convex-schema-validator▌
waynesutton/convexskills · updated Apr 8, 2026
Type-safe database schema definition with indexes, validation, and migration strategies for Convex.
- ›Supports 13+ validator types including strings, numbers, booleans, document references, arrays, objects, unions, and discriminated unions for flexible data modeling
- ›Enables single-field and compound indexes plus full-text search indexes for optimized query performance
- ›Provides optional and nullable field patterns with clear migration paths for adding required fields and backfilling dat
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
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.4★★★★★33 reviews- ★★★★★Dhruvi Jain· Dec 28, 2024
Registry listing for convex-schema-validator matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Arjun Smith· Dec 12, 2024
convex-schema-validator reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Chen Harris· Dec 12, 2024
Solid pick for teams standardizing on skills: convex-schema-validator is focused, and the summary matches what you get after install.
- ★★★★★Arya Rao· Dec 8, 2024
I recommend convex-schema-validator for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Pratham Ware· Dec 4, 2024
convex-schema-validator has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Harper White· Nov 27, 2024
Keeps context tight: convex-schema-validator is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Oshnikdeep· Nov 19, 2024
convex-schema-validator reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Nikhil Taylor· Nov 11, 2024
convex-schema-validator has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Arjun Mehta· Nov 3, 2024
Registry listing for convex-schema-validator matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Arjun Khan· Oct 22, 2024
Keeps context tight: convex-schema-validator is the kind of skill you can hand to a new teammate without a long onboarding doc.
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