convex-schema-validator
About
This skill helps developers define and validate database schemas for Convex applications with proper TypeScript typing and index configuration. It supports optional fields, unions, and provides strategies for handling schema migrations. Use it to ensure data integrity and manage schema evolution in your Convex backend.
Quick Install
Claude Code
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Documentation
Convex Schema Validator
Define and validate database schemas in Convex with proper typing, index configuration, optional fields, unions, and strategies for schema migrations.
Documentation Sources
Before implementing, do not assume; fetch the latest documentation:
- Primary: https://docs.convex.dev/database/schemas
- Indexes: https://docs.convex.dev/database/indexes
- Data Types: https://docs.convex.dev/database/types
- For broader context: https://docs.convex.dev/llms.txt
Instructions
Basic Schema Definition
// convex/schema.ts
import { defineSchema, defineTable } from "convex/server";
import { v } from "convex/values";
export default defineSchema({
users: defineTable({
name: v.string(),
email: v.string(),
avatarUrl: v.optional(v.string()),
createdAt: v.number(),
}),
tasks: defineTable({
title: v.string(),
description: v.optional(v.string()),
completed: v.boolean(),
userId: v.id("users"),
priority: v.union(
v.literal("low"),
v.literal("medium"),
v.literal("high")
),
}),
});
Validator Types
| Validator | TypeScript Type | Example |
|---|---|---|
v.string() | string | "hello" |
v.number() | number | 42, 3.14 |
v.boolean() | boolean | true, false |
v.null() | null | null |
v.int64() | bigint | 9007199254740993n |
v.bytes() | ArrayBuffer | Binary data |
v.id("table") | Id<"table"> | Document reference |
v.array(v) | T[] | [1, 2, 3] |
v.object({}) | { ... } | { name: "..." } |
v.optional(v) | T | undefined | Optional field |
v.union(...) | T1 | T2 | Multiple types |
v.literal(x) | "x" | Exact value |
v.any() | any | Any value |
v.record(k, v) | Record<K, V> | Dynamic keys |
Index Configuration
export default defineSchema({
messages: defineTable({
channelId: v.id("channels"),
authorId: v.id("users"),
content: v.string(),
sentAt: v.number(),
})
// Single field index
.index("by_channel", ["channelId"])
// Compound index
.index("by_channel_and_author", ["channelId", "authorId"])
// Index for sorting
.index("by_channel_and_time", ["channelId", "sentAt"]),
// Full-text search index
articles: defineTable({
title: v.string(),
body: v.string(),
category: v.string(),
})
.searchIndex("search_content", {
searchField: "body",
filterFields: ["category"],
}),
});
Complex Types
export default defineSchema({
// Nested objects
profiles: defineTable({
userId: v.id("users"),
settings: v.object({
theme: v.union(v.literal("light"), v.literal("dark")),
notifications: v.object({
email: v.boolean(),
push: v.boolean(),
}),
}),
}),
// Arrays of objects
orders: defineTable({
customerId: v.id("users"),
items: v.array(v.object({
productId: v.id("products"),
quantity: v.number(),
price: v.number(),
})),
status: v.union(
v.literal("pending"),
v.literal("processing"),
v.literal("shipped"),
v.literal("delivered")
),
}),
// Record type for dynamic keys
analytics: defineTable({
date: v.string(),
metrics: v.record(v.string(), v.number()),
}),
});
Discriminated Unions
export default defineSchema({
events: defineTable(
v.union(
v.object({
type: v.literal("user_signup"),
userId: v.id("users"),
email: v.string(),
}),
v.object({
type: v.literal("purchase"),
userId: v.id("users"),
orderId: v.id("orders"),
amount: v.number(),
}),
v.object({
type: v.literal("page_view"),
sessionId: v.string(),
path: v.string(),
})
)
).index("by_type", ["type"]),
});
Optional vs Nullable Fields
export default defineSchema({
items: defineTable({
// Optional: field may not exist
description: v.optional(v.string()),
// Nullable: field exists but can be null
deletedAt: v.union(v.number(), v.null()),
// Optional and nullable
notes: v.optional(v.union(v.string(), v.null())),
}),
});
Index Naming Convention
Always include all indexed fields in the index name:
export default defineSchema({
posts: defineTable({
authorId: v.id("users"),
categoryId: v.id("categories"),
publishedAt: v.number(),
status: v.string(),
})
// Good: descriptive names
.index("by_author", ["authorId"])
.index("by_author_and_category", ["authorId", "categoryId"])
.index("by_category_and_status", ["categoryId", "status"])
.index("by_status_and_published", ["status", "publishedAt"]),
});
Schema Migration Strategies
Adding New Fields
// Before
users: defineTable({
name: v.string(),
email: v.string(),
})
// After - add as optional first
users: defineTable({
name: v.string(),
email: v.string(),
avatarUrl: v.optional(v.string()), // New optional field
})
Backfilling Data
// convex/migrations.ts
import { internalMutation } from "./_generated/server";
import { v } from "convex/values";
export const backfillAvatars = internalMutation({
args: {},
returns: v.number(),
handler: async (ctx) => {
const users = await ctx.db
.query("users")
.filter((q) => q.eq(q.field("avatarUrl"), undefined))
.take(100);
for (const user of users) {
await ctx.db.patch(user._id, {
avatarUrl: `https://api.dicebear.com/7.x/initials/svg?seed=${user.name}`,
});
}
return users.length;
},
});
Making Optional Fields Required
// Step 1: Backfill all null values
// Step 2: Update schema to required
users: defineTable({
name: v.string(),
email: v.string(),
avatarUrl: v.string(), // Now required after backfill
})
Examples
Complete E-commerce Schema
// convex/schema.ts
import { defineSchema, defineTable } from "convex/server";
import { v } from "convex/values";
export default defineSchema({
users: defineTable({
email: v.string(),
name: v.string(),
role: v.union(v.literal("customer"), v.literal("admin")),
createdAt: v.number(),
})
.index("by_email", ["email"])
.index("by_role", ["role"]),
products: defineTable({
name: v.string(),
description: v.string(),
price: v.number(),
category: v.string(),
inventory: v.number(),
isActive: v.boolean(),
})
.index("by_category", ["category"])
.index("by_active_and_category", ["isActive", "category"])
.searchIndex("search_products", {
searchField: "name",
filterFields: ["category", "isActive"],
}),
orders: defineTable({
userId: v.id("users"),
items: v.array(v.object({
productId: v.id("products"),
quantity: v.number(),
priceAtPurchase: v.number(),
})),
total: v.number(),
status: v.union(
v.literal("pending"),
v.literal("paid"),
v.literal("shipped"),
v.literal("delivered"),
v.literal("cancelled")
),
shippingAddress: v.object({
street: v.string(),
city: v.string(),
state: v.string(),
zip: v.string(),
country: v.string(),
}),
createdAt: v.number(),
updatedAt: v.number(),
})
.index("by_user", ["userId"])
.index("by_user_and_status", ["userId", "status"])
.index("by_status", ["status"]),
reviews: defineTable({
productId: v.id("products"),
userId: v.id("users"),
rating: v.number(),
comment: v.optional(v.string()),
createdAt: v.number(),
})
.index("by_product", ["productId"])
.index("by_user", ["userId"]),
});
Using Schema Types in Functions
// convex/products.ts
import { query, mutation } from "./_generated/server";
import { v } from "convex/values";
import { Doc, Id } from "./_generated/dataModel";
// Use Doc type for full documents
type Product = Doc<"products">;
// Use Id type for references
type ProductId = Id<"products">;
export const get = query({
args: { productId: v.id("products") },
returns: v.union(
v.object({
_id: v.id("products"),
_creationTime: v.number(),
name: v.string(),
description: v.string(),
price: v.number(),
category: v.string(),
inventory: v.number(),
isActive: v.boolean(),
}),
v.null()
),
handler: async (ctx, args): Promise<Product | null> => {
return await ctx.db.get(args.productId);
},
});
Best Practices
- Never run
npx convex deployunless explicitly instructed - Never run any git commands unless explicitly instructed
- Always define explicit schemas rather than relying on inference
- Use descriptive index names that include all indexed fields
- Start with optional fields when adding new columns
- Use discriminated unions for polymorphic data
- Validate data at the schema level, not just in functions
- Plan index strategy based on query patterns
Common Pitfalls
- Missing indexes for queries - Every withIndex needs a corresponding schema index
- Wrong index field order - Fields must be queried in order defined
- Using v.any() excessively - Lose type safety benefits
- Not making new fields optional - Breaks existing data
- Forgetting system fields - _id and _creationTime are automatic
References
- Convex Documentation: https://docs.convex.dev/
- Convex LLMs.txt: https://docs.convex.dev/llms.txt
- Schemas: https://docs.convex.dev/database/schemas
- Indexes: https://docs.convex.dev/database/indexes
- Data Types: https://docs.convex.dev/database/types
GitHub Repository
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