Most agent demos die in the gap between a working notebook and something that survives production. The hard part was never the prompt loop — it's the Terraform, the deployment pipeline, the eval harness, and the tracing you bolt on afterward. This package inverts that order: uvx agent-starter-pack create hands you all of it on day one, then asks you to fill in the agent logic.
What Sets It Apart
- Templates are framework-specific, not generic boilerplate: ADK, LangGraph, ADK Java for JVM shops, and ADK Live for real-time multimodal RAG — so the scaffold matches how your team already builds.
- Two first-class deployment targets, Cloud Run and Vertex AI Agent Engine, each wired with Terraform, so you pick a hosting model without rewriting infrastructure.
- Evaluation, observability, and a RAG data pipeline (Vertex AI Search / Vector Search) come pre-integrated, meaning the parts teams usually defer until an incident are present from commit one.
- An
enhancecommand retrofits this infrastructure onto an agent you already wrote, so adoption doesn't require starting over.
Who It's For
Great fit if you're committed to Google Cloud and want to skip weeks of plumbing to reach a deployable, observable agent. Look elsewhere if you target AWS or Azure, prefer a cloud-agnostic stack, or only need a local prototype — the value here is the GCP-specific production scaffolding, not the agent reasoning itself. Note that the project is now in maintenance mode, with active development continuing in a successor agents-cli, though critical fixes still land here.
