strands-agent

To scaffold a Strands AI agent on Bedrock, run the Starter Toolkit to generate an opinionated project skeleton with memory configuration, OpenTelemetry observability, eval scaffolds, and AgentCore deployment commands.

Yes, you can scaffold your Bedrock agent in both TypeScript and Python. The scaffolding process applies Strands framework best practices to generate production-ready project structures for either language.

The Strands Bedrock AgentCore project skeleton includes memory configuration patterns, OpenTelemetry observability integration, eval scaffolds, and clear deployment guidance using the AgentCore CLI.

Yes, the Strands agent scaffold includes observability and evaluation setup by providing OpenTelemetry integration for monitoring and dedicated eval scaffolds for testing agent performance end-to-end.

The best way to deploy a Strands agent to Bedrock AgentCore is using the provided AgentCore CLI deployment commands included in the scaffolded project skeleton.

Yes, you need the AgentCore CLI to deploy your scaffolded Strands agent, as the generated project skeleton provides clear deployment guidance and commands specifically designed for the AgentCore deployment workflow.