llm-application-dev
Building applications with Large Language Models - prompt engineering, RAG patterns, and LLM integration. Use for AI-powered features, chatbots, or LLM-based automation.
npx skills add majiayu000/claude-skill-registry --skill llm-application-dev-moizibnyousaf-ai-agent-skills --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# LLM Application Development ## Prompt Engineering ### Structured Prompts ```typescript const systemPrompt = `You are a helpful assistant that answers questions about our product. RULES: - Only answer questions about our product - If you don't know, say "I don't know" - Keep responses concise (under 100 words) - Never make up information CONTEXT: {context}`; const userPrompt = `Question: {question}`; ``` ### Few-Shot Examples ```typescript const prompt = `Classify the sentiment of customer feedback. Examples: Input: "Love this product!" Output: positive Input: "Worst purchase ever" Output: negative Input: "It works fine" Output: neutral Input: "${customerFeedback}" Output:`; ``` ### Chain of Thought ```typescript const prompt = `Solve this step by step: Question: ${question} Let's think through this: 1. First, identify the key information 2. Then, determine the approach 3. Finally, calculate the answer Step-by-step solution:`; ``` ## API Integration ### OpenAI Pattern ```typescript import OpenAI from 'openai'; const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY }); async function chat(messages: Message[]): Promise<string> { const response = await openai.chat.completions
- Prompt Engineering
- Structured Prompts
- Few-Shot Examples
- Chain of Thought
- API Integration
- OpenAI Pattern
- Anthropic Pattern
- Streaming Responses
- RAG (Retrieval-Augmented Generation)
- Basic RAG Pipeline
- Document Chunking
- Embedding Storage
- Error Handling
- Best Practices
What does the llm-application-dev skill do?
Building applications with Large Language Models - prompt engineering, RAG patterns, and LLM integration. Use for AI-powered features, chatbots, or LLM-based automation.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill llm-application-dev-moizibnyousaf-ai-agent-skills --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.