Install Keyword Research
Pick your agent. Every command is ready to paste.
npx skills add appeeky/aso-skills --skill keyword-researchThe open skills CLI detects your agents (Claude Code, Cursor, Codex and 70+ more) and installs to the right folder. Add -g to install globally.
01
Install it
Run the command above, or upload the folder in Claude.
02
Ask naturally
Describe the task. Your agent loads keyword-research when the request matches its description.
03
Name it if needed
If it does not trigger, say “use the keyword-research skill”. In Codex, type $keyword-research.
Keyword Research
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.
Initial Assessment
- Check for
app-marketing-context.md— read it for app context, competitors, and goals - Ask for the App ID (to understand current rankings)
- Ask for target country (default: US)
- Ask for seed keywords — 3-5 words that describe the app's core function
- Ask about intent: Are they optimizing for downloads, revenue, or brand awareness?
Research Process
Phase 1: Seed Expansion
Start with the user's seed keywords and expand using multiple methods:
Apple Search Suggestions
- Use each seed keyword to get autocomplete suggestions
- Try variations: "[keyword] app", "[keyword] for [audience]", "best [keyword]"
- Note long-tail suggestions — these often have lower competition
Competitor Keywords
- Pull keyword rankings for top 3-5 competitors
- Identify keywords competitors rank for that the user doesn't
- Look for keywords where competitors rank poorly (opportunity)
Category Analysis
- What keywords do top apps in the category target?
- Are there category-specific terms the user is missing?
Synonym & Related Terms
- Generate synonyms and related terms for each seed keyword
- Consider how users actually describe the problem (not the solution)
- Think about misspellings and abbreviations users might search
Phase 2: Keyword Evaluation
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 |
Phase 3: Opportunity Scoring
Calculate an Opportunity Score for each keyword:
Opportunity = (Volume × 0.4) + ((100 - Difficulty) × 0.3) + (Relevance × 0.3)
Where:
- Volume: 1-100 scale
- Difficulty: 1-100 scale (inverted — lower difficulty = higher score)
- Relevance: 1-100 scale (manual assessment)
Phase 4: Keyword Grouping
Group keywords into strategic buckets:
Primary Keywords (3-5)
- Highest opportunity score
- Must appear in title or subtitle
- These define your core positioning
Secondary Keywords (5-10)
- Good opportunity but lower priority
- Target in subtitle and keyword field
- May rotate based on performance
Long-tail Keywords (10-20)
- Lower volume but very specific intent
- Fill remaining keyword field space
- Often easier to rank for
Aspirational Keywords (3-5)
- High volume, high difficulty
- Long-term targets as the app grows
- Track but don't sacrifice primary keywords for these
Output Format
Keyword Research Report
Summary:
- Total keywords analyzed: [N]
- High-opportunity keywords found: [N]
- Estimated total monthly search volume: [N]
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:
- Immediate changes to make
- Keywords to start tracking
- Content/feature opportunities based on keyword demand
Tips for the User
- Don't repeat keywords across title, subtitle, and keyword field — Apple indexes each field separately
- Use singular forms — Apple automatically indexes both singular and plural
- No spaces after commas in the keyword field — save characters
- Avoid "app" and category names — Apple already knows your category
- Update quarterly — Search trends change with seasons and culture
- Track weekly — Monitor rank changes to measure impact
Related Skills
metadata-optimization— Implement the keyword strategy into actual metadataaso-audit— Broader audit that includes keyword performancecompetitor-analysis— Deep dive into competitor keyword strategieslocalization— Keyword research for international markets
Tips for Keyword Research
- • Start a fresh session after installing so your agent picks up the new skill.
- • It is part of a pack with 30 skills. Install only the ones you need with --skill to keep triggers precise.
- • If two skills overlap, mention the one you want by name.
Questions about Keyword Research
What does the Keyword Research skill do?
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.
How do I install Keyword Research?
Run "npx skills add appeeky/aso-skills --skill keyword-research" in your project. The skills CLI installs it for Claude Code, Cursor, Codex and 70+ other agents. In Claude on the web, upload the skill folder as a ZIP under Customize > Skills.
Does Keyword Research work in Cursor and Codex?
Yes. Keyword Research uses the open SKILL.md format, so it works in Claude Code, Claude, Cursor, OpenAI Codex, Gemini CLI, GitHub Copilot and other agents that support agent skills.
Is Keyword Research free?
Keyword Research is open source on GitHub under the MIT license. It is free to install; check the license before commercial use.
Who made Keyword Research?
Keyword Research is published by appeeky in the appeeky/aso-skills repository, together with 29 other skills.
