ads
- Prompts like what ads is [competitor] running
- Tear down their ad strategy
Example prompts
- “s paid ads. Trigger for prompts like”
- “tear down their ad strategy”
- “competitor ad analysis”
- “/competitor-ad-intelligence”
Requirements
- Compatibility (from SKILL.md): Cross-platform. Uses web search and public ad libraries (Meta Ad Library, Google Ads Transparency Center) only — no API keys or credentials required.
Workflow steps
7 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 727ff2e. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
facebook.comadstransparency.google.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Compatibility
Cross-platform. Uses web search and public ad libraries (Meta Ad Library, Google Ads Transparency Center) only — no API keys or credentials required.
From compatibility in the SKILL.md frontmatter.
Context cost
Competitor Ad Intelligence loads about 3.2k tokens when it runs. Until then it costs about 102 tokens; SKILL.md has 1,167 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from github/awesome-copilot at commit 727ff2e, republished under its MIT licence (© github). 1,167 words, ~3,239 tokens.
Download SKILL.mdSave it as
.claude/skills/competitor-ad-intelligence/SKILL.md (or your agent's skills folder).- 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.
- compatibility
- Cross-platform. Uses web search and public ad libraries (Meta Ad Library, Google Ads Transparency Center) only — no API keys or credentials required.
- license
- MIT
- metadata.version
- 1.0
- metadata.author
- GooseWorks
- metadata.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:
- 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: 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 examplesYou 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_searchas 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 examplesYou 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 | |
|---|---|---|
| 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
Show full SKILL.md (456 more words)Show less
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:
- Angles nobody is running — Hook types absent from competitor ads = white space
- Overcrowded angles — If everyone leads with "save time", avoid it or be more specific
- Format opportunities — If no one is running video in your space, it may stand out
- Underutilized proof — Are competitors avoiding specific proof points you could own?
- 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
# 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 Centerfetch_webpageorcurl— 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]"
© github, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/competitor-ad-intelligence of github/awesome-copilot.
Open the folder on GitHubat commit 727ff2e
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in github/awesome-copilot, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Competitor Ad Intelligence next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Competitor Ad Intelligence this skillgithub/awesome-copilot | 40k | 1 repos | ~3.2k | Automated safety check: Pass | MIT | |
| Marketing OsYuzzyuk/marketing-os | 535 | — | ~2.5k | Automated safety check: Pass | MIT | |
| Competitor Teardownirinabuht12-oss/marketing-skills | 3.8k | — | ~1.6k | Automated safety check: Pass | None | |
| Competitor Researcherhanzili/hanzi-browse | 177 | — | ~4.7k | Automated safety check: Pass | Custom licence | |
| Competitive Teardownalirezarezvani/claude-skills | 28k | 2 repos | ~2.1k | Automated safety check: Pass | MIT | |
| Run Competitive IntelOthmane-Khadri/YALC-the-GTM-operating-system | 317 | — | ~445 | Automated safety check: Notes | MIT |
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Questions about Competitor Ad Intelligence
What does Competitor Ad Intelligence do?
A skill your agent uses when the user asks to analyze, tear down, or reverse-engineer a competitor's paid ads. Competitor Ad Intelligence is an agent skill from github/awesome-copilot, published by the product's own GitHub organization. Use this skill when the user asks to analyze, tear down, or reverse-engineer a competitor's paid ads.
When should I use Competitor Ad Intelligence?
Competitor Ad Intelligence fits situations like: the user asks to analyze; reverse-engineer a competitors paid ads; prompts like what ads is [competitor] running; tear down their ad strategy.
How do I install Competitor Ad Intelligence in Claude Code?
Run `npx skills add github/awesome-copilot --skill competitor-ad-intelligence -a claude-code`. Or copy the skill folder (skills/competitor-ad-intelligence in github/awesome-copilot) into .claude/skills/competitor-ad-intelligence in your project. Claude Code loads it when a task matches its description.
How do I install Competitor Ad Intelligence in Codex?
Run `npx skills add github/awesome-copilot --skill competitor-ad-intelligence -a codex`. Or copy the skill folder (skills/competitor-ad-intelligence in github/awesome-copilot) into .agents/skills/competitor-ad-intelligence in your project. Codex loads it when a task matches its description.
Can I use Competitor Ad Intelligence in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add github/awesome-copilot --skill competitor-ad-intelligence -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/competitor-ad-intelligence, .gemini/skills/competitor-ad-intelligence, .github/skills/competitor-ad-intelligence and .opencode/skills/competitor-ad-intelligence in your project.
What does Competitor Ad Intelligence need to run?
SKILL.md names no scripts, command-line tools or credentials: Competitor Ad Intelligence is instructions for the agent only. Compatibility (from SKILL.md): Cross-platform. Uses web search and public ad libraries (Meta Ad Library, Google Ads Transparency Center) only — no API keys or credentials required..
Does Competitor Ad Intelligence access the network?
SKILL.md names 2 domains. In commands or code: facebook.com and adstransparency.google.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.
Is Competitor Ad Intelligence safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Competitor Ad Intelligence use?
Competitor Ad Intelligence is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Competitor Ad Intelligence use?
About 3.2k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Competitor Ad Intelligence?
Skills that share tags, products or a category with Competitor Ad Intelligence: Marketing Os (Yuzzyuk/marketing-os, 535 stars), Competitor Teardown (irinabuht12-oss/marketing-skills, 3.8k stars), Competitor Researcher (hanzili/hanzi-browse, 177 stars) and Competitive Teardown (alirezarezvani/claude-skills, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Competitor Ad Intelligence?
github (a GitHub organization, an official publisher) maintains it in github/awesome-copilot, which has 39,748 GitHub stars. The repository holds 417 skills in this directory. The repository was last updated on October 7, 2026.
Source: github/awesome-copilot on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.