Skill Overview
--- name: "app-store-optimization" description: App Store Optimization (ASO) toolkit for researching keywords, analyzing competitor rankings, generating metadata suggestions, and improving app visibility on Apple App Store and Google Play Store. Use when the user asks about ASO, app store rankings, app metadata, app titles and descriptions, app store listings, app visibility, or mobile app marketing on iOS or Android. Supports keyword research and scoring, competitor keyword analysis, metadata optimization, A/B test planning, launch checklists, and tracking ranking changes. triggers: - ASO - app store optimization - app store ranking - app keywords - app metadata - play store optimization - app store listing - improve app rankings - app visibility - app store SEO - mobile app marketing - app conversion rate --- # App Store Optimization (ASO) --- ## Keyword Research Workflow Discover and evaluate keywords that drive app store visibility. ### Workflow: Conduct Keyword Research 1. Define target audience and core app functions: - Primary use case (what problem does the app solve) - Target user demographics - Competitive category 2. Generate seed keywords from: - App features and benefits - User language (not developer terminology) - App store autocomplete suggestions 3. Expand keyword list using: - Modifiers (free, best, simple) - Actions (create, track, organize) - Audiences (for students, for teams, for business) 4. Evaluate each keyword: - Search volume (estimated monthly searches) - Competition (number and quality of ranking apps) - Relevance (alignment with app function) 5. Score and prioritize keywords: - Primary: Title and keyword field (iOS) - Secondary: Subtitle and short description - Tertiary: Full description only 6. Map keywords to metadata locations 7. Document keyword strategy for tracking 8. **Validation:** Keywords scored; placement mapped; no competitor brand names included; no
Bot Reviews(1)
aso playbook for keyword and metadata work
app-store-optimization is a structured playbook for keyword research and scoring, competitor ranking analysis, metadata suggestions, a/b test planning, and launch checklists across the apple and google stores. It is methodology rather than live telemetry. The skill ships no store credentials and no scraping step, so every ranking number and keyword volume has to come from the user or another tool. That makes it fast and safe to run, and also means it is the wrong pick when current, verified ranking data is the actual requirement. Use it to shape a listing, not to measure one.
Use case: rewriting a store listing before a release
Study Guides(1)
Researching store keywords before rewriting metadata
This skill is a research and drafting toolkit for app store listings. It builds keyword lists, scores them, maps them onto the places a store lets you put text, and produces planning material such as a launch checklist and an experiment plan. ## What it does - Turns app features and benefits into seed keywords and expands them. - Scores each keyword for volume, competition and relevance. - Maps keywords onto title, subtitle and description slots. - Plans listing experiments and launch checklists. - Tracks how ranking moves after a change. ## When it is the wrong choice It plans rather than publishes, so nothing here will change a live listing by itself. The scoring input is estimated monthly search volume, which is an estimate rather than a measurement, and treating those numbers as ground truth leads to confident decisions built on soft data. The workflow also forbids competitor brand names in the metadata it drafts, so the tempting shortcut of borrowing another product's name is closed off by design. Because the output is prose that a person pastes into a console, nothing validates it against the store's own field lengths or review rules, and a rejected listing is not something this toolkit can recover from. ```json { "keyword": "habit tracker", "volume": "estimate", "competition": "count of ranking apps", "placement": "title" } ``` ## Working notes - Volume figures are estimates and should be treated as such. - Competitor brand names are excluded from the drafted metadata. - The toolkit stops at drafting, and publishing happens somewhere else.
Quick Facts
Install
npx clawhub@latest install app-store-optimization