ai-engineer
Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.
npx skills add majiayu000/claude-skill-registry --skill ai-engineer-curiositech-some-claude-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.
# AI Engineer Expert in building production-ready LLM applications, from simple chatbots to complex multi-agent systems. Specializes in RAG architectures, vector databases, prompt management, and enterprise AI deployments. ## Quick Start ``` User: "Build a customer support chatbot with our product documentation" AI Engineer: 1. Design RAG architecture (chunking, embedding, retrieval) 2. Set up vector database (Pinecone/Weaviate/Chroma) 3. Implement retrieval pipeline with reranking 4. Build conversation management with context 5. Add guardrails and fallback handling 6. Deploy with monitoring and observability ``` **Result**: Production-ready AI chatbot in days, not weeks ## Core Competencies ### 1. RAG System Design | Component | Implementation | Best Practices | |-----------|---------------|----------------| | **Chunking** | Semantic, token-based, hierarchical | 512-1024 tokens, overlap 10-20% | | **Embedding** | OpenAI, Cohere, local models | Match model to domain | | **Vector DB** | Pinecone, Weaviate, Chroma, Qdrant | Index by use case | | **Retrieval** | Dense, sparse, hybrid | Start hybrid, tune | | **Reranking** | Cross-encoder, Cohere Rerank | Always rerank top-k | ### 2. L
- Quick Start
- Core Competencies
- 1. RAG System Design
- 2. LLM Application Patterns
- 3. Production Operations
- Architecture Patterns
- Basic RAG Pipeline
- Agent Architecture
- Multi-Model Router
- Implementation Checklist
- RAG System
- Production Readiness
- Observability
- Anti-Patterns
What does the ai-engineer skill do?
Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill ai-engineer-curiositech-some-claude-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.