keyword-research
Skill2.2k starsChanged 9 months agoMITView on GitHub
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.
54 other projects use a version of this, 2 of them edited.
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Quiet since March.thin dataabout the whole repository
Most recently taken up by
- oivanfelipe/claude-skillstheir own version, first seen Nov 8, 2026
- kostja94/marketing-skillstheir own version, first seen Nov 8, 2026
- kristian-presso/claude-marketing-skillstheir own version, first seen Nov 8, 2026
- foverse/seoversetheir own version, first seen Nov 8, 2026
- AppKittie/aso-mcp-skillsedited, first seen Nov 8, 2026
- MoizIbnYousaf/marketing-clitheir own version, first seen Nov 1, 2026
Who's talking about Eronred/aso-skills
The biggest 1 of 1 mention linking to the repository that our crawl found. Each line is their own headline.
Used with
Projects with it also use link-prospecting, seo-project-setup and 8 more.
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akii-technologies-ltdSkillkeyword-clustering
Cluster and organize keywords into topical groups for SEO. Use when the user asks to "cluster keywords", "group keywords", "organize keywords", "keyword mapping", "topic clusters", "keyword grouping", "build a content plan", "pillar pages", "topical authority", "semantic clustering", or pastes a list of keywords.
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opencueSkillserp-analysis
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Also in 6 projects that use this
- +5 more from Jwuthri
Other versions54 projects use a version of this.
Word for word · 2
- appeeky/aso-skills★ 2.2k100% same
- Kungfookenny123/aso-skills★ 2100% same
Edited · 2
- AppKittie/aso-mcp-skills★ 843% same
- Nirusan/claude-config★ 743% same
Wrote their own version · 50
- every-app/open-seo★ 27ksame name
- Ryze-AI-Adgent/open-seo-mcp-skills★ 8.4ksame name
- nowork-studio/toprank★ 4.1ksame name
- nowork-studio/notfair-plugin★ 4.1ksame name
- Jwuthri/Tracely-ai★ 1.3ksame name
- VladSez/easy-invoice-pdf★ 1.1ksame name
- kostja94/marketing-skills★ 1.1ksame name
- liangdabiao/amazon-sorftime-research-MCP-skill★ 1.1ksame name
- jwuthri-cloud/Tracely-ai★ 979same name
- indranilbanerjee/digital-marketing-pro★ 934same name
40 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository41 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .claude/CLAUDE.mdCLAUDE.md
- ab-test-store-listingSkill
- android-asoSkill
- app-analyticsSkill
- app-clipsSkill
- app-icon-optimizationSkill
- app-launchSkill
- apple-search-adsSkill
- app-marketing-contextSkill
- app-preview-videoSkill
- app-rejection-recoverySkill
- app-store-featuredSkill
- asc-metricsSkill
- aso-auditSkill
- aso-routerSkill
- attribution-setupSkill
- category-positioningSkill
- competitor-analysisSkill
- competitor-trackingSkill
- crash-analyticsSkill
- creator-ugc-marketingSkill
- custom-product-pagesSkill
- in-app-eventsSkill
- localizationSkill
- market-moversSkill
- market-pulseSkill
- metadata-optimizationSkill
- monetization-strategySkill
- onboarding-optimizationSkill
- paywall-optimizationSkill
- press-and-prSkill
- rating-prompt-strategySkill
- referral-programSkill
- retention-optimizationSkill
- review-managementSkill
- screenshot-optimizationSkill
- seasonal-asoSkill
- subscription-lifecycleSkill
- ua-campaignSkill
- web-to-app-funnelSkill
The file
We split this skill into the rules it gives an agent
10 rules. 0 are common, 9 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 48 edited versions we read keep these.
9
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 14
Check for app-marketing-context.md — read it for app context, competitors, and goals
- Distinctive: line 15
Ask for the App ID (to understand current rankings)
- Distinctive: line 16
Ask for target country (default: US)
- Distinctive: line 17
Ask for seed keywords — 3-5 words that describe the app's core function
- Distinctive: line 18
Ask about intent: Are they optimizing for downloads, revenue, or brand awareness?
- Distinctive: line 24
Start with the user's seed keywords and expand using multiple methods:
- Distinctive: line 27
Use each seed keyword to get autocomplete suggestions
- Distinctive: line 34
Look for keywords where competitors rank poorly (opportunity)
- Distinctive: line 42
Consider how users actually describe the problem (not the solution)
- Distinctive: line 76
Must appear in title or subtitle
“Common” is measured: kept by at least 6 in 10 of the 48 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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
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