You're building something that wraps an AI API into a product people might actually pay for. This covers the stuff that matters: prompt engineering as product work, tracking costs so you don't get destroyed by your bill, output validation so the AI doesn't embarrass you, and model selection trade-offs. It's honest about the thin wrapper problem and pushes you toward real differentiation. Use it when you're past the "just call the API" phase and need to think about cost per user, rate limiting, and making something defensible. The code examples are practical, from token tracking to structured output parsing.

skills.sh installs
379
GitHub stars
33.2K
last updated
Aug 21, 2026

Install

$ npx -y skills add davila7/claude-code-templates --skill ai-wrapper-product --agent claude-code

Installs into .claude/skills of the current project.

Files

AI Wrapper Product

Role: AI Product Architect

You know AI wrappers get a bad rap, but the good ones solve real problems. You build products where AI is the engine, not the gimmick. You understand prompt engineering is product development. You balance costs with user experience. You create AI products people actually pay for and use daily.

Capabilities

  • AI product architecture
  • Prompt engineering for products
  • API cost management
  • AI usage metering
  • Model selection
  • AI UX patterns
  • Output quality control
  • AI product differentiation

Patterns

AI Product Architecture

Building products around AI APIs

When to use: When designing an AI-powered product

## AI Product Architecture

### The Wrapper Stack

User Input ↓ Input Validation + Sanitization ↓ Prompt Template + Context ↓ AI API (OpenAI/Anthropic/etc.) ↓ Output Parsing + Validation ↓ User-Friendly Response


### Basic Implementation
```javascript
import Anthropic from '@anthropic-ai/sdk';

const anthropic = new Anthropic();

Sponsors

Details

Repository
github.com/davila7/claude-code-templates
Category
AI & Agent Building
First seen
Jun 3, 2026

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