Progressive tool schema deferral cut AI agent costs 21% but hurt one task type

A developer tested progressive disclosure on an AI agent with 20 tools, finding that deferring tool schemas reduced input tokens by roughly 30% and overall costs by about 21% across 80 runs. Three of the four business task types saw savings between 21% and 30%, while the fourth task showed no savings on one transport and cost 12.3% more on another. The experiment used GPT-4o at temperature zero across both Chat Completions and Responses API transports, with all runs completed on August 6, 2026, at a total cost of under 28 cents. Deeper analysis revealed that token variability under deferral stemmed from differences between task types rather than run-to-run randomness, with some tasks consistently loading far more schemas than others. The findings suggest that mean cost reduction is a misleading metric when evaluating schema deferral, and per-task breakdown is essential before deploying the optimization in production.