ai-engineer-plugin

Plugin ai-engineer-plugin from marketplace pluginagentmarketplace-ai-engineer in pluginagentmarketplace/custom-plugin-ai-engineer. Commands read from the repo's manifest — 1 month ago.

Skills (8)

• agent-frameworks

  AI agent development with LangChain, CrewAI, AutoGen, and tool integration patterns.

• evaluation-metrics

  LLM evaluation frameworks, benchmarks, and quality metrics for production systems.

• fine-tuning

  LLM fine-tuning with LoRA, QLoRA, and instruction tuning for domain adaptation.

• llm-basics

  LLM architecture, tokenization, transformers, and inference optimization. Use for understanding and working with language models.

• model-deployment

  LLM deployment strategies including vLLM, TGI, and cloud inference endpoints.

• prompt-engineering

  Prompt design, optimization, few-shot learning, and chain of thought techniques for LLM applications.

• rag-systems

  Retrieval Augmented Generation systems with vector search, document processing, and hybrid retrieval.

• vector-databases

  Vector database selection, indexing strategies, and semantic search optimization.

Slash commands (3)

• /ai-engineer-plugin:ai-engineer

  AI Engineer assistant for LLM development, RAG systems, and AI applications

• /ai-engineer-plugin:prompt-lab

  Interactive prompt engineering lab for designing, testing, and optimizing LLM prompts

• /ai-engineer-plugin:rag-builder

  RAG system builder for creating production-ready retrieval augmented generation pipelines

Subagents (6)

• 01-llm-fundamentals

  Master LLM architecture, tokenization, transformer models, and inference optimization

• 02-prompt-engineering

  Master prompt design, optimization techniques, and effective LLM interaction patterns

• 03-rag-systems

  Build production RAG systems with vector databases, embeddings, and retrieval optimization

• 04-fine-tuning

  Master LLM fine-tuning techniques including LoRA, QLoRA, and instruction tuning

• 05-evaluation-monitoring

  Implement LLM evaluation frameworks, monitoring, and observability for production systems

• 06-ai-agents

  Build autonomous AI agents with tool use, planning, and multi-agent orchestration