This study identifies a phenomenon called Tool Suppression, where open-weight language models cease invoking tools when JSON Schema constraints are simultaneously enabled. The authors observed this behavior in a production Agent system and reproduced it through controlled experiments across multiple model families. While tool execution and schema compliance function correctly when evaluated independently, they fail under joint deployment conditions. Analysis reveals that JSON Schema constraints are compiled into grammar-based token masks, rendering tool-call tokens unreachable during decoding. To interpret these findings, the paper proposes the Constraint Priority Inversion hypothesis, suggesting schema satisfaction dominates action selection under simultaneous constraints. The authors mitigate this issue by introducing Transparent Two-Pass Execution, an inference-time strategy that decouples tool execution from response generation. This approach restores tool invocation while preserving structured output guarantees without requiring model retraining. The research highlights that evaluating capabilities separately may overlook critical reliability issues in production systems.