Writing effective tools for AI agents—using AI agents

What this post added

This post details Anthropic's techniques for building and improving tools for AI agents, focusing on the Model Context Protocol (MCP). It covers prototyping tools locally, running comprehensive evaluations with agents, and collaborating with agents like Claude Code for automated performance improvements. Key principles for writing effective tools are outlined, including tool selection, namespacing, response optimization for token efficiency, and prompt engineering of tool descriptions. The post emphasizes designing tools for agents' unique affordances and context limitations, contrasting this with traditional software development.