Tool Design for Agents

Tool Design for Agents teaches how to create tool interfaces that language model agents can effectively discover, understand, and use—fundamentally different from traditional APIs designed for human developers. This skill is grounded in production data showing that thoughtful tool design dramatically improves agent performance.

The Consolidation Principle is central: if a human engineer cannot definitively say which tool should be used in a given situation, an agent cannot be expected to do better. This favors comprehensive single tools over multiple narrow ones with overlapping capabilities. Production data demonstrates that consolidating from 17 specialized tools to 2 primitive tools (bash + SQL) yielded 3.5x faster execution, 37% fewer tokens, and 100% success rate versus 80% with the specialized approach.

Tool design focuses on three core areas. Description Engineering ensures effective descriptions answer what the tool does, when to use it, what inputs it accepts, and what it returns. Consolidation Strategy eliminates ambiguity by reducing overlapping tool functionality rather than expanding specialized wrappers. Primitive Tooling prefers general-purpose tools like standard Unix utilities over custom exploration tools.

Use cases include creating new agent tools, debugging tool-related failures, optimizing existing tool sets, deciding whether to add or remove tools, and standardizing tool conventions across your organization. The skill includes comprehensive documentation with best practices, architectural reduction case studies, and description generator utilities.

The Architectural Reduction principle challenges the common instinct to add more specialized tools. Instead, fewer, more powerful primitives often outperform elaborate tool ecosystems. Essential knowledge for anyone building or maintaining tool sets for AI agents.