Defining and validating database schemas with proper typing, index configuration, optional fields, unions, and migration strategies for schema changes
Convex Schema Validator helps developers define and validate database schemas in Convex using strongly typed validators and structured schema definitions. It provides guidance for configuring tables, field validation, optional properties, unions, nested objects, and relationships between documents. By using Convex schema validators, developers can create consistent and type-safe database models while reducing runtime validation errors and improving maintainability in TypeScript-based applications. The skill also emphasizes referencing official Convex documentation before implementation to ensure compatibility with the latest schema, index, and data type features.
The skill covers a wide range of schema modeling capabilities, including primitive validators such as strings, numbers, booleans, IDs, arrays, records, and objects. It demonstrates how to define indexes for efficient querying, including single-field indexes, compound indexes, sorting indexes, and full-text search indexes. Advanced schema structures such as nested objects, arrays of objects, record types with dynamic keys, discriminated unions, and literal-based unions are also included. Additionally, it introduces migration-oriented schema design strategies by showing how optional fields and unions can support evolving database structures over time.
This skill is designed for developers building backend applications with Convex and TypeScript who need structured guidance for database schema creation and validation. It is particularly useful for teams working on scalable applications that require consistent data modeling, efficient indexing, and maintainable schema evolution practices. Common use cases include task management systems, messaging platforms, analytics dashboards, ecommerce order management, and applications that rely on typed relational references between database tables.
The skill includes validators for strings, numbers, booleans, null values, bigint values, arrays, objects, optional fields, unions, literals, records, IDs, bytes, and unrestricted values using v.any().
Yes. The examples include single-field indexes, compound indexes, sorting indexes, and full-text search indexes using Convex schema configuration methods.
Yes. The schema examples and validator mappings are designed specifically for TypeScript and show the corresponding TypeScript types for each validator.
The content references migration strategies through the use of optional fields and unions, which can help support evolving schemas over time.
Yes. The examples demonstrate discriminated unions with literal type fields as well as nested object structures and arrays of objects.
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waynesutton/convexskills