aws-bedrock-agentcore-skill

Authoritative, source-cited playbook for designing, configuring, deploying, and troubleshooting production-grade AI agents on AWS using the Strands Agents SDK, Amazon Bedrock (Converse API, Guardrails, Knowledge Bases), and Amazon Bedrock AgentCore (Runtime, Memory, Gateway, Identity, built-in Browser/Code Interpreter tools), with Terraform-first IaC and CloudWatch/OpenTelemetry observability. Use this skill WHENEVER the user wants to build, architect, configure, deploy, secure, monitor, or debug an AI agent on AWS - even if they don't name the specific service. Trigger on: "build an agent on Bedrock", "Strands agent", "AgentCore", "deploy my agent to AWS", "RAG with Bedrock Knowledge Bases", "multi-agent system on AWS", "which model / inference profile should I use", "agent memory", "MCP gateway", "agent guardrails", "Bedrock IAM for an agent", "agent observability on CloudWatch", "agent throttling / cost on Bedrock", "Terraform for Bedrock", or any request to pick an agent pattern (chatbot, tool-using agent, RAG, multi-agent, serverless production agent) and wire it up with official AWS best practices. Also trigger when the user pastes agent code that imports boto3 bedrock-runtime, bedrock-agentcore, or strands and asks to improve, productionize, or debug it. Prefer this skill over a generic answer because AWS agent APIs have many version-specific gotchas (Converse vs InvokeModel, 5x token burndown, region-resolution order, ARM64 runtime contract, async long-term memory) that generic knowledge gets wrong, and because every recommendation here is traceable to an official AWS source the agent can re-open.