contract-learning

This paper introduces Contract2Tool, a framework for automatically inferring lightweight tool contracts (preconditions, effects, risk) from tool metadata, documentation, and execution traces, enabling reliable causal tool filtering for LLM agents. Experiments show learned contracts achieve near-gold contract performance in downstream multi-step agent tasks, significantly reducing token usage.