This skill enables comprehensive Apple App Store Optimization (ASO) analysis and metadata generation. Analyze existing app listings, generate optimized metadata following Apple's guidelines and character limits, provide competitive insights, and recommend screenshot storyboard strategies.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionapp-store-asoExecute the skills CLI command in your project's root directory to begin installation:
Fetches app-store-aso from timbroddin/app-store-aso-skill and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate app-store-aso. Access via /app-store-aso in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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This skill enables comprehensive Apple App Store Optimization (ASO) analysis and metadata generation. Analyze existing app listings, generate optimized metadata following Apple's guidelines and character limits, provide competitive insights, and recommend screenshot storyboard strategies.
When a user requests ASO optimization or metadata review:
Analyze the App Context
Load ASO Knowledge Base
references/aso_learnings.md for comprehensive ASO best practicesGenerate Optimized Metadata
Validate Character Counts
scripts/validate_metadata.py to verify all metadata meets Apple's requirementsProvide Screenshot Strategy
Critical Limits to Validate:
After generating recommendations, always validate using the validation script:
python scripts/validate_metadata.py
The script will:
Integration Pattern:
Structure recommendations as:
App Name (X/30 characters) [optimized name]
Subtitle (X/30 characters) [optimized subtitle]
Promotional Text (X/170 characters) [promotional text]
Keywords (X/100 characters) [keyword,list,no,spaces]
Description (X/4000 characters) [full description]
[Key insights and positioning recommendations]
[Ordered list of screenshot recommendations with messaging]
[Output from validation script showing compliance]
Krankie is an agent-first CLI tool for tracking App Store keyword rankings. Use it to monitor keyword performance, track ranking changes over time, and inform ASO optimization decisions with real data.
bun install -g krankie
# or run directly
bunx krankie
App Management:
# Search for apps
krankie app search "<query>" --platform ios
# Add an app to track
krankie app create <app_id> --platform ios
# List tracked apps
krankie app list
Keyword Tracking:
# Add keywords to track for an app
krankie keyword add <app_id> "<keyword>" --store us
# List tracked keywords
krankie keyword list
Ranking Checks:
# Run ranking checks for all tracked keywords
krankie check run
# View current rankings
krankie rankings
# See biggest movers (gains/losses)
krankie rankings movers
# View ranking history for a keyword
krankie rankings history <keyword_id>
# Check status of last run
krankie check status
Automation:
# Install daily cron job (default: 6 AM)
krankie cron install --hour 6
# Check cron status
krankie cron status
All commands support --json flag for structured output:
krankie rankings --json
krankie app list --json
Get agent-friendly instructions:
krankie instructions --format json
~/.krankie/krankie.db (SQLite)--force to override~/.krankie/check.logkrankie rankings to establish baseline keyword positionskrankie rankings movers to measure impactkrankie rankings history to identify patternsPython script that validates App Store metadata against Apple's character limits. Provides interactive validation with clear pass/fail indicators.
Comprehensive ASO knowledge base containing optimization strategies, competitive analysis frameworks, keyword research techniques, and proven best practices. Load this file to inform all ASO recommendations.
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
I recommend app-store-aso for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added app-store-aso from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
app-store-aso reduced setup friction for our internal harness; good balance of opinion and flexibility.
Useful defaults in app-store-aso — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
app-store-aso fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
app-store-aso fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: app-store-aso is focused, and the summary matches what you get after install.
Useful defaults in app-store-aso — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
app-store-aso has been reliable in day-to-day use. Documentation quality is above average for community skills.
Registry listing for app-store-aso matched our evaluation — installs cleanly and behaves as described in the markdown.
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