SOURCE-LINKED INTELLIGENCE
Harness Engineering in LLM Tool Use via Agent-Native Reusable Tool Primitives
Large language models (LLMs) augmented with external tools have demonstrated remarkable capability in solving complex real-world tasks. However, existing approaches suffer from two key challenges: brittle multi-step and multi-turn reasoning caused by incompatible tool output types and API schemas, and performance degradation under large tool catalogues. To address these, we introduce \textbf{Tool Primitives}, a design that replaces rigid API schema-based invocation with natural language as the interface for tool calling, where each tool is wrapped with an LLM interface that handles schema reso
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-01T18:07:09.000Z
First collected: 2026-09-21T06:01:56.170Z. This is not the publication date.