llm-application-dev

Plugin llm-application-dev from marketplace libreuiux in HermeticOrmus/LibreUIUX-Claude-Code. Commands read from the repo's manifest — 1 month ago.

Skills (5)

• langchain-architecture

  Design LLM applications using the LangChain framework with agents, memory, and tool integration patterns. Use when building LangChain applications, implementing AI agents, or creating complex LLM workflows.

• llm-evaluation

  Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.

• prompt-engineering-patterns

  Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt templates.

• prompt-engineering-ui

  Prompt patterns for consistent UI generation: stating design intent precisely, component specification formats, few-shot examples, and structured refinement loops. Use when UI output from an LLM is inconsistent or generic, or when building reusable prompt templates for a design system.

• rag-implementation

  Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.

Slash commands (3)

• /llm-application-dev:ai-assistant

  Design and build an AI assistant or chatbot

• /llm-application-dev:langchain-agent

  Build a LangChain or LangGraph agent system

• /llm-application-dev:prompt-optimize

  Turn a basic instruction into an optimized, production-ready prompt

Subagents (2)

• 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.

• prompt-engineer

  Expert prompt engineer specializing in advanced prompting techniques, LLM optimization, and AI system design. Masters chain-of-thought, constitutional AI, and production prompt strategies. Use when building AI features, improving agent performance, or crafting system prompts.

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