ai-wrapper-product
Expert in building products that wrap AI APIs (OpenAI, Anthropic, etc.) into focused tools people will pay for.
Skill by alexander-kastil
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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About
Use cases: agent-building
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What's inside
- Skill name
ai-wrapper-product- Description
- Expert in building products that wrap AI APIs (OpenAI, Anthropic, etc.) into focused tools people will pay for. Not just 'ChatGPT but different' - products that solve specific problems with AI. Covers prompt engineering for products, cost management, rate limiting, and building defensible AI businesses. Use when: AI wrapper, GPT product, AI tool, wrap AI, AI SaaS.
- License
- MIT
- Instructions
- 269 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# 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
```python
## 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();
async function generateContent(userInput, context) {
// 1. Validate input
if (!userInput || userInput.length > 5000) {
throw new Error('Invalid input');
}
// 2. Build prompt
const systemPrompt = `You are a ${context.role}.
Always respond in ${context.format}.
Tone: ${context.tone}`;
// 3. Call API
const response = await anthropic.messages.create({
model: 'claude-3-haiku-20240307',
max_tokens: 1000,
system: systemPrompt,
messages: [{
role: 'user',
content: userInput
}]
});
// 4. Parse and validate output
const output = response.content[0].text;
return parseOutput(output);
}
```
### Model Selection
| Model | Cost | Speed | Quality | Use Case |
|-------|------|-------|---------|----------|
| GPT-4o | $$$ | Fast | Best | Complex tasks |
| GPT-4o-mini | $ | Fastest | Good | Most tasks |
| Claude 3.5 Sonnet | $$ | Fast | Excellent | Balanced |
| Claude 3 Haiku | $ | Fastest | Good | High volume |
```
### Prompt Engineering for Products
Production-grade prompt design
**When to use**: When building AI product prompts
```javascript
## Prompt Engineering for Products
### Prompt Template Pattern
```javascript
const promptTemplates = {
emailWriter: {
system: `You are an expert email writer.
Write professional, concise emails.
Match the requested tone.
Never include placeholder text.`,
user: (input) => `Write an email:
Purpose: ${input.purpose}
Recipient: ${input.recipient}
Tone: ${input.tone}
Key points: ${input.points.join(', ')}
Length: ${input.length} sentences`,
},
};
```
### Output Control
```javascript
// Force structured outputFrom alexander-kastil/skills-collection, MIT.
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Signals
- Stars
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- Forks
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- Open issues
- 1
- Last commit (this folder)
- Feb 16, 2026 (8 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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ai-wrapper-product skill. Agent Mart. https://agentmart.dev/skills/alexander-kastil-ai-wrapper-product (last updated 2026-10-24)