Delegate SDLC tasks to 14 specialized AI agents that design multi-agent architectures, engineer prompts and RAG systems, orchestrate workflows, optimize LLM infrastructure, handle AI DevOps, testing, and quality assurance for production-ready AI/ML applications.
npx claudepluginhub stevegjones/ai-first-sdlc-practices --plugin sdlc-team-aiExpert in LangChain 0.1+ and LangGraph architectures. Use for LCEL chain design, RAG system architecture, multi-agent orchestration, tool integration patterns, or production deployment of LLM applications with observability.
Expert in MCP specification compliance, security auditing, and production readiness assessment. Use for quality reviews, security assessments, and deployment validation of MCP servers.
Expert in multi-agent system architecture including MCP and A2A protocols, inter-agent messaging, orchestration patterns, fault tolerance, and scaling strategies. Use for designing agent communication, orchestrating workflows, integrating heteroge...
Expert in agent architecture, persona design, and multi-agent systems. Designs agents using ReAct/Plan-Execute/Reflection patterns, implements RAG and tool integration, creates evaluation frameworks. Use for agent design decisions, system architec...
Expert in LLM serving infrastructure, GPU orchestration, AI cost optimization, and multi-agent system operations. Use for deploying AI systems to production, managing AI-specific CI/CD, and operating AI workloads at scale.
Expert in AI/ML system architecture, LLM application design, RAG systems, MLOps pipelines, and AI safety. Use for designing AI systems, evaluating model selection, architecting multi-agent systems, and ensuring production-grade AI implementations.
Expert in AI team transformation, multi-agent orchestration, and developer coaching. Use for AI adoption programs, team collaboration training, and building legendary AI-augmented teams.
Expert in comprehensive test strategy design, modern test automation frameworks, AI-augmented testing, contract testing, and quality engineering. Use for test pyramid design, CI/CD test integration, flaky test resolution, and shift-left testing pa...
Expert in AI memory architectures, context window optimization, token budget management, and state persistence. Use for designing conversation memory systems, implementing sliding window strategies, RAG-based context extension, and multi-agent con...
Expert in Model Context Protocol server architecture, tool schema design, transport configuration, and production deployment. Use for MCP server design, tool hierarchy planning, security architecture, and integration strategy.
MCP server testing specialist validating functionality, reliability, performance, and AI usability. Use for testing MCP implementations, validating production readiness, or debugging server issues.
Expert in multi-agent workflow design, state machines, agent coordination, and distributed orchestration. Use for designing agent pipelines, implementing handoff protocols, scaling orchestration systems, and choosing frameworks like LangGraph, Aut...
Expert in prompt engineering for Claude, GPT, Gemini, and Llama models. Specializes in chain-of-thought prompting, structured outputs, few-shot learning, system prompt architecture, and prompt optimization. Use for designing effective prompts, imp...
RAG architecture specialist for vector databases, embeddings, chunking strategies, and retrieval optimization. Use for designing production RAG systems, selecting vector stores, or optimizing retrieval quality.
Use this agent when creating user interfaces, designing components, building design systems, or improving visual aesthetics. This agent specializes in creating beautiful, functional interfaces that can be implemented quickly within 6-day sprints. Examples:\n\n<example>\nContext: Starting a new app or feature design
Comprehensive PR review agents specializing in comments, tests, error handling, type design, code quality, and code simplification
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
Use this agent when you need expert assistance with React Native development tasks including code analysis, component creation, debugging, performance optimization, or architectural decisions. Examples: <example>Context: User is working on a React Native app and needs help with a navigation issue. user: 'My stack navigator isn't working properly when I try to navigate between screens' assistant: 'Let me use the react-native-dev agent to analyze your navigation setup and provide a solution' <commentary>Since this is a React Native specific issue, use the react-native-dev agent to provide expert guidance on navigation problems.</commentary></example> <example>Context: User wants to create a new component that follows the existing app structure. user: 'I need to create a custom button component that matches our app's design system' assistant: 'I'll use the react-native-dev agent to create a button component that aligns with your existing codebase structure and design patterns' <commentary>The user needs React Native component development that should follow existing patterns, so use the react-native-dev agent.</commentary></example>
Comprehensive startup business analysis with market sizing (TAM/SAM/SOM), financial modeling, team planning, and strategic research
Semantic search for Claude Code conversations. Remember past discussions, decisions, and patterns.