Brief

This article introduces a practical toolkit for external AI agent stacks, inspired by the principles of the Augment Intent system. The toolkit focuses on semantic retrieval, reducing verbose shell output, and sensible model routing, rather than simply increasing context length. It comprises four main components: Claude Code for coding tasks, Augment Context Engine MCP for retrieving relevant codebase sections, RTK for trimming unnecessary shell output, and LiteLLM as a local gateway for model management. AI