Agent skill

AI Wrapper Product

by davila7 in davila7/claude-code-templates

Expert in building products that wrap AI APIs (OpenAI, Anthropic, etc.) into focused tools people will pay for.

MITAuto-check passedAI & LLM Engineering

Install AI Wrapper Product

skills CLI
$ npx skills add davila7/claude-code-templates --skill ai-wrapper-product -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install davila7/claude-code-templates ai-wrapper-product --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/davila7/claude-code-templates.git skills-src && mkdir -p .claude/skills && cp -r skills-src/cli-tool/components/skills/business-marketing/ai-wrapper-product .claude/skills/ai-wrapper-product && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
ai-wrapper-product
GitHub stars
32k
Used in
4 other repos
Token cost
~1.7k tokens
SKILL.md length
200 words
Files
1
Skills in repo
478
Repo updated
First seen
Licence
MIT

At a glance

Expert in building products that wrap AI APIs (OpenAI, Anthropic, etc.) into focused tools people will pay for.

  • Tasks that involve Cloud cost optimization
  • SKILL.md covers Capabilities and Patterns
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Tasks that involve Prompt engineering

What it does

AI Wrapper Product is an agent skill from davila7/claude-code-templates. 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.

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in AI & LLM Engineering, covering Cloud cost optimization, Prompt engineering and Rate limiting. It works with OpenAI. The repository describes itself as: CLI tool for configuring and monitoring Claude Code. The licence is MIT.

When your agent uses it

  • Tasks that involve Cloud cost optimization
  • Tasks that involve Prompt engineering
  • Tasks that involve Rate limiting

Example prompts

  • “ChatGPT but different”
  • “/ai-wrapper-product”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 46b4d8b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are javascript and python).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

AI Wrapper Product loads about 1.7k tokens when it runs. Until then it costs about 96 tokens; SKILL.md has 200 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~96
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from davila7/claude-code-templates at commit 46b4d8b, republished under its MIT licence (© davila7). 200 words, ~1,652 tokens.

Download SKILL.mdSave it as .claude/skills/ai-wrapper-product/SKILL.md (or your agent's skills folder).
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.
source
vibeship-spawner-skills (Apache 2.0)

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-haiku-4-5-20251001',
    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
ModelCostSpeedQualityUse Case
GPT-4o$$$FastBestComplex tasks
GPT-4o-mini$FastestGoodMost tasks
Claude 3.5 Sonnet$$FastExcellentBalanced
Claude 3 Haiku$FastestGoodHigh 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 output
const systemPrompt = `
  Always respond with valid JSON in this format:
  {
    "title": "string",
    "content": "string",
    "suggestions": ["string"]
  }
  Never include any text outside the JSON.
`;

// Parse with fallback
function parseAIOutput(text) {
  try {
    return JSON.parse(text);
  } catch {
    // Fallback: extract JSON from response
    const match = text.match(/\{[\s\S]*\}/);
    if (match) return JSON.parse(match[0]);
    throw new Error('Invalid AI output');
  }
}
Quality Control
TechniquePurpose
Examples in promptGuide output style
Output format specConsistent structure
ValidationCatch malformed responses
Retry logicHandle failures
Fallback modelsReliability

### Cost Management

Controlling AI API costs

**When to use**: When building profitable AI products

```javascript
## AI Cost Management

### Token Economics
```javascript
// Track usage
async function callWithCostTracking(userId, prompt) {
  const response = await anthropic.messages.create({...});

  // Log usage
  await db.usage.create({
    userId,
    inputTokens: response.usage.input_tokens,
    outputTokens: response.usage.output_tokens,
    cost: calculateCost(response.usage),
    model: 'claude-3-haiku',
  });

  return response;
}

function calculateCost(usage) {
  const rates = {
    'claude-3-haiku': { input: 0.25, output: 1.25 }, // per 1M tokens
  };
  const rate = rates['claude-3-haiku'];
  return (usage.input_tokens * rate.input +
          usage.output_tokens * rate.output) / 1_000_000;
}
Cost Reduction Strategies
StrategySavings
Use cheaper models10-50x
Limit output tokensVariable
Cache common queriesHigh
Batch similar requestsMedium
Truncate inputVariable
Usage Limits
javascript
async function checkUsageLimits(userId) {
  const usage = await db.usage.sum({
    where: {
      userId,
      createdAt: { gte: startOfMonth() }
    }
  });

  const limits = await getUserLimits(userId);
  if (usage.cost >= limits.monthlyCost) {
    throw new Error('Monthly limit reached');
  }
  return true;
}

## Anti-Patterns

### ❌ Thin Wrapper Syndrome

**Why bad**: No differentiation.
Users just use ChatGPT.
No pricing power.
Easy to replicate.

**Instead**: Add domain expertise.
Perfect the UX for specific task.
Integrate into workflows.
Post-process outputs.

### ❌ Ignoring Costs Until Scale

**Why bad**: Surprise bills.
Negative unit economics.
Can't price properly.
Business isn't viable.

**Instead**: Track every API call.
Know your cost per user.
Set usage limits.
Price with margin.

### ❌ No Output Validation

**Why bad**: AI hallucinates.
Inconsistent formatting.
Bad user experience.
Trust issues.

**Instead**: Validate all outputs.
Parse structured responses.
Have fallback handling.
Post-process for consistency.

## ⚠️ Sharp Edges

| Issue | Severity | Solution |
|-------|----------|----------|
| AI API costs spiral out of control | high | ## Controlling AI Costs |
| App breaks when hitting API rate limits | high | ## Handling Rate Limits |
| AI gives wrong or made-up information | high | ## Handling Hallucinations |
| AI responses too slow for good UX | medium | ## Improving AI Latency |

## Related Skills

Works well with: `llm-architect`, `micro-saas-launcher`, `frontend`, `backend`

© davila7, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in cli-tool/components/skills/business-marketing/ai-wrapper-product of davila7/claude-code-templates.

Open the folder on GitHubat commit 46b4d8b

Used in 4 other repositories

We found 6 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 4 other GitHub owners. This page covers the copy in davila7/claude-code-templates, which our catalogue first saw on October 7, 2026.

Compare with similar skills

AI Wrapper Product next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

AI Wrapper Product compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
AI Wrapper Product this skilldavila7/claude-code-templates32k4 repos~1.7kAutomated safety check: PassMIT
AI Wrapper Productaiskillstore/marketplace4303 repos~3.9kAutomated safety check: PassNone
LLM GatewayBagelHole/DevOps-Security-Agent-Skills1.1k—~2kAutomated safety check: PassMIT
Codex Fable5baskduf/FableCodex437—~1.6kAutomated safety check: PassAGPL-3.0
System Prompt Writing Guidecashew-labs/libretto904—~570Automated safety check: PassMIT
Flowfile AI Subsystem GuideEdwardvaneechoud/Flowfile375—~7kAutomated safety check: NotesMIT

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Works with

Questions about AI Wrapper Product

What does AI Wrapper Product do?

Expert in building products that wrap AI APIs (OpenAI, Anthropic, etc.) into focused tools people will pay for. AI Wrapper Product is an agent skill from davila7/claude-code-templates.) into focused tools people will pay for.

When should I use AI Wrapper Product?

AI Wrapper Product fits situations like: tasks that involve Cloud cost optimization; tasks that involve Prompt engineering; tasks that involve Rate limiting.

How do I install AI Wrapper Product in Claude Code?

Run `npx skills add davila7/claude-code-templates --skill ai-wrapper-product -a claude-code`. Or copy the skill folder (cli-tool/components/skills/business-marketing/ai-wrapper-product in davila7/claude-code-templates) into .claude/skills/ai-wrapper-product in your project. Claude Code loads it when a task matches its description.

How do I install AI Wrapper Product in Codex?

Run `npx skills add davila7/claude-code-templates --skill ai-wrapper-product -a codex`. Or copy the skill folder (cli-tool/components/skills/business-marketing/ai-wrapper-product in davila7/claude-code-templates) into .agents/skills/ai-wrapper-product in your project. Codex loads it when a task matches its description.

Can I use AI Wrapper Product in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add davila7/claude-code-templates --skill ai-wrapper-product -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ai-wrapper-product, .gemini/skills/ai-wrapper-product, .github/skills/ai-wrapper-product and .opencode/skills/ai-wrapper-product in your project.

What does AI Wrapper Product need to run?

SKILL.md names no scripts, command-line tools or credentials: AI Wrapper Product is instructions for the agent only. Our summary lists: Python 3.

Does AI Wrapper Product access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is AI Wrapper Product safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does AI Wrapper Product use?

AI Wrapper Product is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does AI Wrapper Product use?

About 1.7k tokens (SKILL.md is roughly 6.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to AI Wrapper Product?

Skills that share tags, products or a category with AI Wrapper Product: AI Wrapper Product (aiskillstore/marketplace, 430 stars), LLM Gateway (BagelHole/DevOps-Security-Agent-Skills, 1.1k stars), Codex Fable5 (baskduf/FableCodex, 437 stars) and System Prompt Writing Guide (cashew-labs/libretto, 904 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains AI Wrapper Product?

davila7 (a GitHub user) maintains it in davila7/claude-code-templates, which has 32,483 GitHub stars. The repository holds 478 skills in this directory. The repository was last updated on October 9, 2026.

Source: davila7/claude-code-templates on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.