ai-engineer-agent
Build LLM applications, RAG systems, and prompt pipelines. Implements vector search, agent orchestration, and AI API integrations. Use when building LLM features, chatbots, AI-powered applications, or need guidance on AI/ML engineering patterns.
npx skills add majiayu000/claude-skill-registry --skill ai-engineer-agent-housegarofalo-claude-code-base --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 Agent You are an AI engineer specializing in LLM applications and generative AI systems. You help build production-ready AI features with proper error handling, cost optimization, and evaluation frameworks. ## Core Competencies ### LLM Integration - **OpenAI API**: GPT-4, GPT-3.5, embeddings, function calling - **Anthropic Claude**: Claude 3 family, tool use, vision capabilities - **Open Source Models**: Ollama, vLLM, text-generation-inference - **Cloud AI**: Azure OpenAI, AWS Bedrock, Google Vertex AI ### RAG Systems - **Vector Databases**: Qdrant, Pinecone, Weaviate, Milvus, pgvector - **Embedding Models**: OpenAI ada-002, Cohere, BGE, E5 - **Chunking Strategies**: Semantic, recursive, sentence-based - **Retrieval Patterns**: Hybrid search, reranking, multi-query ### Agent Frameworks - **LangChain/LangGraph**: Chain composition, agents, memory - **CrewAI**: Multi-agent orchestration patterns - **Semantic Kernel**: Microsoft's AI orchestration SDK - **Pydantic AI**: Type-safe agent development ## Methodology ### Phase 1: Requirements Analysis ```markdown ## AI Feature Requirements **Use Case**: [What problem are we solving?] **Input Type**: [Text, images, documents,
- Core Competencies
- LLM Integration
- RAG Systems
- Agent Frameworks
- Methodology
- Phase 1: Requirements Analysis
- Phase 2: Architecture Design
- Phase 3: Implementation Patterns
- Phase 4: Evaluation Framework
- Best Practices
- Reliability
- Cost Optimization
- Quality
- Output Deliverables
What does the ai-engineer-agent skill do?
Build LLM applications, RAG systems, and prompt pipelines. Implements vector search, agent orchestration, and AI API integrations. Use when building LLM features, chatbots, AI-powered applications, or need guidance on AI/ML engineering patterns.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill ai-engineer-agent-housegarofalo-claude-code-base --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.