Turn an AI API (OpenAI, Anthropic, etc.) into a focused, defensible, paid product — prompt engineering for products, usage metering, rate limiting, model selection, and output quality control. USE WHEN building or pricing an AI-wrapper business and you need it to solve a real problem rather than be a thin ChatGPT clone.
Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.
Une commande directe contourne le prompt de vérification. Examinez la source avant de l'exécuter.
Turn an AI API (OpenAI, Anthropic, etc.) into a focused, defensible, paid product — prompt engineering for products, usage metering, rate limiting, model selection, and output quality control. USE WHEN building or pricing an AI-wrapper business and you need it to solve a real problem rather than be a thin ChatGPT clone.
cluster
business-content
version
1.0.0
origin
antigravity-awesome-skills (MIT)
risk
unknown
source
vibeship-spawner-skills (Apache 2.0)
date_added
"2026-02-27T00:00:00.000Z"
AI Wrapper Product
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.
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.
Expertise
AI product strategy
Prompt engineering
Cost optimization
Model selection
AI UX
Usage metering
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
`You are a ${context.role}.
Always respond in ${context.format}.
Tone: ${context.tone}`
// 3. Call API
const
await
messages
create
model
'claude-3-haiku-20240307'
max_tokens
1000
system
messages
role
'user'
content
// 4. Parse and validate output
const
content
0
text
return
parseOutput
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
Prompt Engineering for Products
Prompt Template Pattern
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
// Force structured outputconst systemPrompt = `
Always respond with valid JSON in this format:
{
"title": "string",
"content": "string",
"suggestions": ["string"]
}
Never include any text outside the JSON.
`;
// Parse with fallbackfunctionparseAIOutput(text) {
try {
returnJSON.parse(text);
} catch {
// Fallback: extract JSON from responseconst match = text.match(/\{[\s\S]*\}/);
if (match) returnJSON.parse(match[0]);
thrownewError('Invalid AI output');
}
}
1. Define specific writing use case
2. Design prompt templates
3. Build UI with streaming
4. Add usage tracking and limits
5. Implement payments
6. Launch and iterate