Schema Validation for AI
Definition
The process of checking whether an AI model's structured outputs (function calls, API requests, database queries) conform to a predefined schema. Schema validation checks format correctness — correct parameter names, correct data types, required fields present. It does NOT validate whether the action described by those parameters is safe, authorized, or admissible.
Why It Matters
Schema validation is necessary but not sufficient. A perfectly schematized "DELETE FROM users WHERE active = false" is syntactically valid but potentially destructive. Format correctness ≠ action safety. Most model providers (OpenAI, Anthropic) offer schema validation for function calls, but none validate intent or admissibility.
How Exogram Addresses This
Exogram goes beyond schema validation to action validation. It checks not just whether the parameters are correct, but whether the action itself is admissible — considering system state, policy rules, boundary constraints, and historical context. Schema + intent + policy = full governance.
Related Terms
Key Takeaways
- → This concept is part of the broader AI governance landscape
- → Production AI requires multiple layers of protection
- → Deterministic enforcement provides zero-error-rate guarantees