Claude Code Templates is a command-line tool and catalogue for configuring Anthropic’s Claude Code with agents, commands, settings, hooks, integrations, skills, and project templates. Developers use it to browse and install reusable components for their coding workflows. The catalogue includes many of these Claude Code components.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add davila7/claude-code-templates --skill ai-wrapper-productgit clone --depth 1 https://github.com/davila7/claude-code-templatesWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/davila7/claude-code-templates/ai-wrapper-product)<a href="https://agentmods.dev/skills/davila7/claude-code-templates/ai-wrapper-product"><img src="https://agentmods.dev/badge/skills/davila7/claude-code-templates/ai-wrapper-product.svg" alt="Measured on agentmods" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 67 Skill instructs the agent to never refuse or to always comply. Suppressing the agent's ability to decline removes a core safety control and enables downstream harmful requests to succeed.Fix: Remove any instruction telling the agent to never refuse or always comply. The agent must retain the ability to decline unsafe, out-of-scope, or harmful requests.
- high Anti-Refusal · line 127 Skill instructs the agent to never refuse or to always comply. Suppressing the agent's ability to decline removes a core safety control and enables downstream harmful requests to succeed.Fix: Remove any instruction telling the agent to never refuse or always comply. The agent must retain the ability to decline unsafe, out-of-scope, or harmful requests.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00084 | $0.01587 |
| Opus 5 | $0.00042 | $0.00794 |
| Sonnet 5 | $0.00017 | $0.00317 |
| Haiku 4.5 | $0.00008 | $0.00159 |
Grade A, and why
ai-wrapper-product scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
4 near-identical copies found in the catalogue:
- ai-wrapper-product — 98% identical, 2 lines differ
- ai-wrapper-product — 92% identical, 8 lines differ
- ai-wrapper-product — 92% identical, 8 lines differ
- ai-wrapper-product — 88% identical, 11 lines differ
How it starts
The opening of the file, as written. The whole thing — 274 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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();
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
| 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 |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 274 lines · 84 tokens per session scan A 9fd8d9199def
ai-wrapper-product is a skill published in the GitHub repository davila7/claude-code-templates (30,546 stars, last pushed yesterday), licensed MIT. It adds 84 tokens to every session and 1,587 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
ccc-prompt-fix
Fix and sharpen a prompt. Diagnoses it against the 6 prompt-quality patterns, returns a tightened rewrite with the reasoning, and suggests the right library prompt for your task.
fabric-semantic-model-ai-instructions
Use when configuring AI instructions on a Power BI semantic model — the 10,000-character blob attached via Prep data for AI → Add AI instructions in Desktop or the service. Applies everywhere Copilot uses the model (reports, Q&A, Copilot pane). Covers what belongs in the blob (business context, terminology, date…
midjourney-prompter
Engineer Midjourney prompts — style references, aspect ratios, negative prompts, and v6 parameter tuning.
stable-diffusion-helper
Craft Stable Diffusion prompts — SDXL, LoRA triggers, ControlNet hints, and ComfyUI workflow design.
midjourney-replicate-flux
Generate highly detailed, Midjourney-style image prompts optimized for the FLUX 1.1 Pro model on Replicate. Transform basic user descriptions into rich, cinematic prompts with professional photography qualities, dramatic lighting, and editorial-quality aesthetics. Use when users request image generation, need prompt…
guidance
Constrain LLM output with grammars; guarantee valid JSON.