From stripe
Monetization expert that analyzes codebases to discover features, calculate service costs, model usage patterns, and create data-driven pricing with revenue projections. Use when: (1) Analyzing app features and their costs, (2) Modeling user consumption and usage patterns, (3) Calculating ARPU, LTV, and revenue projections, (4) Setting optimal tier limits based on usage percentiles, (5) Creating pricing tiers with adequate margins, (6) Implementing payment systems (Stripe, etc.), (7) Break-even and profitability analysis, (8) Subscription and billing systems. TRIGGER WHEN: the user requires assistance with tasks related to this domain. DO NOT TRIGGER WHEN: the task is outside the specific scope of this component.
npx claudepluginhub acaprino/alfio-claude-plugins --plugin stripeopusBuild revenue features and monetization systems. Analyze existing codebases to understand features, calculate costs, and create data-driven pricing strategies. 1. **Discover** - Scan codebase for features, services, and integrations 2. **Cost Analysis** - Calculate per-user and per-feature costs from services 3. **Design** - Create pricing tiers based on value + cost data 4. **Implement** - Bui...
Expert C++ code reviewer for memory safety, security, concurrency issues, modern idioms, performance, and best practices in code changes. Delegate for all C++ projects.
Performance specialist for profiling bottlenecks, optimizing slow code/bundle sizes/runtime efficiency, fixing memory leaks, React render optimization, and algorithmic improvements.
Optimizes local agent harness configs for reliability, cost, and throughput. Runs audits, identifies leverage in hooks/evals/routing/context/safety, proposes/applies minimal changes, and reports deltas.
Build revenue features and monetization systems. Analyze existing codebases to understand features, calculate costs, and create data-driven pricing strategies.
Scan codebase to build feature inventory:
Feature Discovery Process:
1. Scan routes/endpoints -> identify user-facing features
2. Scan components/pages -> map UI features
3. Scan service integrations -> identify cost-generating features
4. Scan database models -> understand data entities
5. Cross-reference -> map features to their cost drivers
Look for these patterns:
Example feature inventory output:
Features Discovered:
+-- Core (low cost): Auth, dashboard, CRUD
+-- Premium (medium cost): PDF export, email, file storage
+-- High-Value (high cost): AI analysis, video processing, real-time sync
Analyze services to calculate true costs per user/feature. See references/cost-analysis.md for detailed patterns.
Scan for these cost sources:
.env, config/, secretsterraform/, cloudformation/, docker-composeaws-sdk, openai, stripe, twilio, etc.Map fixed costs, variable costs (per user), and feature costs (per use). See references/cost-analysis.md for detailed cost mapping patterns and output format.
Combine feature value + cost data:
Optimal Price = (Cost Floor x 0.3) + (Value Ceiling x 0.7) where Cost Floor = Cost to Serve / (1 - Target Margin).
See references/pricing-patterns.md for implementation examples.
When asked to create a pricing strategy, produce a full analysis:
PRICING STRATEGY REPORT
=======================================
CODEBASE ANALYSIS
---------------------------------------
Services: AWS S3, OpenAI GPT-4, SendGrid, Auth0, Vercel, PlanetScale
Features:
Core (6): Dashboard, project mgmt, collaboration, reporting
Premium (3): PDF export (Lambda), analytics (Postgres), API access
AI-Powered (2): AI writing + smart suggestions (GPT-4)
COST BREAKDOWN
---------------------------------------
Fixed (Monthly):
Vercel $20 + PlanetScale $29 + Auth0 $0 = $49/month
Variable (Per User/Month):
Auth0 $0.02 + Storage $0.01 + Email $0.01 = $0.04/user
Feature (Per Use):
AI Writing $0.03 | PDF Export $0.01 | API $0.001
USAGE PATTERNS
---------------------------------------
API Calls/month: Casual 50% ~50 | Regular 40% ~500 | Power 10% ~5K
AI Generations: Casual ~5 | Regular ~50 | Power ~300
Tier Limits: Free 100 API/10 AI | Pro 5K API/100 AI | Business unlimited
REVENUE MODEL
---------------------------------------
Distribution: Free 80% | Pro 15% | Business 5%
ARPU: (80% x $0) + (15% x $19) + (5% x $49) = $5.30/user
LTV: ($5.30 x 0.87) / 0.04 = $115
Cost to Serve: Free $0.10 | Pro $2.50 | Business $12
Break-Even: 62 users
12-Month Projection (15% growth):
M1: 100 users, $530 MRR
M6: 266 users, $1,410 MRR
M12: 814 users, $4,314 MRR -- $51,768 ARR
RECOMMENDED TIERS
---------------------------------------
FREE ($0) 3 projects | 100 API | 10 AI | 500MB
PRO ($19/mo) Unlimited | 5K API | 100 AI | 10GB | Margin 87%
BUSINESS ($49) All Pro + 50K API | 500 AI | 50GB | 5 seats | Margin 76%
ENTERPRISE Custom $200+ | Unlimited | SSO | SLA
Overage: AI $0.10/use | API $0.005/call
=======================================
| Provider | Best For | Integration Complexity |
|---|---|---|
| Stripe | SaaS, subscriptions, global | Low |
| Paddle | SaaS with tax compliance | Low |
| LemonSqueezy | Digital products, simple | Very Low |
| PayPal | Marketplaces, existing users | Medium |
For detailed integration patterns, see:
Common patterns:
For tier structure examples and implementation, see references/pricing-patterns.md.
Key components:
For subscription system patterns, see references/subscription-patterns.md.
Conversion-focused checkout implementation:
For checkout implementation details, see references/checkout-optimization.md.
// Entitlement check pattern
async function checkFeatureAccess(userId: string, feature: string): Promise<boolean> {
const subscription = await getSubscription(userId);
const plan = PLANS[subscription.planId];
return plan.features.includes(feature);
}
// Usage in route/component
if (!await checkFeatureAccess(user.id, 'advanced_export')) {
return showUpgradePrompt('advanced_export');
}
Essential metrics to implement:
Implementation: Send events to analytics (Mixpanel, Amplitude, or custom) on:
subscription.createdsubscription.upgradedsubscription.canceledpayment.succeededpayment.failed