Schema First Tool APIs for LLM Agents: A Controlled Study of Tool Misuse, Recovery, and Budgeted Performance

A research study examined how different tool interface designs affect LLM agent performance under strict interaction budgets. While schema-based interfaces reduced contract violations, they didn't improve overall task success or semantic understanding, suggesting that formal tool specifications alone aren't sufficient for reliable AI agent operation.

• →Schema-based tool interfaces reduced interface misuse but didn't improve semantic understanding or task completion rates.
• →All tested conditions showed zero task success rates, indicating fundamental challenges beyond interface design.
• →Formal tool contracts improve adherence to technical specifications but don't solve core reasoning bottlenecks.
• →Timeout-sensitive tasks and semantic action quality remain major challenges for constrained local AI models.
• →Interface formalization provides incremental improvements but doesn't address the dominant performance limitations.