Skill
Community

aws-ai-assistant

Install
1
Install the plugin
$
npx claudepluginhub diegouis/provectus-marketplace --plugin proagent-aws-ai

Want just this skill?

Then install: npx claudepluginhub u/[userId]/[slug]

Description

Building AI Solutions on AWS - Bedrock AgentCore agents, MCP server development and deployment, Knowledge Bases RAG with S3 Vectors, generative AI architecture patterns, CDK/CloudFormation infrastructure, and AWS AI service integration. Use when designing, building, deploying, or reviewing any AI system on Amazon Web Services including chatbots, copilots, multi-agent orchestration, content generation pipelines, and enterprise knowledge systems. Do NOT use for general backend development (use backend-assistant), frontend work (use frontend-assistant), or non-AI AWS infrastructure.

Tool Access

This skill uses the workspace's default tool permissions.

Supporting Assets
View in Repository
references/agentcore-patterns.md
references/architecture-patterns.md
references/cdk-iac-patterns.md
references/knowledge-bases-rag.md
references/mcp-server-patterns.md
Skill Content

Building AI Solutions on AWS

Comprehensive AWS AI skill covering the full lifecycle of AI solution development on Amazon Web Services — from architecture design through agent building, MCP server creation, knowledge base setup, and production deployment.

When to Use This Skill

  • Designing AI architectures on AWS (chatbots, agents, copilots, content generators)
  • Building AI agents with Amazon Bedrock AgentCore
  • Creating and deploying Model Context Protocol (MCP) servers on AWS
  • Setting up RAG systems with Amazon Bedrock Knowledge Bases
  • Deploying AI infrastructure with CDK, CloudFormation, or Terraform
  • Integrating AWS AI services (Bedrock, SageMaker, Comprehend, Rekognition, etc.)
  • Reviewing AWS AI architectures for Well-Architected compliance
  • Implementing responsible AI with Bedrock Guardrails
  • Optimizing AI workload costs on AWS
  • Selecting foundation models (Claude, Nova, Llama, Mistral) for specific use cases
  • Configuring Cedar policies for agent access control
  • Setting up agent evaluation and observability

CRITICAL: Ask First, Load Later

DO NOT read reference files, run environment detection commands, or load mode files until the user has told you what they want to do.

MANDATORY: You MUST call the AskUserQuestion tool — do NOT render these options as text:

AskUserQuestion( header: "AWS AI", question: "What AWS AI topic would you like help with?", options: [ { label: "Bedrock AgentCore", description: "Build agents with AgentCore, Cedar policies, and evaluations" }, { label: "MCP Servers on AWS", description: "Create and deploy Model Context Protocol servers on AWS" }, { label: "RAG / Knowledge Bases", description: "RAG systems, Knowledge Bases, chunking, vector storage" }, { label: "AI Architecture", description: "AI architecture design, service and model selection, Well-Architected" } ] )

If the user selects "Other", offer CDK/IaC infrastructure for AI workloads.

Reference Routing

CONTEXT GUARD: Load reference files only when the user's request matches a specific topic below. Do NOT load all references upfront.

User IntentReference File
Building agents with Bedrock AgentCore, Cedar policies, evaluationsreferences/agentcore-patterns.md
Creating or deploying MCP servers on AWSreferences/mcp-server-patterns.md
RAG systems, Knowledge Bases, chunking, vector storagereferences/knowledge-bases-rag.md
AI architecture design, service selection, model selectionreferences/architecture-patterns.md
CDK infrastructure, CloudFormation, IaC for AI workloadsreferences/cdk-iac-patterns.md

Core Principles

  • Follow the AWS Well-Architected Generative AI Lens (six pillars)
  • Use AgentCore for production agent deployments with session isolation
  • Prefer S3 Vectors for cost-optimized vector storage (90% savings)
  • Always apply Bedrock Guardrails and Cedar policies for safety
  • Deploy infrastructure as code — never ClickOps

Visual Diagramming

Use Excalidraw MCP for AWS AI architecture diagrams, agent flow diagrams, RAG pipeline topology, and multi-agent orchestration visualizations.

Reference Assets

See AWS Bedrock AgentCore Docs, AWS MCP Servers, Gen AI CDK Constructs, and the Well-Architected Generative AI Lens.

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Last CommitMar 12, 2026

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