Cookbook & Design Patterns

📄️Cookbook

Task-oriented recipes for generated TeaQL APIs, Java services, runtime providers, and AI-native usage.

Perform a TeaQL write with explicit business intent, transaction ownership, and verification evidence.

Keep tenant scope server-controlled while using generated TeaQL query APIs.

Change a TeaQL database provider while keeping generated business APIs stable and verifying provider-specific behavior.

Page a generated TeaQL query with deterministic ordering, trusted scope, and verification.

Shape related TeaQL data explicitly and verify the resulting query behavior.

Build counts and grouped business statistics with generated TeaQL requests and verify their scope.

Accept bounded user-driven search JSON without handing tenant, permission, or resource limits to the caller.

Choose and register internal or business ID generation without modifying generated entities.

Route eligible Java reads to replicas while keeping writes, transactions, and consistency-sensitive reads on primary.

Model, select, audit, mask, and verify sensitive TeaQL fields without treating masking as authorization.

Use TeaQL Rust memory execution for fast generated-API tests without mistaking it for database-provider verification.

Inspect generated TeaQL code to diagnose behavior while keeping the model and generator as the source of truth.

Suggested TeaQL responsibility boundaries and delivery flow for a small internal product team.

Suggested TeaQL ownership, review, and delivery boundaries for distributed implementation teams.