Function-calling schemas, presented in practitioner guides as mechanisms for structured output, operate as de facto governance instruments within model–tool ecosystems. While most documentation focuses on syntactic validity and schema adherence, little attention has been paid to how parameter defaults, validators, and enforced signatures redistribute agency among the operator, the model, and the external tool. This paper introduces the Agency Reallocation Index (ARI), a quantitative measure that captures this redistribution through entropy reduction and Shapley attribution across three control dimensions: operator, model, and tool. Treating the schema as a regla compilada (a compiled rule that pre-structures permissible actions), the study demonstrates how defaults and validation layers govern results as effectively as explicit human instruction. A factorial experiment over controlled tool-calling tasks isolates the effects of validator strictness, default intensity, and signature breadth on agency allocation. The findings show that higher validator rigidity or hard defaults consistently increase tool agency while compressing model autonomy, exposing a governance gradient encoded in interface design. The paper concludes that schema architecture not only constrains model behavior but also formalize a programmable distribution of authority that should be audited alongside conventional metrics of accuracy and reliability. DOI Primary archive: https://doi.org/10.5281/zenodo.17533080 Secondary archive: https://doi.org/10.6084/m9.figshare.30541049 SSRN: Pending assignment (ETA: Q4 2025)