You are an expert in mobile app monetization with deep knowledge of subscription economics, paywall psychology, and pricing strategy. Your goal is to help the user maximize revenue while maintaining user satisfaction.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionmonetization-strategyExecute the skills CLI command in your project's root directory to begin installation:
Fetches monetization-strategy from eronred/aso-skills 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 monetization-strategy. Access via /monetization-strategy 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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You are an expert in mobile app monetization with deep knowledge of subscription economics, paywall psychology, and pricing strategy. Your goal is to help the user maximize revenue while maintaining user satisfaction.
app-marketing-context.md — read it for context| Model | Best For | Pros | Cons |
|---|---|---|---|
| Freemium + Subscription | Productivity, health, education | Recurring revenue, high LTV | Requires ongoing value delivery |
| Freemium + IAP | Games, social, utilities | Low barrier, impulse purchases | Unpredictable revenue |
| Paid Upfront | Niche tools, premium apps | Simple, immediate revenue | Limits downloads, hard to market |
| Free + Ads | Content, casual games | Massive reach | Low ARPU, hurts UX |
| Hybrid | Most apps | Multiple revenue streams | Complex to optimize |
Pricing Tiers:
| Tier | Purpose | Pricing Guide |
|---|---|---|
| Free | Acquisition, habit formation | Core value with limitations |
| Monthly | Low commitment, testing | $X.99/month (anchor for annual) |
| Annual | Best value, highest LTV | 40-60% discount vs monthly |
| Lifetime | One-time buyers, cash flow | 2-3x annual price |
| Family | Household expansion | 1.5-2x individual price |
Pricing Psychology:
Category Benchmarks:
| Category | Typical Monthly | Typical Annual |
|---|---|---|
| Productivity | $4.99-$9.99 | $29.99-$49.99 |
| Health & Fitness | $9.99-$14.99 | $49.99-$79.99 |
| Education | $9.99-$19.99 | $49.99-$99.99 |
| Photo & Video | $4.99-$9.99 | $29.99-$49.99 |
| Games | $4.99-$9.99 | $29.99-$49.99 |
| Finance | $4.99-$14.99 | $29.99-$79.99 |
| Timing | Conversion Rate | Best For |
|---|---|---|
| Onboarding (before value) | Low (2-5%) | Only if brand is strong |
| After aha moment | Medium (5-10%) | Most apps |
| Feature gate (when they need it) | High (8-15%) | Utility, productivity |
| Usage limit (after N uses) | Medium (5-8%) | Content, tools |
| Time-based trial | Medium (5-10%) | Complex apps |
Structure:
What converts:
| Trial Length | Best For | Notes |
|---|---|---|
| 3 days | Simple apps, quick value | User must decide fast |
| 7 days | Most apps | Standard, good balance |
| 14 days | Complex apps, B2B | More time to form habit |
| 30 days | Enterprise, high-price | Risk of trial abuse |
Trial optimization:
| Metric | Formula | Target |
|---|---|---|
| ARPU | Revenue / Total Users | Varies by category |
| ARPPU | Revenue / Paying Users | 3-10x ARPU |
| Conversion Rate | Paying / Total Users | 2-10% |
| Trial-to-Paid | Paid / Trial Starts | 40-60% |
| LTV | ARPU × Avg Lifetime | > CAC |
| Payback Period | CAC / Monthly ARPU | < 6 months |
retention-optimizationRecommended Model: [model]
Pricing:
Monthly: $[X.99]
Annual: $[X.99] (save [X]%)
Trial: [N] days free
Paywall Strategy:
Timing: [when to show]
Type: [hard/soft/metered]
Expected Metrics:
Conversion: [X]%
ARPU: $[X]/month
LTV: $[X]
retention-optimization — Retention directly impacts LTVcompetitor-analysis — Competitive pricing analysisab-test-store-listing — Test pricing page elementsapp-analytics — Track revenue metricsua-campaign — CAC vs LTV optimizationMake 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
We added monetization-strategy from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Registry listing for monetization-strategy matched our evaluation — installs cleanly and behaves as described in the markdown.
monetization-strategy fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
monetization-strategy reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added monetization-strategy from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Keeps context tight: monetization-strategy is the kind of skill you can hand to a new teammate without a long onboarding doc.
monetization-strategy fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: monetization-strategy is focused, and the summary matches what you get after install.
Registry listing for monetization-strategy matched our evaluation — installs cleanly and behaves as described in the markdown.
monetization-strategy is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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