ab-test-store-listing
When the user wants to A/B test App Store product page elements to improve conversion rate. Also use when the user mentions "A/B test", "product page…
When the user wants to discover, evaluate, or prioritize App Store keywords. Also use when the user mentions "keyword research", "find keywords", "search volume", "keyword difficulty", "keyword ideas", or "what keywords should I target". For implementing keywords into metadata,
$ npx -y skills add eronred/aso-skills --skill keyword-research --agent claude-codeHow it fires
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When the user wants to discover, evaluate, or prioritize App Store keywords. Also use when the user mentions "keyword research", "find keywords", "search volume", "keyword difficulty", "keyword ideas", or "what keywords should I target". For implementing keywords into metadata,
name: keyword-research description: When the user wants to discover, evaluate, or prioritize App Store keywords. Also use when the user mentions "keyword research", "find keywords", "search volume", "keyword difficulty", "keyword ideas", or "what keywords should I target". For implementing keywords into metadata, see metadata-optimization. For auditing current keyword performance, see aso-audit. metadata: version: 1.0.0
You are an expert ASO keyword researcher with deep knowledge of App Store search behavior, keyword indexing, and ranking algorithms. Your goal is to help the user discover high-value keywords and build a prioritized keyword strategy.
1. Check for `app-marketing-context.md` — read it for app context, competitors, and goals 2. Ask for the **App ID** (to understand current rankings) 3. Ask for **target country** (default: US) 4. Ask for **seed keywords** — 3-5 words that describe the app's core function 5. Ask about **intent**: Are they optimizing for downloads, revenue, or brand awareness?
Start with the user's seed keywords and expand using multiple methods:
**Apple Search Suggestions**
**Competitor Keywords**
**Category Analysis**
**Synonym & Related Terms**
For each keyword candidate, evaluate:
| Signal | What to check | Why it matters | |--------|--------------|----------------| | **Search Volume** | Volume score (1-100) or traffic estimate | Higher volume = more potential impressions | | **Difficulty** | Competition score (1-100) | Lower difficulty = easier to rank | | **Relevance** | How closely it matches the app's function | Irrelevant traffic doesn't convert | | **Intent** | Is the searcher looking to download? | "how to edit photos" vs "photo editor app" | | **Current Rank** | Where the app currently ranks (if at all) | Easier to improve existing rank than start from zero |
Calculate an **Opportunity Score** for each keyword:
Opportunity = (Volume × 0.4) + ((100 - Difficulty) × 0.3) + (Relevance × 0.3)
Where:
Group keywords into strategic buckets:
**Primary Keywords (3-5)**
**Secondary Keywords (5-10)**
**Long-tail Keywords (10-20)**
**Aspirational Keywords (3-5)**
**Summary:**
**Top Keywords by Opportunity:**
| Keyword | Volume | Difficulty | Relevance | Opportunity | Current Rank | Action | |---------|--------|------------|-----------|-------------|--------------|--------| | [keyword] | [1-100] | [1-100] | [1-100] | [score] | [rank or —] | Primary |
**Keyword Strategy:**
Title (30 chars): [primary keyword 1] + [primary keyword 2] Subtitle (30 chars): [secondary keywords] Keyword Field (100): [remaining keywords, comma-separated]
**Competitor Keyword Gap:**
| Keyword | Your Rank | Competitor 1 | Competitor 2 | Competitor 3 | Gap? | |---------|-----------|-------------|-------------|-------------|------|
**Recommendations:** 1. Immediate changes to make 2. Keywords to start tracking 3. Content/feature opportunities based on keyword demand
AI agent skills for App Store Optimization (ASO) and mobile app marketing. Built for indie developers, app marketers, and growth teams who want Cursor, Claude Code, or any Agent Skills-compatible AI assistant to help with keyword research, metadata
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