This article discusses the importance of robust contracts between Large Language Models (LLMs) and external tools to ensure reliability and predictability in AI agent operations. It emphasizes that the contract, not the LLM itself, is often the source of fragility when dealing with retries, timeouts, or duplicate requests. The proposed solution involves defining explicit contracts that detail input schemas, output statuses, error codes, and retry policies, moving beyond simple function calls to a more API-like interface. This approach aims to make tools more predictable, auditable, and easier for both the LLM and human operators to manage, especially in sensitive applications like email processing or resource deployment. AI
IMPACT Establishes best practices for building more reliable and auditable AI agents by focusing on explicit tool contracts.
RANK_REASON The article provides an opinion and technical guidance on designing LLM tool contracts, rather than announcing a new product or research finding.
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