This skill provides a comprehensive framework for designing tool APIs that language models can reason about effectively, minimizing the common failure modes caused by ambiguous documentation or over-complex architectures. It guides developers through the consolidation principle—grouping related functions to reduce cognitive load—and architectural reduction, which favors general-purpose primitives over specialized wrappers. By implementing these patterns, developers can create more reliable, token-efficient agentic systems that scale with future model improvements while ensuring consistent naming conventions and robust error recovery.
주요 기능
01Consolidation Principle Implementation
02Agentic Error Recovery Design
03MCP Server Naming Conventions
04Architectural Reduction Patterns
05Tool Description Prompt Engineering
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사용 사례
01Refactoring complex toolsets to improve token efficiency
02Designing new tool APIs from scratch for agentic workflows
03Debugging agent failures and tool misuse in production