keyword-research▌
eronred/aso-skills · updated Apr 8, 2026
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.
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
Ratings
4.5★★★★★10 reviews- ★★★★★Shikha Mishra· Oct 10, 2024
keyword-research is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Piyush G· Sep 9, 2024
Keeps context tight: keyword-research is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Chaitanya Patil· Aug 8, 2024
Registry listing for keyword-research matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Sakshi Patil· Jul 7, 2024
keyword-research reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Ganesh Mohane· Jun 6, 2024
I recommend keyword-research for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Oshnikdeep· May 5, 2024
Useful defaults in keyword-research — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Dhruvi Jain· Apr 4, 2024
keyword-research has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Rahul Santra· Mar 3, 2024
Solid pick for teams standardizing on skills: keyword-research is focused, and the summary matches what you get after install.
- ★★★★★Pratham Ware· Feb 2, 2024
We added keyword-research from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Yash Thakker· Jan 1, 2024
keyword-research fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.