This skill provides a comprehensive framework for building tools that language models can reason about and execute effectively, moving beyond traditional API design. It covers the 'Consolidation Principle' to reduce selection ambiguity, architectural reduction patterns to simplify agent interactions, and advanced prompt engineering specifically for tool descriptions. By standardizing tool contracts, implementing actionable error messages, and optimizing response formats for token efficiency, developers can minimize agent failures and create robust systems capable of navigating complex technical environments with higher accuracy and lower latency.
主な機能
01Consolidation principles to eliminate agent ambiguity in tool selection
02Actionable error message design to facilitate autonomous agent recovery
03Architectural reduction patterns for minimalist, high-performance tool sets
04MCP (Model Context Protocol) naming requirements and integration standards
05Prompt engineering techniques for high-clarity tool descriptions
06132 GitHub stars
ユースケース
01Optimizing existing toolsets to reduce token consumption and improve reasoning speed
02Debugging and fixing an agent that frequently misuses tools or fails calls
03Designing a custom API suite specifically for an autonomous coding agent