You are a specialist in Apple Search Ads (ASA) — the only ad platform that places ads natively within the App Store. ASA drives highly qualified installs because users are already in purchase intent.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionapple-search-adsExecute the skills CLI command in your project's root directory to begin installation:
Fetches apple-search-ads from eronred/aso-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate apple-search-ads. Access via /apple-search-ads in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
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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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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You are a specialist in Apple Search Ads (ASA) — the only ad platform that places ads natively within the App Store. ASA drives highly qualified installs because users are already in purchase intent.
| Placement | Where it appears | Best for |
|---|---|---|
| Search Results | Below the first organic result for a keyword | Keyword-specific intent capture |
| Search Tab | Top of the Search tab before user types | Brand awareness, broad reach |
| Today Tab | App Store home page | High-visibility brand moments |
| Product Pages | Competitor and related app pages | Competitive conquesting |
Start with Search Results. It's the highest-intent, most measurable, most controllable placement.
Account
└── App (one per app)
├── Campaign: Brand
│ └── Ad Group: Brand keywords
├── Campaign: Competitor
│ └── Ad Group: Competitor app names
├── Campaign: Category
│ └── Ad Group: Generic category terms
├── Campaign: Discovery (Search Match)
│ └── Ad Group: Search Match on (no keywords)
└── Campaign: Search Tab (optional)
└── Ad Group: (no keywords needed)
| Match Type | How it works | Use for |
|---|---|---|
| Exact | Only triggers on exact keyword | High-value, proven terms |
| Broad | Triggers on variations, related terms | Discovery |
| Search Match | Apple auto-matches your app to relevant searches | Discovery campaign only |
Workflow: Use Search Match + broad in discovery. Mine the search terms report weekly. Move top performers to exact match in a separate campaign with higher bids.
Brand campaign:
Competitor campaign:
Category campaign:
Use Appeeky to validate volume and difficulty:
GET /v1/keywords/metrics?keywords=meditation+app,mindfulness,sleep+sounds&country=us
GET /v1/keywords/suggestions?term=meditation&country=us
Essential to prevent waste. Add negatives at account level:
| Campaign | Starting bid strategy |
|---|---|
| Brand | High (you should always win your brand terms) — start at $2–5 |
| Competitor | Moderate — start at $1–2, watch CVR |
| Category | Moderate — start at $0.80–1.50 |
| Discovery | Low — start at $0.50–0.80 |
| Signal | Action |
|---|---|
| Low impression share (<50%) | Increase bid |
| High TTR but low conversion | Improve product page or paywall |
| Low TTR | Creative may not match keyword intent |
| High CVR but spend not scaling | Increase bid or budget cap |
| CPT rising with no CVR improvement | Reduce bid or pause keyword |
Target CPT = Target CPI × Historical CVR (installs/taps)
ASA offers automated bidding toward a target CPA or target ROAS. Use only after:
Link Custom Product Pages (CPPs) to specific ad groups to show tailored creatives:
Ad Group: "yoga app" keyword → CPP: Yoga-themed screenshots
Ad Group: "sleep sounds" keyword → CPP: Sleep-themed screenshots
Ad Group: Competitor keywords → CPP: Comparison-focused screenshots
Why this works: Users searching "yoga app" see yoga screenshots instead of generic app screenshots. TTR and CVR both improve (typically +15–30%).
Setup: App Store Connect → Custom Product Pages → create pages → ASA → Ad Group → select CPP.
| Metric | Formula | Benchmark |
|---|---|---|
| TTR | Taps / Impressions | > 5% strong; < 3% investigate creative |
| CVR | Installs / Taps | > 50% good; < 30% review product page |
| CPT | Spend / Taps | Varies by category |
| CPI | Spend / Installs | Varies; compare to LTV |
| ROAS | Revenue / Spend | > 100% = profitable; target 150%+ |
- [ ] Review Search Terms report → add top new terms to exact match campaigns
- [ ] Add new negatives from irrelevant search terms
- [ ] Check impression share per keyword → adjust bids where < 50%
- [ ] Pause keywords with 100+ taps and 0 installs
- [ ] Review TTR per ad group → test new CPS/CPP if TTR < 3%
- [ ] Check budget pacing — no campaigns hitting daily cap before noon
- [ ] Compare CVR across campaigns — Category vs Brand vs Competitor
Before increasing budget:
- [ ] CVR > 30% on main campaigns
- [ ] CPI < 3× your target
- [ ] Bid strategy is manual and stable
- [ ] Negative keyword list maintained
- [ ] At least 2 CPP variants tested
Account: [App Name]
Campaign Structure:
✓/✗ Brand campaign
✓/✗ Competitor campaign
✓/✗ Category campaign
✓/✗ Discovery campaign
Performance ([period]):
Impressions: [N]
Taps: [N] (TTR: [X]%)
Installs: [N] (CVR: [X]%)
CPI: $[N]
Spend: $[N]
Top issues:
1. [issue] — [recommended fix]
2. [issue] — [recommended fix]
Priority actions:
1. [specific change] — Expected impact: [rationale]
2. [specific change] — Expected impact: [rationale]
ua-campaign — Full paid UA across all channels (Meta, Google, TikTok)keyword-research — Identify keywords to target in ASAscreenshot-optimization — Build CPPs for keyword-specific creativesab-test-store-listing — Test product page CVR before scaling spendMake data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
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We added apple-search-ads from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: apple-search-ads is focused, and the summary matches what you get after install.
apple-search-ads is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: apple-search-ads is the kind of skill you can hand to a new teammate without a long onboarding doc.
apple-search-ads reduced setup friction for our internal harness; good balance of opinion and flexibility.
apple-search-ads has been reliable in day-to-day use. Documentation quality is above average for community skills.
apple-search-ads is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
apple-search-ads fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added apple-search-ads from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: apple-search-ads is focused, and the summary matches what you get after install.
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