app-ads▌
kostja94/marketing-skills · updated Apr 8, 2026
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Guides app advertising: app install campaigns, user acquisition (UA), and in-app promotion. Use when promoting mobile apps (iOS, Android); conversion = install or in-app action, not landing page.
Paid Ads: App Ads
Guides app advertising: app install campaigns, user acquisition (UA), and in-app promotion. Use when promoting mobile apps (iOS, Android); conversion = install or in-app action, not landing page.
When invoking: On first use, if helpful, open with 1–2 sentences on what this skill covers and why it matters, then provide the main output. On subsequent use or when the user asks to skip, go directly to the main output.
Key Platforms
| Platform | Best for | Conversion |
|---|---|---|
| Google App Campaigns | Android + iOS; automated across Search, YouTube, Display, Play, Discover | Install, in-app event |
| Apple Search Ads (ASA) | iOS only; high-intent App Store search | Install |
| Meta App Install | Facebook/Instagram; demand gen for apps | Install, in-app event |
| TikTok App Install | Younger users; viral creative | Install |
Google App Campaigns
- Reach: Search, YouTube, Display, Google Play, Discover
- Bidding: Maximize Conversions (automated) or Target CPI/CPA (30+ conversions/week)
- Creative: Provide diverse assets (videos, images, text); algorithm tests combinations
- iOS: SKAdNetwork; conversion value mapping; Firebase for in-app events
- Bid–budget ratio: ≥10× for CPI, ≥15× for CPA
Apple Search Ads
- Placements: App Store search results, Today tab, Search tab, product pages
- Modes: Basic (automated) or Advanced (keywords, audiences, bids)
- Audience: High-intent users actively searching in App Store
- ASO benefit: Can improve keyword rankings as secondary effect
Metrics
| Metric | Use |
|---|---|
| CPI | Cost per install |
| CPA | Cost per acquisition (in-app action) |
| LTV | Lifetime value; iOS often higher than Android |
| Retention | D1, D7, D30; quality signal |
iOS vs Android: iOS typically higher LTV, higher CPI; Android greater scale, lower CPI.
Tracking
- Firebase: In-app events, audiences, value-based optimization (Google)
- SKAdNetwork: iOS attribution; configure conversion value mapping
- UTM: Use
utm_medium=apporcpcwithutm_sourcefor app campaigns in GA4
Pre-Launch Checklist
- App Store / Play Store listing optimized (ASO)
- Firebase or equivalent connected; in-app events defined
- Creative assets (video, images, text) prepared
- Conversion events (install, signup, purchase) configured
- Bid–budget ratio meets minimum (10× CPI, 15× CPA)
Related Skills
- paid-ads-strategy: Ad formats by medium; when to use app vs web
- analytics-tracking: In-app events; conversion setup
- traffic-analysis: UTM for app campaigns; attribution
How to use app-ads on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add app-ads
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches app-ads from GitHub repository kostja94/marketing-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate app-ads. Access the skill through slash commands (e.g., /app-ads) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
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Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★32 reviews- ★★★★★Ishan Abbas· Dec 28, 2024
app-ads reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Zara Jackson· Dec 20, 2024
I recommend app-ads for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Pratham Ware· Dec 8, 2024
We added app-ads from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Sakshi Patil· Nov 27, 2024
app-ads fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Ava Thomas· Nov 27, 2024
app-ads has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Mateo Ndlovu· Nov 19, 2024
Registry listing for app-ads matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Tariq Gupta· Nov 11, 2024
Keeps context tight: app-ads is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Chaitanya Patil· Oct 18, 2024
app-ads is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Ava Li· Oct 18, 2024
Useful defaults in app-ads — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Noor Robinson· Oct 10, 2024
Keeps context tight: app-ads is the kind of skill you can hand to a new teammate without a long onboarding doc.
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